20.7.2 Lungs, and Lung Cancer Image Analysis

Chapter Contents (Back)
Lungs. Lung Cancer. Medical, Applications.
See also Pulmonary Nodules, Lung Nodules.
See also Airway Tree Structure.
See also Emphysema, Lung Analysis.
See also Bronchoscopy Systems, Bronchial Analysis.
See also Lung Motion Analysis, Respiration, Breathing.

Sutton, R.N., Hall, E.L.,
Texture Measures for Automatic Classification of Pulmonary Disease,
TC(21), No. 7, July 1972, pp. 667-676. BibRef 7207

Roellinger, Jr., F.X., Kahveci, A.E., Chang, J.K., Harlow, C.A., Dwyer, III, S.J., Lodwick, G.S.,
Computer Analysis of Chest Radiographs,
CGIP(2), 1973, pp. 232-251. BibRef 7300

Toriwaki, J.I., Suenaga, Y., Negoro, T., Fukumura, T.,
Pattern Recognition of Chest X-Ray Images,
CGIP(2), 1973, pp. 252-271. BibRef 7300

Chien, Y.P., Fu, K.S.,
Recognition of X-Ray Picture Patterns,
SMC(4), 1974, pp. 145-156. BibRef 7400

Ballard, D.M., and Sklansky, J.,
A Ladder-Structured Decision Tree for Recognizing Tumors in Chest Radiographs,
TC(25), No. 5, May 1976, pp. 503-513. BibRef 7605

Cocklin, M.L., Gourlay, A.R., Jackson, P.H., Kaye, G., Kerr, I.H., Lams, P.,
Digital Processing of Chest Radiographs,
IVC(1), No. 2, May 1983, pp. 67-78.
Elsevier DOI BibRef 8305

Pahlplatz, M.M.M., Katzko, M.W., Hesselmans, G.H.F.M., Oud, P.S., Vooys, G.P.,
Two Methods for Analyzing Pleural Smears for the Presence of Abnormalities,
PRL(4), 1986, pp. 405-411. BibRef 8600

Pan, T.S.[Tin Su], King, M.A., de Vries, D.J., Ljungberg, M.,
Correction to 'Segmentation of the Body and Lungs from Compton Scatter and Photopeak Window Data,
MedImg(15), No. 3, June 1996, pp. 394.
IEEE Top Reference. 0203
BibRef

Hasegawa, A., Lo, S.C.B., Lin, J.S., Freedman, M.T., Mun, S.K.,
A Shift-Invariant Neural Network for the Lung Field Segmentation in Chest Radiography,
VLSIVideo(18), No. 3, April 1998, pp. 241-250. 9806
BibRef

Hu, S., Hoffman, E.A., Reinhardt, J.M.,
Automatic lung segmentation for accurate quantitation of volumetric X-ray CT images,
MedImg(20), No. 6, June 2001, pp. 490-498.
IEEE Top Reference. 0110
BibRef

Zhang, L., Hoffman, E.A., Reinhardt, J.M.,
Atlas-Driven Lung Lobe Segmentation in Volumetric X-Ray CT Images,
MedImg(25), No. 1, January 2006, pp. 1-16.
IEEE DOI 0601
BibRef

Ukil, S., Reinhardt, J.M.,
Anatomy-Guided Lung Lobe Segmentation in X-Ray CT Images,
MedImg(28), No. 2, February 2009, pp. 202-214.
IEEE DOI 0902
BibRef

Cao, K.[Kunlin], Ding, K.[Kai], Christensen, G.E.[Gary E.], Raghavan, M.L.[Madhavan L.], Amelon, R.E.[Ryan E.], Reinhardt, J.M.[Joseph M.],
Unifying Vascular Information in Intensity-Based Nonrigid Lung CT Registration,
WBIR10(1-12).
Springer DOI 1007
BibRef

Blechschmidt, R.A., Werthschutzky, R., Lorcher, U.,
Automated CT image evaluation of the lung: a morphology-based concept,
MedImg(20), No. 5, May 2001, pp. 434-442.
IEEE Top Reference. 0110
BibRef

van Ginneken, B., ter Haar Romeny, B.M., Viergever, M.A.,
Computer-aided diagnosis in chest radiography: a survey,
MedImg(20), No. 12, December 2001, pp. 1228-1241.
IEEE Top Reference. 0201
Survey, Radiography. BibRef

van Ginneken, B.[Bram], Katsuragawa, S., ter Haar Romeny, B.M., Doi, K.[Kunio], Viergever, M.A.,
Automatic detection of abnormalities in chest radiographs using local texture analysis,
MedImg(21), No. 2, February 2002, pp. 139-149.
IEEE Top Reference. 0204
BibRef

Fan, L.X.[Lie-Xiang], Santago, P., Jiang, H.[Huai], Herrington, D.M.,
Ultrasound measurement of brachial flow-mediated vasodilator response,
MedImg(19), No. 6, June 2000, pp. 621-631.
IEEE Top Reference. 0110
BibRef

Frerichs, I., Hinz, J., Herrmann, P., Weisser, G., Hahn, G., Quintel, M., Hellige, G.,
Regional lung perfusion as determined by electrical impedance tomography in comparison with electron beam ct imaging,
MedImg(21), No. 6, June 2002, pp. 646-652.
IEEE Top Reference. 0208
BibRef

Lee, Z.H.[Zheng-Hong], Berridge, M.S.,
PET imaging-based evaluation of aerosol drugs and their delivery devices: nasal and pulmonary studies,
MedImg(21), No. 10, October 2002, pp. 1324-1331.
IEEE Top Reference. 0301
BibRef

Sonka, M., Liang, W.D.[Wei-Dong], Lauer, R.M.,
Automated analysis of brachial ultrasound image sequences: early detection of cardiovascular disease via surrogates of endothelial function,
MedImg(21), No. 10, October 2002, pp. 1271-1279.
IEEE Top Reference. 0301
BibRef

Koning, G., Tuinenburg, J.C., Hekking, E., Peelen, J., van Weert, A.W.M., Bergkamp, D., Goedhart, B., Reiber, J.H.C.,
A novel measurement technique to assess the effects of coronary brachytherapy in clinical trials,
MedImg(21), No. 10, October 2002, pp. 1254-1263.
IEEE Top Reference. 0301
BibRef

Masutani, Y., MacMahon, H., Doi, K.[Kunio],
Computerized detection of pulmonary embolism in spiral CT angiography based on volumetric image analysis,
MedImg(21), No. 12, December 2002, pp. 1517-1523.
IEEE Top Reference. 0301
BibRef

Ray, N., Acton, S.T., Altes, T., de Lange, E.E., Brookeman, J.R.,
Merging parametric active contours within homogeneous image regions for MRI-based lung segmentation,
MedImg(22), No. 2, February 2003, pp. 189-199.
IEEE Top Reference. 0304
BibRef

Ray, N., Acton, S.T., Altes, T., de Lange, E.E.,
MRI Ventilation Analysis by Merging Parametric Active Contours,
ICIP01(II: 861-864).
IEEE DOI 0108
BibRef

Behrens, T., Rohr, K.[Karl], Stiehl, H.S.[H. Siegfried],
Robust segmentation of tubular structures in 3-D medical images by parametric object detection and tracking,
SMC-B(33), No. 4, August 2003, pp. 554-561.
IEEE Abstract. 0308
BibRef
Earlier:
Using an Extended Hough Transform Combined with a Kalman Filter to Segment Tubular Structures in 3-D Medical Images,
VMV01(xx-yy).
PDF File. 0209
BibRef

Jiang, M.[Ming], Ji, Q.A.[Qi-Ang], McEwen, B.F.[Bruce F.],
Automated Extraction of Fine Features of Kinetochore Microtubules and Plus-Ends From Electron Tomography Volume,
IP(15), No. 7, July 2006, pp. 2035-2048.
IEEE DOI 0606
BibRef
Earlier:
Automated Extraction of Microtubules and Their Plus-Ends,
WACV05(I: 336-341).
IEEE DOI 0502
BibRef

Liang, L.C.[Li-Chen], Ji, Q.A.[Qi-Ang], McEwen, B.F.,
Extraction of 3d microtubules axes from cellular electron tomography images,
ICPR02(I: 804-807).
IEEE DOI 0211
BibRef

Luo, H., Luo, J.,
Robust Online Orientation Correction for Radiographs in PACS Environments,
MedImg(25), No. 10, October 2006, pp. 1370-1379.
IEEE DOI 0609
BibRef

Singh, V.[Vikas], Mukherjee, L.[Lopamudra], Xu, J.H.[Jin-Hui], Hoffmann, K.R., Dinu, P.M., Podgorsak, M.,
Brachytherapy Seed Localization Using Geometric and Linear Programming Techniques,
MedImg(26), No. 9, September 2007, pp. 1291-1304.
IEEE DOI 0710
BibRef

Mukherjee, L.[Lopamudra], Singh, V.[Vikas], Peng, J.M.[Ji-Ming], Xu, J.H.[Jin-Hui], Zeitz, M.J.[Michael J.], Berezney, R.[Ronald],
Generalized Median Graphs: Theory and Applications,
ICCV07(1-8).
IEEE DOI 0710
BibRef

Miller, G.W., Carl, M., Mata, J.F., Cates, Jr., G.D., Mugler, III, J.P.,
Simulations of Short-Time Diffusivity in Lung Airspaces and Implications for S/V Measurements Using Hyperpolarized-Gas MRI,
MedImg(26), No. 11, November 2007, pp. 1456-1463.
IEEE DOI 0709
BibRef

Lohscheller, J., Eysholdt, U., Toy, H., Dollinger, M.,
Phonovibrography: Mapping High-Speed Movies of Vocal Fold Vibrations Into 2-D Diagrams for Visualizing and Analyzing the Underlying Laryngeal Dynamics,
MedImg(27), No. 3, March 2008, pp. 300-309.
IEEE DOI 0803
BibRef

Luegmair, G., Mehta, D.D., Kobler, J.B., Dollinger, M.,
Three-Dimensional Optical Reconstruction of Vocal Fold Kinematics Using High-Speed Video With a Laser Projection System,
MedImg(34), No. 12, December 2015, pp. 2572-2582.
IEEE DOI 1601
biomechanics BibRef

Luegmair, G., Kniesburges, S., Zimmermann, M., Sutor, A., Eysholdt, U., Dollinger, M.,
Optical Reconstruction of High-Speed Surface Dynamics in an Uncontrollable Environment,
MedImg(29), No. 12, December 2010, pp. 1979-1991.
IEEE DOI 1101
BibRef

Shi, Y., Qi, F., Xue, Z., Chen, L., Ito, K., Matsuo, H., Shen, D.,
Segmenting Lung Fields in Serial Chest Radiographs Using Both Population-Based and Patient-Specific Shape Statistics,
MedImg(27), No. 4, April 2008, pp. 481-494.
IEEE DOI 0804
BibRef

Smal, I., Draegestein, K., Galjart, N., Niessen, W.J., Meijering, E.H.W.,
Particle Filtering for Multiple Object Tracking in Dynamic Fluorescence Microscopy Images: Application to Microtubule Growth Analysis,
MedImg(27), No. 6, June 2008, pp. 789-804.
IEEE DOI 0711
BibRef

Ramachandran, J., Pattichis, M.S., Soliz, P.,
Pre-classification of chest radiographs for improved active shape model segmentation of ribs,
Southwest02(188-192).
IEEE Top Reference. 0208
BibRef

Pattichis, M.S., Muralidharan, H., Pattichis, C.S., Soliz, P.,
New image processing models for opacity image analysis in chest radiographs,
Southwest02(260-264).
IEEE Top Reference. 0208
BibRef

Malik, A.S.[Aamir Saeed], Choi, T.S.[Tae-Sun],
Differentiating Honeycombed Images from Normal HRCT Lung Images,
IEICE(E92-D), No. 5, May 2009, pp. 1218-1221.
WWW Link. 0907
BibRef
Earlier:
Multiscale Segmentation of HRCT Images Using Bipolar Incoherent Filtering,
ISVC05(76-83).
Springer DOI 0512
BibRef

Bouma, H., Sonnemans, J.J., Vilanova, A., Gerritsen, F.A.,
Automatic Detection of Pulmonary Embolism in CTA Images,
MedImg(28), No. 8, August 2009, pp. 1223-1230.
IEEE DOI 0909
BibRef

Elizabeth, D.S.[D. Shiloah], Kannan, A., Nehemiah, H.K.[H. Khanna],
Computer-aided diagnosis system for the detection of bronchiectasis in chest computed tomography images,
IJIST(19), No. 4, December 2009, pp. 290-298.
DOI Link 0912
BibRef

Elizabeth, D.S., Nehemiah, H.K., Retmin Raj, C.S., Kannan, A.,
Computer-aided diagnosis of lung cancer based on analysis of the significant slice of chest computed tomography image,
IET-IPR(6), No. 6, 2012, pp. 697-705.
DOI Link 1210
BibRef

Huysmans, T.[Toon], Sijbers, J.[Jan], Brigitte, V.[Verdonk],
Automatic Construction of Correspondences for Tubular Surfaces,
PAMI(32), No. 4, April 2010, pp. 636-651.
IEEE DOI 1003
Obtain correspondences for tubular shapes. MDL used to optimize parameterization. BibRef

Pinho, R.[Romulo], Sijbers, J.[Jan], Huysmans, T.[Toon],
Segmentation of the Human Trachea Using Deformable Statistical Models of Tubular Shapes,
ACIVS07(531-542).
Springer DOI 0708
BibRef

van Rikxoort, E.M., Prokop, M., de Hoop, B., Viergever, M.A., Pluim, J.P.W., van Ginneken, B.,
Automatic Segmentation of Pulmonary Lobes Robust Against Incomplete Fissures,
MedImg(29), No. 6, June 2010, pp. 1286-1296.
IEEE DOI 1007
BibRef

Lassen, B., van Rikxoort, E.M., Schmidt, M., Kerkstra, S., van Ginneken, B., Kuhnigk, J.M.,
Automatic Segmentation of the Pulmonary Lobes From Chest CT Scans Based on Fissures, Vessels, and Bronchi,
MedImg(32), No. 2, February 2013, pp. 210-222.
IEEE DOI 1301
BibRef

Dawoud, A.[Amer],
Lung segmentation in chest radiographs by fusing shape information in iterative thresholding,
IET-CV(5), No. 3, 2011, pp. 185-190.
DOI Link 1106
BibRef
Earlier:
Fusing Shape Information in Lung Segmentation in Chest Radiographs,
ICIAR10(II: 70-78).
Springer DOI 1006
BibRef

Feulner, J., Zhou, S.K., Hammon, M., Seifert, S., Huber, M., Comaniciu, D., Hornegger, J., Cavallaro, A.,
A Probabilistic Model for Automatic Segmentation of the Esophagus in 3-D CT Scans,
MedImg(30), No. 6, June 2011, pp. 1252-1264.
IEEE DOI 1101
BibRef

Yang, Q.[Qian], Karpikov, A.[Alexander], Toomre, D.[Derek], Duncan, J.S.[James S.],
3-D Reconstruction of Microtubules From Multi-Angle Total Internal Reflection Fluorescence Microscopy Using Bayesian Framework,
IP(20), No. 8, August 2011, pp. 2248-2259.
IEEE DOI 1108
BibRef
Earlier:
3-D reconstruction and measurement of microtubules from multiple angle-total internal reflection fluorescence microscopy,
MMBIA09(172-177).
IEEE DOI 0906
BibRef

Massoptier, L.[Laurent], Misra, A.[Avishkar], Sowmya, A.[Arcot], Casciaro, S.[Sergio],
Combining Graph-cut Technique And Anatomical Knowledge For Automatic Segmentation Of Lungs Affected By Diffuse Parenchymal Disease In Hrct Images,
IJIG(11), No. 4, October 2011, pp. 509-529.
DOI Link 1201
BibRef

Sorensen, L., Nielsen, M., Lo, P.[Pechin], Ashraf, H., Pedersen, J.H., de Bruijne, M.,
Texture-Based Analysis of COPD: A Data-Driven Approach,
MedImg(31), No. 1, January 2012, pp. 70-78.
IEEE DOI 1201
BibRef

Sun, S., Bauer, C., Beichel, R.,
Automated 3-D Segmentation of Lungs With Lung Cancer in CT Data Using a Novel Robust Active Shape Model Approach,
MedImg(31), No. 2, February 2012, pp. 449-460.
IEEE DOI 1202
BibRef

Zhang, Y.[Yu], Wu, G.R.[Guo-Rong], Yap, P.T.[Pew-Thian], Feng, Q.J.[Qian-Jin], Lian, J.[Jun], Chen, W.F.[Wu-Fan], Shen, D.G.[Ding-Gang],
Hierarchical Patch-Based Sparse Representation: A New Approach for Resolution Enhancement of 4D-CT Lung Data,
MedImg(31), No. 11, November 2012, pp. 1993-2005.
IEEE DOI 1211
BibRef
Earlier:
Reconstruction of super-resolution lung 4D-CT using patch-based sparse representation,
CVPR12(925-931).
IEEE DOI 1208
BibRef

Wang, Z.S.[Zhen-Song], Wei, L.F.[Li-Fang], Wang, L.[Li], Gao, Y.Z.[Yao-Zong], Chen, W.F.[Wu-Fan], Shen, D.G.[Ding-Gang],
Hierarchical Vertex Regression-Based Segmentation of Head and Neck CT Images for Radiotherapy Planning,
IP(27), No. 2, February 2018, pp. 923-937.
IEEE DOI 1712
Biomedical imaging, Computed tomography, Deformable models, Image segmentation, Shape, Testing, Training, Image segmentation, vertex regression BibRef

Shao, Y.Q.[Ye-Qin], Gao, Y.Z.[Yao-Zong], Guo, Y.R.[Yan-Rong], Shi, Y.H.[Yong-Hong], Yang, X.[Xin], Shen, D.G.[Ding-Gang],
Hierarchical Lung Field Segmentation With Joint Shape and Appearance Sparse Learning,
MedImg(33), No. 9, September 2014, pp. 1761-1780.
IEEE DOI 1410
diagnostic radiography BibRef

Gu, Y.H.[Yu-Hua], Kumar, V.[Virendra], Hall, L.O.[Lawrence O.], Goldgof, D.B.[Dmitry B.], Li, C.Y.[Ching-Yen], Korn, R.[René], Bendtsen, C.[Claus], Velazquez, E.R.[Emmanuel Rios], Dekker, A.[Andre], Aerts, H.[Hugo], Lambin, P.[Philippe], Li, X.L.[Xiu-Li], Tian, J.[Jie], Gatenby, R.A.[Robert A.], Gillies, R.J.[Robert J.],
Automated delineation of lung tumors from CT images using a single click ensemble segmentation approach,
PR(46), No. 3, March 2013, pp. 692-702.
Elsevier DOI 1212
Image features; Delineation; Lung tumor; Lesion; CT; Region growing; Ensemble segmentation BibRef

Martins, A.L.D.[Ana L. D.], Mascarenhas, N.D.A.[Nelson D.A.],
Spatio-Temporal Resolution Enhancement of Vocal Tract MRI Sequences: A Comparison Among Wiener Filter Based Methods,
JMIV(45), No. 3, March 2013, pp. 200-213.
WWW Link. 1301
BibRef

Song, Y.[Yang], Cai, W.D.[Wei-Dong], Zhou, Y., Feng, D.D.[David Dagan],
Feature-Based Image Patch Approximation for Lung Tissue Classification,
MedImg(32), No. 4, April 2013, pp. 797-808.
IEEE DOI 1304
BibRef

Zhang, F.[Fan], Song, Y.[Yang], Cai, W.D.[Wei-Dong], Zhou, Y.[Yun], Shan, S.M.[Shi-Min], Feng, D.D.[D. Dagan],
Context Curves for Classification of Lung Nodule Images,
DICTA13(1-7)
IEEE DOI 1402
computerised tomography BibRef

Song, Y.[Yang], Li, Q.[Qing], Huang, H.[Heng], Feng, D.[Dagan], Chen, M.[Mei], Cai, W.D.[Wei-Dong],
Low Dimensional Representation of Fisher Vectors for Microscopy Image Classification,
MedImg(36), No. 8, August 2017, pp. 1636-1649.
IEEE DOI 1708
BibRef
Earlier:
Histopathology Image Categorization with Discriminative Dimension Reduction of Fisher Vectors,
BioImage16(I: 306-317).
Springer DOI 1611
Biomarkers, Biomedical imaging, Breast cancer, Feature extraction, Microscopy, Fisher vector, dimensionality reduction, discriminative learning, feature, learning BibRef

Song, Y.[Yang], Cai, W.D.[Wei-Dong], Eberl, S.[Stefan], Fulham, M.J.[Michael J.], Feng, D.D.[David Dagan],
Structure-Adaptive Feature Extraction and Representation for Multi-modality Lung Images Retrieval,
DICTA10(152-157).
IEEE DOI 1012
BibRef

Song, Y.[Yang], Cai, W.D.[Wei-Dong], Feng, D.D.,
Microscopic Image Segmentation with Two-Level Enhancement of Feature Discriminability,
DICTA12(1-6).
IEEE DOI 1303
BibRef

Xu, R.[Rui], Hirano, Y.S.[Yasu-Shi], Tachibana, R.[Rie], Kido, S.[Shoji],
A Bag-of-Features Approach to Classify Six Types of Pulmonary Textures on High-Resolution Computed Tomography,
IEICE(E96-D), No. 4, April 2013, pp. 845-855.
WWW Link. 1304
BibRef

Heinrich, M.P.[Mattias P.], Jenkinson, M.[Mark], Brady, M.[Michael], Schnabel, J.A.[Julia A.],
MRF-Based Deformable Registration and Ventilation Estimation of Lung CT,
MedImg(32), No. 7, 2013, pp. 1239-1248.
IEEE DOI 1307
Markov processes BibRef

Heinrich, M.P.[Mattias P.], Papiez, B.W.[Bartlomiej W.], Schnabel, J.A.[Julia A.], Handels, H.[Heinz],
Non-parametric Discrete Registration with Convex Optimisation,
WBIR14(51-61).
Springer DOI 1407
BibRef

Degen, J., Heinrich, M.P.[Mattias P.],
Multi-Atlas Based Pseudo-CT Synthesis Using Multimodal Image Registration and Local Atlas Fusion Strategies,
WBIR16(600-608)
IEEE DOI 1612
BibRef

Heinrich, M.P.[Mattias P.], Jenkinson, M.[Mark], Gleeson, F.V.[Fergus V.], Brady, S.M.[Sir Michael], Schnabel, J.A.[Julia A.],
Deformable multimodal registration with gradient orientation based on structure tensors,
BMVA(2011), No. 2, 2011, pp. 1-11.
PDF File. 1209
BibRef

Cahill, N.D.[Nathan D.], Schnabel, J.A.[Julia A.], Noble, J.A.[J. Alison], Hawkes, D.J.[David J.],
Revisiting overlap invariance in medical image alignment,
Tensor08(1-8).
IEEE DOI 0806
BibRef

Edwards, P.J., Hill, D.L.G., Little, J.A., Sahni, V.A.S., Hawkes, D.J.,
Medical Image Registration Incorporating Deformations,
BMVC95(xx-yy).
PDF File. 9509
BibRef

Wang, C.W.[Ching-Wei], Yu, C.P.[Cheng-Ping],
Automated morphological classification of lung cancer subtypes using H&E tissue images,
MVA(24), No. 7, October 2013, pp. 1383-1391.
WWW Link. 1309
BibRef

Candemir, S., Jaeger, S., Palaniappan, K., Musco, J.P., Singh, R.K., Xue, Z.Y.[Zhi-Yun], Karargyris, A., Antani, S., Thoma, G., McDonald, C.J.,
Lung Segmentation in Chest Radiographs Using Anatomical Atlases With Nonrigid Registration,
MedImg(33), No. 2, February 2014, pp. 577-590.
IEEE DOI 1403
Radon transforms BibRef

Devan, L.[Lakshmi], Santosham, R.[Roy], Hariharan, R.[Ranganathan],
Automated texture-based characterization of fibrosis and carcinoma using low-dose lung CT images,
IJIST(24), No. 1, 2014, pp. 39-44.
DOI Link 1403
artificial neural network BibRef

Mansoor, A., Bagci, U., Xu, Z.Y.[Zi-Yue], Foster, B., Olivier, K.N., Elinoff, J.M., Suffredini, A.F., Udupa, J.K., Mollura, D.J.,
A Generic Approach to Pathological Lung Segmentation,
MedImg(33), No. 12, December 2014, pp. 2293-2310.
IEEE DOI 1412
BibRef
And: Correction: MedImg(34), No. 1, January 2015, pp. 354-354.
IEEE DOI 1502
Computed tomography; Fuzzy set theory; Image segmentation;Lungs BibRef

Kecheril, S.S.[S. Sajith], Venkataraman, D., Suganthi, J., Sujathan, K.,
Automated lung cancer detection by the analysis of glandular cells in sputum cytology images using scale space features,
SIViP(9), No. 4, May 2015, pp. 851-863.
Springer DOI 1504
BibRef

Philipsen, R.H.H.M., Maduskar, P., Hogeweg, L., Melendez, J., Sanchez, C.I., van Ginneken, B.,
Localized Energy-Based Normalization of Medical Images: Application to Chest Radiography,
MedImg(34), No. 9, September 2015, pp. 1965-1975.
IEEE DOI 1509
Biomedical imaging BibRef

Ju, W.[Wei], Xiang, D.[Deihui], Zhang, B.[Bin], Wang, L.R.[Li-Rong], Kopriva, I., Chen, X.J.[Xin-Jian],
Random Walk and Graph Cut for Co-Segmentation of Lung Tumor on PET-CT Images,
IP(24), No. 12, December 2015, pp. 5854-5867.
IEEE DOI 1512
BibRef
Earlier: Correction: IP(25), No. 3, March 2016, pp. 1192-1192.
IEEE DOI 1602
Atomic beams; Lungs; Tumors. computerised tomography BibRef

Chong, D.Y., Kim, H.J., Lo, P., Young, S., McNitt-Gray, M.F., Abtin, F., Goldin, J.G., Brown, M.S.,
Robustness-Driven Feature Selection in Classification of Fibrotic Interstitial Lung Disease Patterns in Computed Tomography Using 3D Texture Features,
MedImg(35), No. 1, January 2016, pp. 144-157.
IEEE DOI 1601
Computed tomography BibRef

Hurtado, D.E., Villarroel, N., Retamal, J., Bugedo, G., Bruhn, A.,
Improving the Accuracy of Registration-Based Biomechanical Analysis: A Finite Element Approach to Lung Regional Strain Quantification,
MedImg(35), No. 2, February 2016, pp. 580-588.
IEEE DOI 1602
Approximation methods BibRef

Anthimopoulos, M., Christodoulidis, S., Ebner, L., Christe, A., Mougiakakou, S.,
Lung Pattern Classification for Interstitial Lung Diseases Using a Deep Convolutional Neural Network,
MedImg(35), No. 5, May 2016, pp. 1207-1216.
IEEE DOI 1605
Computed tomography BibRef

Xiao, C., Stoel, B.C., Bakker, M.E., Peng, Y., Stolk, J., Staring, M.,
Pulmonary Fissure Detection in CT Images Using a Derivative of Stick Filter,
MedImg(35), No. 6, June 2016, pp. 1488-1500.
IEEE DOI 1606
Computed tomography BibRef

Islam, M.S.[M. Sirajul], Kitchen, M.J.[Marcus J.],
GPU accelerated regional lung air volume measurements from phase contrast X-ray images,
RealTimeIP(12), No. 1, June 2016, pp. 43-54.
WWW Link. 1606
BibRef

Semmler, M., Kniesburges, S., Birk, V., Ziethe, A., Patel, R., Döllinger, M.,
3D Reconstruction of Human Laryngeal Dynamics Based on Endoscopic High-Speed Recordings,
MedImg(35), No. 7, July 2016, pp. 1615-1624.
IEEE DOI 1608
biomedical optical imaging BibRef

Procházka, A.[Aleš], Kuchynka, J.[Jirí], Vyšata, O.[Oldrich], Schätz, M.[Martin], Yadollahi, M.[Mohammadreza], Sanei, S.[Saeid], Vališ, M.[Martin],
Sleep scoring using polysomnography data features,
SIViP(12), No. 6, September 2018, pp. 1043-1051.
Springer DOI 1808
BibRef

van Tulder, G.[Gijs], de Bruijne, M.[Marleen],
Combining Generative and Discriminative Representation Learning for Lung CT Analysis With Convolutional Restricted Boltzmann Machines,
MedImg(35), No. 5, May 2016, pp. 1262-1272.
IEEE DOI 1605
BibRef
Earlier:
Learning Features for Tissue Classification with the Classification Restricted Boltzmann Machine,
MCV14(47-58).
Springer DOI 1501
Computed tomography BibRef

van Tulder, G.[Gijs], de Bruijne, M.[Marleen],
Learning Cross-Modality Representations From Multi-Modal Images,
MedImg(38), No. 2, February 2019, pp. 638-648.
IEEE DOI 1902
BibRef
Earlier:
Representation Learning for Cross-Modality Classification,
MCV16(126-136).
Springer DOI 1711
Magnetic resonance imaging, Biomedical imaging, Encoding, Decoding, Training, Image reconstruction, Computed tomography, deep learning BibRef

Bragman, F.J.S., McClelland, J.R., Jacob, J., Hurst, J.R., Hawkes, D.J.,
Pulmonary Lobe Segmentation With Probabilistic Segmentation of the Fissures and a Groupwise Fissure Prior,
MedImg(36), No. 8, August 2017, pp. 1650-1663.
IEEE DOI 1708
Biomedical imaging, Brain modeling, Image segmentation, Lungs, Probabilistic logic, Sociology, Statistics, Lobe segmentation, fissure segmentation, pulmonary, image, analysis BibRef

Muller, P.A.[Peter A.], Mueller, J.L.[Jennifer L.], Mellenthin, M.M.[Michelle M.],
Real-Time Implementation of Caldeórn's Method on Subject-Specific Domains,
MedImg(36), No. 9, September 2017, pp. 1868-1875.
IEEE DOI 1709
electric impedance imaging, EIT, lung, electrical impedance tomography, human thorax, BibRef

Anantrasirichai, N., Hayes, W., Allinovi, M., Bull, D., Achim, A.,
Line Detection as an Inverse Problem: Application to Lung Ultrasound Imaging,
MedImg(36), No. 10, October 2017, pp. 2045-2056.
IEEE DOI 1710
Inverse problems, Lungs, Noise measurement, Radon, Speckle, Transforms, Ultrasonic imaging, ADMM, Line detection, deconvolution, image restoration, inverse problem, sparsity regularisation, ultrasound BibRef

Mittal, A.[Ajay], Hooda, R.[Rahul], Sofat, S.[Sanjeev],
Lung field segmentation in chest radiographs: a historical review, current status, and expectations from deep learning,
IET-IPR(11), No. 11, November 2017, pp. 937-952.
DOI Link 1711
BibRef

Zhang, Y.K.[Yuan-Ke], Rong, J.Y.[Jun-Yan], Lu, H.B.[Hong-Bing], Xing, Y.X.[Yu-Xiang], Meng, J.[Jing],
Low-Dose Lung CT Image Restoration Using Adaptive Prior Features From Full-Dose Training Database,
MedImg(36), No. 12, December 2017, pp. 2510-2523.
IEEE DOI 1712
Computed tomography, Databases, Image restoration, Lungs, Principal component analysis, restoration BibRef

Gao, Y.F.[Yong-Feng], Liang, Z.R.[Zheng-Rong], Moore, W.[William], Zhang, H.[Hao], Pomeroy, M.J.[Marc J.], Ferretti, J.A.[John A.], Bilfinger, T.V.[Thomas V.], Ma, J.H.[Jian-Hua], Lu, H.B.[Hong-Bing],
A Feasibility Study of Extracting Tissue Textures From a Previous Full-Dose CT Database as Prior Knowledge for Bayesian Reconstruction of Current Low-Dose CT Images,
MedImg(38), No. 8, August 2019, pp. 1981-1992.
IEEE DOI 1908
Image reconstruction, Databases, Computed tomography, Radiology, Bayes methods, Image edge detection, Low dose CT, Bayesian image reconstruction BibRef

Yin, Y., Sedlaczek, O., Müller, B., Warth, A., González-Vallinas, M., Lahrmann, B., Grabe, N., Kauczor, H.U., Breuhahn, K., Vignon-Clementel, I.E., Drasdo, D.,
Tumor Cell Load and Heterogeneity Estimation From Diffusion-Weighted MRI Calibrated With Histological Data: an Example From Lung Cancer,
MedImg(37), No. 1, January 2018, pp. 35-46.
IEEE DOI 1801
biodiffusion, biomedical MRI, cancer, cellular biophysics, computerised tomography, deconvolution, image colour analysis, tumor cellularity BibRef

de Carvalho Filho, A.O.[Antonio Oseas], Corręa Silva, A.[Aristofanes], Cardoso de Paiva, A.[Anselmo], Acatauassú Nunes, R.[Rodolfo], Gattass, M.[Marcelo],
Classification of patterns of benignity and malignancy based on CT using topology-based phylogenetic diversity index and convolutional neural network,
PR(81), 2018, pp. 200-212.
Elsevier DOI 1806
Lung cancer, Phylogenetic diversity index, Convolutional neural network BibRef

Oluyide, O.M.[Oluwakorede M.], Tapamo, J.R.[Jules-Raymond], Viriri, S.[Serestina],
Automatic lung segmentation based on Graph Cut using a distance-constrained energy,
IET-CV(12), No. 5, August 2018, pp. 609-615.
DOI Link 1807
BibRef

Novikov, A.A., Lenis, D., Major, D., Hladuvka, J., Wimmer, M., Bühler, K.,
Fully Convolutional Architectures for Multiclass Segmentation in Chest Radiographs,
MedImg(37), No. 8, August 2018, pp. 1865-1876.
IEEE DOI 1808
Lung, Image segmentation, Heart, Task analysis, Biomedical imaging, Shape, Feature extraction, Lung segmentation, JSRT dataset BibRef

Netto, S.M.B., Bandeira Diniz, J.O., Silva, A.C., de Paiva, A.C., Nunes, R.A., Gattass, M.,
Modified Quality Threshold Clustering for Temporal Analysis and Classification of Lung Lesions,
IP(28), No. 4, April 2019, pp. 1813-1823.
IEEE DOI 1901
cancer, computerised tomography, feature extraction, image classification, lung, medical image processing, temporal analysis BibRef

Gradl, R., Morgan, K.S., Dierolf, M., Jud, C., Hehn, L., Günther, B., Möller, W., Kutschke, D., Yang, L., Stoeger, T., Pfeiffer, D., Gleich, B., Achterhold, K., Schmid, O., Pfeiffer, F.,
Dynamic In Vivo Chest X-ray Dark-Field Imaging in Mice,
MedImg(38), No. 2, February 2019, pp. 649-656.
IEEE DOI 1902
Lung, Gratings, Imaging, X-ray imaging, Diseases, Mice, Animal imaging, dark-field and phase-contrast X-ray methods, X-ray imaging BibRef

Li, X.M.[Xiao-Mei], Dong, X.P.[Xiao-Peng], Lian, J.[Jian], Zhang, Y.[Yan], Yu, J.M.[Jin-Ming],
Knockoff filter-based feature selection for discrimination of non-small cell lung cancer in CT image,
IET-IPR(13), No. 3, February 2019, pp. 543-548.
DOI Link 1903
BibRef

Zhou, B., Chen, A., Crawford, R., Dogdas, B., Goldmarcher, G.,
A Progressively-Trained Scale-Invariant and Boundary-Aware Deep Neural Network for the Automatic 3D Segmentation of Lung Lesions,
WACV19(1-10)
IEEE DOI 1904
computerised tomography, image segmentation, lung, medical image processing, neural nets, supervised learning, Training data BibRef

Eppenhof, K.A.J., Pluim, J.P.W.,
Pulmonary CT Registration Through Supervised Learning With Convolutional Neural Networks,
MedImg(38), No. 5, May 2019, pp. 1097-1105.
IEEE DOI 1905
Training, Image registration, Strain, Lung, Biomedical imaging, Computed tomography, Convolutional neural networks, machine learning BibRef

Salehinejad, H., Colak, E., Dowdell, T., Barfett, J., Valaee, S.,
Synthesizing Chest X-Ray Pathology for Training Deep Convolutional Neural Networks,
MedImg(38), No. 5, May 2019, pp. 1197-1206.
IEEE DOI 1905
X-ray imaging, Computed tomography, Biomedical imaging, Magnetic resonance imaging, Training, synthesized images BibRef

Bozorgtabar, B.[Behzad], Mahapatra, D.[Dwarikanath], von Teng, H.[Hendrik], Pollinger, A.[Alexander], Ebner, L.[Lukas], Thiran, J.P.[Jean-Phillipe], Reyes, M.[Mauricio],
Informative sample generation using class aware generative adversarial networks for classification of chest Xrays,
CVIU(184), 2019, pp. 57-65.
Elsevier DOI 1906
GAN, Active learning, Classification, Chest xray, Informative samples BibRef

Chen, G., Xiang, D., Zhang, B., Tian, H., Yang, X., Shi, F., Zhu, W., Tian, B., Chen, X.,
Automatic Pathological Lung Segmentation in Low-Dose CT Image Using Eigenspace Sparse Shape Composition,
MedImg(38), No. 7, July 2019, pp. 1736-1749.
IEEE DOI 1907
Shape, Lung, Image segmentation, Pathology, Computed tomography, Strain, discriminative appearance dictionary BibRef

Nezamabadi, K.[Kasra], Naseri, Z.[Zeinab], Abrishami Moghaddam, H.[Hamid], Modarresi, M.[Mohammadreza], Pak, N.[Neda], Mahdizade, M.[Mehrzad],
Lung HRCT pattern classification for cystic fibrosis using convolutional neural network,
SIViP(13), No. 6, September 2019, pp. 1225-1232.
Springer DOI 1908
BibRef

Liu, C.X.[Cai-Xia], Zhao, R.B.[Rui-Bin], Pang, M.Y.[Ming-Yong],
Lung segmentation based on random forest and multi-scale edge detection,
IET-IPR(13), No. 10, 22 August 2019, pp. 1745-1754.
DOI Link 1909
BibRef

Liu, Y.[Ying], Wang, H.[Haodong], Gu, Y.[Yue], Lv, X.H.[Xiao-Hong],
Image classification toward lung cancer recognition by learning deep quality model,
JVCIR(63), 2019, pp. 102570.
Elsevier DOI 1909
Image classification, Cancer recognition, Deep feature, CNN BibRef

Jin, Y.[Yan], Jiang, X.B.[Xiao-Ben], Wei, Z.K.[Zhen-Kun], Li, Y.[Yuan],
Chest X-ray image denoising method based on deep convolution neural network,
IET-IPR(13), No. 11, 19 September 2019, pp. 1970-1978.
DOI Link 1909
BibRef

Saad, M.[Maliazurina], Lee, I.H.[Ik Hyun], Choi, T.S.[Tae-Sun],
Automated delineation of non-small cell lung cancer: A step toward quantitative reasoning in medical decision science,
IJIST(29), No. 4, 2019, pp. 561-576.
DOI Link 1911
collinearity, computer-aided delineation, convexity, non-small cell lung cancer, spatial analysis, topological processing BibRef

Seo, J.K.[Jin Keun], Kim, K.C.[Kang Cheol], Jargal, A.[Ariungerel.], Lee, K.[Kyounghun.], Harrach, B.[Bastian],
A Learning-Based Method for Solving Ill-Posed Nonlinear Inverse Problems: A Simulation Study of Lung EIT,
SIIMS(12), No. 3, 2019, pp. 1275-1295.
DOI Link 1911
BibRef

Khan, M.A.[M. Attique], Rubab, S., Kashif, A.[Asifa], Sharif, M.I.[Muhammad Imran], Muhammad, N.[Nazeer], Shah, J.H.[Jamal Hussain], Zhang, Y.D.[Yu-Dong], Satapathy, S.C.[Suresh Chandra],
Lungs cancer classification from CT images: An integrated design of contrast based classical features fusion and selection,
PRL(129), 2020, pp. 77-85.
Elsevier DOI 2001
Lungs cancer, Contrast normalization, Multiple features, Fusion, Selection BibRef

Kumar, A., Fulham, M., Feng, D., Kim, J.,
Co-Learning Feature Fusion Maps From PET-CT Images of Lung Cancer,
MedImg(39), No. 1, January 2020, pp. 204-217.
IEEE DOI 2001
Computed tomography, Tumors, Lung, Image segmentation, Biomedical imaging, Cancer, Multi-modality imaging, deep learning, PET-CT BibRef

Bhandary, A.[Abhir], Prabhu, G.A.[G. Ananth], Rajinikanth, V., Thanaraj, K.P.[K. Palani], Satapathy, S.C.[Suresh Chandra], Robbins, D.E.[David E.], Shasky, C.[Charles], Zhang, Y.D.[Yu-Dong], Tavares, J.M.R.S.[Joăo Manuel R.S.], Raja, N.S.M.[N. Sri Madhava],
Deep-learning framework to detect lung abnormality: A study with chest X-Ray and lung CT scan images,
PRL(129), 2020, pp. 271-278.
Elsevier DOI 2001
BibRef

Guan, Q.[Qingji], Huang, Y.P.[Ya-Ping],
Multi-label chest X-ray image classification via category-wise residual attention learning,
PRL(130), 2020, pp. 259-266.
Elsevier DOI 2002
Chest X-ray, Residual attention, Convolutional neural network, Image classification BibRef

Xue, P., Dong, E., Ji, H.,
Lung 4D CT Image Registration Based on High-Order Markov Random Field,
MedImg(39), No. 4, April 2020, pp. 910-921.
IEEE DOI 2004
Lung, Image registration, Computed tomography, Optimization, Strain, Topology, Image registration, 4D CT, multi-level processing strategy BibRef

Ozdemir, O., Russell, R.L., Berlin, A.A.,
A 3D Probabilistic Deep Learning System for Detection and Diagnosis of Lung Cancer Using Low-Dose CT Scans,
MedImg(39), No. 5, May 2020, pp. 1419-1429.
IEEE DOI 2005
Solid modeling, Lung, Cancer, Computed tomography, Deep learning, Uncertainty, Machine learning, image classification BibRef

Lakshmi, D., Thanaraj, K.P.[K. Palani], Arunmozhi, M.,
Convolutional neural network in the detection of lung carcinoma using transfer learning approach,
IJIST(30), No. 2, 2020, pp. 445-454.
DOI Link 2005
convolution neural network, transfer learning approach BibRef

Bansal, G.[Gaurang], Chamola, V.[Vinay], Narang, P.[Pratik], Kumar, S.[Subham], Raman, S.[Sundaresan],
Deep3DSCan: Deep residual network and morphological descriptor based framework for lung cancer classification and 3D segmentation,
IET-IPR(14), No. 7, 29 May 2020, pp. 1240-1247.
DOI Link 2005
BibRef

Shao, W., Patton, T.J., Gerard, S.E., Pan, Y., Reinhardt, J.M., Durumeric, O.C., Bayouth, J.E., Christensen, G.E.,
N-Phase Local Expansion Ratio for Characterizing Out-of-Phase Lung Ventilation,
MedImg(39), No. 6, June 2020, pp. 2025-2034.
IEEE DOI 2006
CT, functional avoidance, image registration, lung, out-of-phase ventilation, radiation therapy BibRef

Chen, B.Z.[Bing-Zhi], Zhang, Z.[Zheng], Lin, J.Y.[Jian-Yong], Chen, Y.[Yi], Lu, G.M.[Guang-Ming],
Two-stream collaborative network for multi-label chest X-ray Image classification with lung segmentation,
PRL(135), 2020, pp. 221-227.
Elsevier DOI 2006
Two-stream collaborative network, Lung segmentation, Self-adaptive weighted fusion, Multi-label CXR image classification BibRef

Ghani, T.[Tahira], Oommen, B.J.[B. John],
Enhancing the Prediction of Lung Cancer Survival Rates Using 2d Features from 3d Scans,
ICIAR20(II:202-215).
Springer DOI 2007
BibRef

Priya, M.M.A.[Michael Mary Adline], Jawhar, S.J.[S. Joseph],
Advanced lung cancer classification approach adopting modified graph clustering and whale optimisation-based feature selection technique accompanied by a hybrid ensemble classifier,
IET-IPR(14), No. 10, August 2020, pp. 2204-2215.
DOI Link 2008
BibRef

Wang, X., Chen, H., Gan, C., Lin, H., Dou, Q., Tsougenis, E., Huang, Q., Cai, M., Heng, P.,
Weakly Supervised Deep Learning for Whole Slide Lung Cancer Image Analysis,
Cyber(50), No. 9, September 2020, pp. 3950-3962.
IEEE DOI 2008
Cancer, Lung, Feature extraction, Tumors, Task analysis, Supervised learning, Image analysis, Deep learning, whole slide images (WSIs) BibRef

Luo, L., Yu, L., Chen, H., Liu, Q., Wang, X., Xu, J., Heng, P.A.,
Deep Mining External Imperfect Data for Chest X-Ray Disease Screening,
MedImg(39), No. 11, November 2020, pp. 3583-3594.
IEEE DOI 2011
Diseases, X-ray imaging, Training, Task analysis, Training data, Biomedical imaging, Predictive models, uncertainty BibRef

Jena, S.R.[Sanjukta Rani], George, S.T.[Selvaraj Thomas],
Morphological feature extraction and KNG-CNN classification of CT images for early lung cancer detection,
IJIST(30), No. 4, 2020, pp. 1324-1336.
DOI Link 2011
automatic detection, CLAHE, CT, kernel based non-Gaussian convolutional neural networks, ROI BibRef

Schaff, F., Morgan, K.S., Pollock, J.A., Croton, L.C.P., Hooper, S.B., Kitchen, M.J.,
Material Decomposition Using Spectral Propagation-Based Phase-Contrast X-Ray Imaging,
MedImg(39), No. 12, December 2020, pp. 3891-3899.
IEEE DOI 2012
X-ray imaging, Attenuation, Lung, Approximation algorithms, Mathematical model, Radiography, Inverse methods, lung imaging, dual-energy BibRef

Kircher, M., Elke, G., Stender, B., Hernández Mesa, M., Schuderer, F., Dössel, O., Fuld, M.K., Halaweish, A.F., Hoffman, E.A., Weiler, N., Frerichs, I.,
Regional Lung Perfusion Analysis in Experimental ARDS by Electrical Impedance and Computed Tomography,
MedImg(40), No. 1, January 2021, pp. 251-261.
IEEE DOI 2012
Lung, Impedance, Ventilation, Computed tomography, Animals, Pulmonary perfusion imaging, EIT, MDCT, first pass kinetics BibRef

Cho, Y.[Yongwon], Lee, S.M.[Sang Min], Cho, Y.H.[Young-Hoon], Lee, J.G.[June-Goo], Park, B.[Beomhee], Lee, G.[Gaeun], Kim, N.[Namkug], Seo, J.B.[Joon Beom],
Deep chest X-ray: Detection and classification of lesions based on deep convolutional neural networks,
IJIST(31), No. 1, 2021, pp. 72-81.
DOI Link 2102
chest radiographs, computer-aided detection, deep learning, lung diseases, machine learning, radiography BibRef

Cai, N., Chen, H., Li, Y., Peng, Y., Li, J.,
Adaptive Weighting Landmark-Based Group-Wise Registration on Lung DCE-MRI Images,
MedImg(40), No. 2, February 2021, pp. 673-687.
IEEE DOI 2102
Strain, Principal component analysis, Lung, Magnetic resonance imaging, Time series analysis, robust principal component analysis BibRef

Xiao, N.[Ning], Qiang, Y.[Yan], Zhao, Z.J.[Zi-Juan], Zhao, J.J.[Juan-Juan], Lian, J.H.[Jian-Hong],
Tumour growth prediction of follow-up lung cancer via conditional recurrent variational autoencoder,
IET-IPR(14), No. 15, 15 December 2020, pp. 3975-3981.
DOI Link 2103
BibRef

Rani, K.V.[K. Vijila], Dayana, C.T.[C. Thinkal], Therese, P.S.[P. Sujatha], Prince, M.E.[M. Eugine],
Triple novelty block detection and classification approach for lung tumor analysis,
IJIST(31), No. 2, 2021, pp. 1034-1049.
DOI Link 2105
bilateral filter, CAD, firefly search-based Macqueen's K-means clustering, texture feature BibRef

Nishio, M.[Mizuho], Fujimoto, K.[Koji], Togashi, K.[Kaori],
Lung segmentation on chest X-ray images in patients with severe abnormal findings using deep learning,
IJIST(31), No. 2, 2021, pp. 1002-1008.
DOI Link 2105
Bayesian optimization, chest X-ray images, dice similarity coefficient, lung segmentation, U-net BibRef

Taphorn, K.[Kirsten], Mechlem, K.[Korbinian], Sellerer, T.[Thorsten], de Marco, F.[Fabio], Viermetz, M.[Manuel], Pfeiffer, F.[Franz], Pfeiffer, D.[Daniela], Herzen, J.[Julia],
Direct Differentiation of Pathological Changes in the Human Lung Parenchyma With Grating-Based Spectral X-ray Dark-Field Radiography,
MedImg(40), No. 6, June 2021, pp. 1568-1578.
IEEE DOI 2106
Lung, Imaging, Gratings, X-ray imaging, Pulmonary diseases, Sensitivity, Correlation, Imaging modalities, lung, x-ray imaging and computed tomography BibRef

Zheng, S.H.[Shao-Hua], Nie, W.Y.[Wei-Yu], Pan, L.[Lin], Zheng, B.[Bin], Shen, Z.Q.[Zhi-Qiang], Huang, L.Q.[Li-Qin], Pei, C.H.[Chen-Hao], She, Y.H.[Yu-Hang], Chen, L.Q.[Liu-Qing],
A dual-attention V-network for pulmonary lobe segmentation in CT scans,
IET-IPR(15), No. 8, 2021, pp. 1644-1654.
DOI Link 2106
BibRef

Doddavarapu, V.N.S.[V. N. Sukanya], Kande, G.B.[Giri Babu], Rao, B.P.[B. Prabhakar],
Rotational invariant fractional derivative filters for lung tissue classification,
IET-IPR(15), No. 10, 2021, pp. 2202-2212.
DOI Link 2108
BibRef

Chilakala, L.R.[Lokanath Reddy], Kishore, G.N.[Gattim Naveen],
Optimal deep belief network with opposition-based hybrid grasshopper and honeybee optimization algorithm for lung cancer classification: A DBNGHHB approach,
IJIST(31), No. 3, 2021, pp. 1404-1423.
DOI Link 2108
computed tomography (CT), deep belief networks (DBN), grasshopper and honey bee (GHHB) optimization algorithm, local tangent space alignment (LTSA) BibRef

Yang, B.[Bing], Kang, Y.[Yan], Zhang, L.[Lan], Li, H.[Hao],
GGAC: Multi-relational image gated GCN with attention convolutional binary neural tree for identifying disease with chest X-rays,
PR(120), 2021, pp. 108113.
Elsevier DOI 2109
Multi-relational graph, Gated graph convolutional network, Identifying disease, Attention transformer BibRef

Yin, L.[Li], Liu, Y.[Yang], Pei, M.[Mingtao], Li, J.R.[Jin-Rang], Wu, M.[Mukun], Jia, Y.Y.[Yuan-Yuan],
Laryngoscope8: Laryngeal image dataset and classification of laryngeal disease based on attention mechanism,
PRL(150), 2021, pp. 207-213.
Elsevier DOI 2109
Laryngeal image dataset, Laryngeal disease classification, Attention mechanism BibRef


Zhang, L.[Lipei], Liu, A.[Aozhi], Xiao, J.[Jing], Taylor, P.[Paul],
Dual Encoder Fusion U-Net (DEFU-Net) for Cross-manufacturer Chest X-ray Segmentation,
ICPR21(9333-9339)
IEEE DOI 2105
Deep learning, Image segmentation, Hospitals, Feature extraction, Data models, Decoding, Convolutional neural networks, DEFU-Net BibRef

Ma, S.[Sike], Zhao, M.[Meng], Wang, H.[Hao], Shi, F.[Fan], Sun, X.[Xuguo], Chen, S.[Shengyong], Dai, H.N.[Hong-Ning],
Fused 3-Stage Image Segmentation for Pleural Effusion Cell Clusters,
ICPR21(1934-1941)
IEEE DOI 2105
Image segmentation, Clustering algorithms, Lung, Fluorescence, Feature extraction, Pattern recognition, Metastasis BibRef

Seibold, C.[Constantin], Kleesiek, J.[Jens], Schlemmer, H.P.[Heinz-Peter], Stiefelhagen, R.[Rainer],
Self-guided Multiple Instance Learning for Weakly Supervised Disease Classification and Localization in Chest Radiographs,
ACCV20(V:617-634).
Springer DOI 2103
BibRef

Hamad, A.S., Wang, Y.Y., Lever, T.E., Bunyak, F.,
Ensemble Of Deep Cascades For Detection Of Laryngeal Adductor Reflex Events In Endoscopy Videos,
ICIP20(300-304)
IEEE DOI 2011
Image segmentation, Videos, Endoscopes, Training, Machine learning, Event detection, Pipelines, deep learning, endoscopy video analysis BibRef

Majdi, M.S., Salman, K.N., Morris, M.F., Merchant, N.C., Rodriguez, J.J.,
Deep Learning Classification of Chest X-Ray Images,
SSIAI20(116-119)
IEEE DOI 2009
computerised tomography, diagnostic radiography, diseases, image classification, learning (artificial intelligence), cardiomegaly BibRef

Han, F., Yu, L., Jiang, Y.,
Computer-aided diagnosis system of lung carcinoma using Convolutional Neural Networks,
EDLCV20(2953-2958)
IEEE DOI 2008
Training, Lung, Cancer, Pathology, Hospitals, Medical diagnostic imaging BibRef

Kalra, S.[Shivam], Adnan, M.[Mohammed], Taylor, G.[Graham], Tizhoosh, H.R.,
Learning Permutation Invariant Representations Using Memory Networks,
ECCV20(XXIX: 677-693).
Springer DOI 2010
BibRef

Adnan, M., Kalra, S., Tizhoosh, H.R.,
Representation Learning of Histopathology Images using Graph Neural Networks,
Microscopy20(4254-4261)
IEEE DOI 2008
Pathology, Lung, Convolution, Feature extraction, Neural networks, Cancer, Machine learning BibRef

Liu, J., Zhao, G., Fei, Y., Zhang, M., Wang, Y., Yu, Y.,
Align, Attend and Locate: Chest X-Ray Diagnosis via Contrast Induced Attention Network With Limited Supervision,
ICCV19(10631-10640)
IEEE DOI 2004
diagnostic radiography, diseases, learning (artificial intelligence), medical image processing, Visualization BibRef

Devnath, L., Luo, S., Summons, P., Wang, D.,
An accurate black lung detection using transfer learning based on deep neural networks,
IVCNZ19(1-6)
IEEE DOI 2004
coal, computerised tomography, decision trees, diseases, image classification, image segmentation, Computer-Aided Diagnosis BibRef

Oliveira, A.C.[Ana Catarina], Domingues, I.[Inęs], Duarte, H.[Hugo], Santos, J.[Joăo], Abreu, P.H.[Pedro H.],
Going Back to Basics on Volumetric Segmentation of the Lungs in CT: A Fully Image Processing Based Technique,
IbPRIA19(II:322-334).
Springer DOI 1910
BibRef

Dias, C.[Catarina], Pinheiro, G.[Gil], Cunha, A.[António], Oliveira, H.P.[Hélder P.],
Radiogenomics: Lung Cancer-Related Genes Mutation Status Prediction,
IbPRIA19(II:335-345).
Springer DOI 1910
BibRef

Khanagha, V.[Vahid], Kardehdeh, S.A.[Sanaz Aliari],
Context Aware Lung Cancer Annotation in Whole Slide Images Using Fully Convolutional Neural Networks,
ICIAR19(II:345-352).
Springer DOI 1909
BibRef

Zhou, B.[Bo], Lin, X.[Xunyu], Eck, B.[Brendan], Hou, J.[Jun], Wilson, D.[David],
Generation of Virtual Dual Energy Images from Standard Single-Shot Radiographs Using Multi-scale and Conditional Adversarial Network,
ACCV18(I:298-313).
Springer DOI 1906
Dual-energy (DE) chest radiographs. BibRef

Liu, Z., Song, Y., Maere, C., Liu, Q., Zhu, Y., Lu, H., Yuan, D.,
A Method for PET-CT Lung Cancer Segmentation based on Improved Random Walk,
ICPR18(1187-1192)
IEEE DOI 1812
Computed tomography, Tumors, Image segmentation, Positron emission tomography, Lung, Cancer, Random walk BibRef

Shaffie, A., Soliman, A., Ghazal, M., Taher, F., Dunlap, N., Wang, B., van Berkel, V., Gimel'farb, G.L.[Georgy L.], Elmaghraby, A., El-Baz, A.,
A Novel Autoencoder-Based Diagnostic System for Early Assessment of Lung Cancer,
ICIP18(1393-1397)
IEEE DOI 1809
Lung, Cancer, Computed tomography, Feature extraction, Magnetic resonance imaging, Tools, Machine learning, Computer Aided Diagnosis BibRef

dos S. Neto, A.C.[Antonino C.], Diniz, P.H.B.[Pedro H. B.], Diniz, J.O.B.[Joăo O. B.], Cavalcante, A.B.[André B.], Silva, A.C.[Aristófanes C.], de Paiva, A.C.[Anselmo C.], deAlmeida, J.D.S.[Joăo D. S.],
Diagnosis of Non-Small Cell Lung Cancer Using Phylogenetic Diversity in Radiomics Context,
ICIAR18(598-604).
Springer DOI 1807
BibRef

Rashid, R.[Rabia], Akram, M.U.[Muhammad Usman], Hassan, T.[Taimur],
Fully Convolutional Neural Network for Lungs Segmentation from Chest X-Rays,
ICIAR18(71-80).
Springer DOI 1807
BibRef

Cardoso, I.[Isadora], Almeida, E.[Eliana], Allende-Cid, H.[Héctor], Frery, A.C.[Alejandro C.], Rangayyan, R.M.[Rangaraj M.], Azevedo-Marques, P.M.[Paulo M.], Ramos, H.S.[Heitor S.],
Evaluation of Deep Feedforward Neural Networks for Classification of Diffuse Lung Diseases,
CIARP17(152-159).
Springer DOI 1802
BibRef

Bayramoglu, N., Kaakinen, M., Eklund, L., Heikkilä, J.,
Towards Virtual H E Staining of Hyperspectral Lung Histology Images Using Conditional Generative Adversarial Networks,
BioIm17(64-71)
IEEE DOI 1802
Chemicals, Hyperspectral imaging, Lung, Microscopy, Principal component analysis BibRef

Cid, Y.D.[Yashin Dicente], Müller, H.[Henning], Platon, A.[Alexandra], Janssens, J.P.[Jean-Paul], Lador, F.[Frédéric], Poletti, P.A.[Pierre-Alexandre], Depeursinge, A.[Adrien],
A Lung Graph-Model for Pulmonary Hypertension and Pulmonary Embolism Detection on DECT Images,
MCV16(58-68).
Springer DOI 1711
BibRef

Sakamoto, M.[Masaharu], Nakano, H.[Hiroki], Zhao, K.[Kun], Sekiyama, T.[Taro],
Multi-stage Neural Networks with Single-Sided Classifiers for False Positive Reduction and Its Evaluation Using Lung X-Ray CT Images,
CIAP17(I:370-379).
Springer DOI 1711
BibRef

Wang, X., Peng, Y., Lu, L., Lu, Z., Bagheri, M., Summers, R.M.,
ChestX-Ray8: Hospital-Scale Chest X-Ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases,
CVPR17(3462-3471)
IEEE DOI 1711
Biomedical imaging, Databases, Diseases, Image segmentation, Machine learning, Pathology, X-ray, imaging BibRef

Wang, C.L.[Chun-Liang],
Segmentation of Multiple Structures in Chest Radiographs Using Multi-task Fully Convolutional Networks,
SCIA17(II: 282-289).
Springer DOI 1706
BibRef

Kumar, D.[Devinder], Chung, A.G.[Audrey G.], Shaifee, M.J.[Mohammad J.], Khalvati, F.[Farzad], Haider, M.A.[Masoom A.], Wong, A.[Alexander],
Discovery Radiomics for Pathologically-Proven Computed Tomography Lung Cancer Prediction,
ICIAR17(54-62).
Springer DOI 1706
BibRef

Hamzah, M.F.M., Kasim, R.M., Yunus, A., Rijal, O.M., Noor, N.M.,
Detection of Interstitial Lung Disease using correlation and regression methods on texture measure,
IVPR17(1-4)
IEEE DOI 1704
Computed tomography BibRef

Noor, N.M.,
Keynote speaker: Computer aided diagnostics in medicine: Discrimination for some lung diseases,
IVPR17(1-1)
IEEE DOI 1704
Biographies;Biomedical imaging;Diseases;IEEE Sections BibRef

Wan Ahmad, W.S.H.M.[Wan Siti Halimatul Munirah], Wan Zaki, W.M.D.[Wan Mimi Diyana], Ahmad Fauzi, M.F.[Mohammad Faizal], Tan, W.H.[Wooi Haw],
Classification of Infection and Fluid Regions in Chest X-Ray Images,
DICTA16(1-5)
IEEE DOI 1701
Feature extraction BibRef

Zhao, B., Christensen, G.E., Song, J.H., Pan, Y., Gerard, S.E., Reinhardt, J.M., Du, K., Patton, T., Bayouth, J.M., Hugo, G.D.,
Tissue-Volume Preserving Deformable Image Registration for 4DCT Pulmonary Images,
WBIR16(481-489)
IEEE DOI 1612
4D image registration BibRef

Szmul, A., Papiez, B.W., Bates, R., Hallack, A., Schnabel, J.A., Grau, V.,
Graph Cuts-Based Registration Revisited: A Novel Approach for Lung Image Registration Using Supervoxels and Image-Guided Filtering,
WBIR16(592-599)
IEEE DOI 1612
discrete optimization BibRef

Wang, X., Lu, L., Shin, H.C., Kim, L., Bagheri, M., Nogues, I., Yao, J., Summers, R.M.,
Unsupervised Joint Mining of Deep Features and Image Labels for Large-Scale Radiology Image Categorization and Scene Recognition,
WACV17(998-1007)
IEEE DOI 1609
Biomedical imaging, Computational modeling, Feature extraction, Image recognition, Image representation, Optimization, Radiology BibRef

Shin, H.C., Roberts, K., Lu, L., Demner-Fushman, D., Yao, J., Summers, R.M.,
Learning to Read Chest X-Rays: Recurrent Neural Cascade Model for Automated Image Annotation,
CVPR16(2497-2506)
IEEE DOI 1612
BibRef

Gao, M.[Mingchen], Xu, Z.Y.[Zi-Yue], Lu, L.[Le], Harrison, A.P.[Adam P.], Summers, R.M.[Ronald M.], Mollura, D.J.[Daniel J.],
Multi-label Deep Regression and Unordered Pooling for Holistic Interstitial Lung Disease Pattern Detection,
MLMI16(147-155).
Springer DOI 1611
BibRef

Soliman, A., Khalifa, F., Shaffie, A., Dunlap, N., Wang, B., Elmaghraby, A., Gimel'farb, G., Ghazal, M., El-Baz, A.,
A comprehensive framework for early assessment of lung injury,
ICIP17(3275-3279)
IEEE DOI 1803
Gaussian processes, Laplace equations, Markov processes, computerised tomography, feature extraction, RILI BibRef

Soliman, A., Khalifa, F., Shaffie, A., Liu, N., Dunlap, N., Wang, B., Elmaghraby, A., Gimel'farb, G., El-Baz, A.,
Image-based CAD system for accurate identification of lung injury,
ICIP16(121-125)
IEEE DOI 1610
Adaptation models BibRef

Noor, N.M.[Norliza Mohd.], Rijal, O.M.[Omar Mohd.], Than, J.C.M.[Joel Chia Ming], Kassim, R.M.[Rosminah M.], Yunus, A.[Ashari],
Regression as a Tool to Measure Segmentation Quality and Preliminary Indicator of Diseased Lungs,
PSIVT15(502-511).
Springer DOI 1602
BibRef

Soliman, A.[Ahmed], Elnakib, A.[Ahmed], Khalifa, F.[Fahmi], El-Ghar, M.A.[Mohamed Abou], El-Baz, A.[Ayman],
Segmentation of pathological lungs from CT chest images,
ICIP15(3655-3659)
IEEE DOI 1512
Computed Tomography; Lung; Markov Random Field; Pathology; Segmentation BibRef

Ngo, T.A.[Tuan Anh], Carneiro, G.[Gustavo],
Lung segmentation in chest radiographs using distance regularized level set and deep-structured learning and inference,
ICIP15(2140-2143)
IEEE DOI 1512
Deep learning; Level set methods; Lung segmentation BibRef

Costa, A.[Addson], Carvalho, B.M.[Bruno M.],
SALSA: A Simple Automatic Lung Segmentation Algorithm,
CIARP15(501-508).
Springer DOI 1511
BibRef

Yao, J.W.[Jia-Wen], Ganti, D.[Dheeraj], Luo, X.[Xin], Xiao, G.H.[Guang-Hua], Xie, Y.[Yang], Yan, S.[Shirley], Huang, J.Z.[Jun-Zhou],
Computer-Assisted Diagnosis of Lung Cancer Using Quantitative Topology Features,
MLMI15(288-295).
Springer DOI 1511
BibRef

Hossain, M.R.I.[Mir Rayat Imtiaz], Ahmed, I.[Imran], Kabir, M.H.[Md. Hasanul],
Automatic Lung Tumor Detection Based on GLCM Features,
FSLCV14(III: 109-121).
Springer DOI 1504
BibRef

Hosseini-Asl, E.[Ehsan], Zurada, J.M.[Jacek M.], El-Baz, A.[Ayman],
Automatic segmentation of pathological lung using incremental nonnegative matrix factorization,
ICIP15(3111-3115)
IEEE DOI 1512
BibRef
Earlier:
Lung segmentation based on Nonnegative Matrix Factorization,
ICIP14(877-881)
IEEE DOI 1502
Nonnegative matrix factorization. Computed tomography BibRef

Schlegl, T.[Thomas], Ofner, J.[Joachim], Langs, G.[Georg],
Unsupervised Pre-training Across Image Domains Improves Lung Tissue Classification,
MCV14(82-93).
Springer DOI 1501
BibRef

Gill, G.[Gurman], Beichel, R.R.[Reinhard R.],
Segmentation of Lungs with Interstitial Lung Disease in CT Scans: A TV-L 1 Based Texture Analysis Approach,
ISVC14(I: 511-520).
Springer DOI 1501
BibRef

Cheplygina, V.[Veronika], Sorensen, L.[Lauge], Tax, D.M.J.[David M.J.], Pedersen, J.H.[Jesper Holst], Loog, M.[Marco], de Bruijne, M.[Marleen],
Classification of COPD with Multiple Instance Learning,
ICPR14(1508-1513)
IEEE DOI 1412
Diseases BibRef

Orjuela-Cańón, A.D.[Alvaro D.], Gómez-Cajas, D.F.[Diego F.], Jiménez-Moreno, R.[Robinson],
Artificial Neural Networks for Acoustic Lung Signals Classification,
CIARP14(214-221).
Springer DOI 1411
BibRef

Wujcicki, A.[Artur], Materka, A.[Andrzej],
Quantitative and Qualitative Evaluation of Selected Lung MR Image Registration Techniques,
ICCVG14(653-660).
Springer DOI 1410
BibRef

Amemiya, T., Maeda, T.,
Depth and rate estimation for chest compression CPR with smartphone,
3DUI13(125-126)
IEEE DOI 1406
accelerometers BibRef

Huang, W.[Wei], Li, J.[Jing], Zhang, P.[Peng], Wan, M.[Min],
A novel marker-less tumor tracking strategyonlow-rank fluoroscopic images for image-guided lung cancer radiotherapy,
ICIP13(1399-1403)
IEEE DOI 1402
Fluoroscopic image BibRef

Sakai, T.[Tomoya], Miyahara, S.[Sueharu], Kiyasu, S.[Senya],
Unmixing three types of lung sounds by convex optimization,
ICPR16(2884-2888)
IEEE DOI 1705
Convex functions, Discrete cosine transforms, Discrete wavelet transforms, Lungs, Optimization, Spectrogram, Time-frequency, analysis BibRef

Sakai, T.[Tomoya], Kato, M.[Madoka], Miyahara, S.[Sueharu], Kiyasu, S.[Senya],
Robust detection of adventitious lung sounds in electronic auscultation signals,
ICPR12(1993-1996).
WWW Link. 1302
BibRef

Yamashita, T.[Tatsuya], Tamura, S.[Satoshi], Hayashi, K.[Kenji], Nishimoto, Y.[Yutaka], Hayamizu, S.[Satoru],
Sparse representation of audio features for sputum detection from lung sounds,
ICPR12(2005-2008).
WWW Link. 1302
BibRef

Kockelkorn, T.T.J.P.[Thessa T.J.P.], Sanchez, C.I.[Clara I.], Grutters, J.C.[Jan C.], Ramos, R.[Rui], de Jong, P.A.[Pim A.], Viergever, M.A.[Max A.], Ramos, J.[Jose], Schaefer-Prokop, C.[Cornelia], van Ginneken, B.[Bram],
Interactive classification of lung tissue in CT scans by combining prior and interactively obtained training data: A simulation study,
ICPR12(105-108).
WWW Link. 1302
BibRef

Giuca, A.M.[Anne-Marie], Seitz, K.A.[Kerry A.], Furst, J.[Jacob], Raicu, D.[Daniela],
Expanding diagnostically labeled datasets using content-based image retrieval,
ICIP12(2397-2400).
IEEE DOI 1302
aided diagnosis system. Use CBIR system to label unlabelled images. BibRef

Taher, F.[Fatma], Werghi, N.[Naoufel], Al-Ahmad, H.[Hussain],
Computer aided diagnosis system for early lung cancer detection,
WSSIP15(5-8)
IEEE DOI 1603
biomedical optical imaging BibRef

Werghi, N.[Naoufel], Donner, C.[Christian], Taher, F.[Fatma], Al-Ahmad, H.[Hussain],
Detection and segmentation of sputum cell for early lung cancer detection,
ICIP12(2813-2816).
IEEE DOI 1302
BibRef

Zheng, C.[Chaojie], Wang, X.[Xiuying], Chen, J.H.[Jin-Hu], Yin, Y.[Yong], Feng, D.[Dagan],
Deformable registration model with local rigidity preservation for radiation therapy of lung tumor,
ICIP12(1673-1676).
IEEE DOI 1302
BibRef

Abdollahi, B.[Behnoush], Soliman, A.[Ahmed], Civelek, A.C., Li, X.F., Gimel'farb, G.L., El-Baz, A.[Ayman],
A novel Gaussian Scale Space-based joint MGRF framework for precise lung segmentation,
ICIP12(2029-2032).
IEEE DOI 1302
BibRef
And:
A Novel 3D Joint MGRF Framework for Precise Lung Segmentation,
MLMI12(86-93).
Springer DOI 1211
BibRef

Hollensen, C.[Christian], Cannon, G.[George], Cannon, D.[Donald], Bentzen, S.[Sřren], Larsen, R.[Rasmus],
Lung Tumor Segmentation Using Electric Flow Lines for Graph Cuts,
ICIAR12(II: 206-213).
Springer DOI 1206
BibRef

Faltin, P.[Peter], Chaisaowong, K.[Kraisorn], Kraus, T.[Thomas], Aach, T.[Til],
Markov-Gibbs model based registration of CT lung images using subsampling for the follow-up assessment of pleural thickenings,
ICIP11(2181-2184).
IEEE DOI 1201
BibRef

Faltin, P.[Peter], Chaisaowong, K.[Kraisorn], Aach, T.[Til],
Volume-preserving correction for image registration using free-form deformations,
ICIP12(2945-2948).
IEEE DOI 1302
BibRef

Wang, C.W.[Ching-Wei], Yu, C.P.[Cheng-Ping],
Automatic Morphological Classification of Lung Cancer Subtypes with Boosting Algorithms for Optimizing Therapy,
MLMI11(217-224).
Springer DOI 1109
BibRef

Takano, H.[Hirofumi], Watanabe, M.[Masahiro], Hironaka, S.[Shoji], Mukai, Y.[Yoshiharu], Aoki, Y.[Yoshimitsu],
Non-contact measurement system for swallowing time using Fiber grating vision sensor,
FCV11(1-5).
IEEE DOI 1102
Not really lungs. BibRef

Gangeh, M.J.[Mehrdad J.], Sřrensen, L.[Lauge], Shaker, S.B.[Saher B.], Kamel, M.S.[Mohamed S.], de Bruijne, M.[Marleen],
Multiple Classifier Systems in Texton-Based Approach for the Classification of CT Images of Lung,
MCV10(153-163).
Springer DOI 1009
BibRef

Farag, A.[Amal], Graham, J.[James], Farag, A.A.[Aly A.],
Robust segmentation of lung tissue in chest CT scanning,
ICIP10(2249-2252).
IEEE DOI 1009
BibRef

de Boer, W.[Willem], Lasenby, J.[Joan], Cameron, J.[Jonathan], Wareham, R.[Rich], Ahmad, S.[Shiraz], Roach, C.[Charlotte], Hills, W.[Ward], Iles, R.[Richard],
SLP: A Zero-contact Non-invasive Method for Pulmonary Function Testing,
BMVC10(xx-yy).
HTML Version. 1009
BibRef

Herberich, G.[Gerlind], Ivanescu, A.[Anca], Gamper, I.[Ivonne], Sechi, A.S.[Antonio S.], Aach, T.[Til],
Analysis of Length and Orientation of Microtubules in Wide-Field Fluorescence Microscopy,
DAGM10(182-191).
Springer DOI 1009
BibRef

Murray, V.[Victor], Pattichis, M.S.[Marios S.], Soliz, P.[Peter],
Multiscale directional AM-FM demodulation of images using a 2D optimized method,
ICIP11(249-252).
IEEE DOI 1201
BibRef

Vo, K.T.[Kiet T.], Sowmya, A.[Arcot],
Scale-Space Representation of Lung HRCT Images for Diffuse Lung Disease Classification,
ICISP10(550-558).
Springer DOI 1006
BibRef
Earlier:
Diffuse lung disease classification in HRCT lung images using generalized Gaussian density modeling of wavelets coefficients,
ICIP09(2645-2648).
IEEE DOI 0911
BibRef

Wantroba, J.S.[Joseph S.], Raicu, D.S.[Daniela S.], Furst, J.D.[Jacob D.],
A statistical analysis of the effects of CT acquisition parameters on low-level features extracted from CT images of the lung,
ICIP09(4197-4200).
IEEE DOI 0911
BibRef

Vo, K.T.[Kiet T.], Sowmya, A.[Arcot],
Multiscale sparse representation of high-resolution computed tomography (HRCT) lung images for diffuse lung disease classification,
ICIP11(441-444).
IEEE DOI 1201
BibRef
Earlier:
Directional Multi-scale Modeling of High-Resolution Computed Tomography (HRCT) Lung Images for Diffuse Lung Disease Classification,
CAIP09(663-671).
Springer DOI 0909
BibRef

Baradarani, A.[Aryaz], Wu, Q.M.J.[Q. M. Jonathan],
Efficient Segmentation of Lung Abnormalities in CT Images,
ICIAR09(749-758).
Springer DOI 0907
BibRef

Franchini, E.[Elena], Morigi, S.[Serena], Sgallari, F.[Fiorella],
Composed Segmentation of Tubular Structures by an Anisotropic PDE Model,
SSVM09(75-86).
Springer DOI 0906
BibRef

Ali, A.M.[Asem M.], Farag, A.A.[Aly A.],
Automatic Lung Segmentation of Volumetric Low-Dose CT Scans Using Graph Cuts,
ISVC08(I: 258-267).
Springer DOI 0812
BibRef

Aliotta, D.[Domenico], Buffa, P.[Pietro], Iaccarino, G.[Gennaro],
An Evolutionary General Purpose WebGIS to Disclose EGFR Mutations in Lung Cancer,
Visual08(xx-yy).
Springer DOI 0809
BibRef

El-Baz, A.S., Gimel'farb, G.L., Falk, R., Holland, T., Shaffer, T.,
A Framework for Unsupervised Segmentation of Lung Tissues from Low Dose Computed Tomography Images,
BMVC08(xx-yy).
PDF File. 0809
BibRef

Georg, M.[Manfred], Souvenir, R.[Richard], Hope, A.[Andrew], Pless, R.[Robert],
Manifold learning for 4D CT reconstruction of the lung,
MMBIA08(1-8).
IEEE DOI 0806
BibRef

da Silva Sousa, J.R.F.[Joăo Rodrigo Ferreira], Silva, A.C.[Aristófanes Corręa], de Paiva, A.C.[Anselmo Cardoso],
Lung Structure Classification Using 3D Geometric Measurements and SVM,
CIARP07(783-792).
Springer DOI 0711
BibRef

Gelzinis, A.[Adas], Verikas, A.[Antanas], Bacauskiene, M.[Marija],
Categorizing Laryngeal Images for Decision Support,
ACIVS07(521-530).
Springer DOI 0708
BibRef

Korfiatis, P.[Panayiotis], Skiadopoulos, S.[Spyros], Sakellaropoulos, P.[Philippos], Kalogeropoulou, C.[Christina], Costaridou, L.[Lena],
Automated 3D Segmentation of Lung Fields in Thin Slice CT Exploiting Wavelet Preprocessing,
CAIP07(237-244).
Springer DOI 0708
BibRef

Bi, J.B.[Jin-Bo], Liang, J.M.[Jian-Ming],
Multiple Instance Learning of Pulmonary Embolism Detection with Geodesic Distance along Vascular Structure,
CVPR07(1-8).
IEEE DOI 0706
BibRef

Vinhais, C.[Carlos], Campilho, A.[Aurélio],
Lung Parenchyma Segmentation from CT Images Based on Material Decomposition,
ICIAR06(II: 624-635).
Springer DOI 0610
BibRef
Earlier:
Genetic Model-Based Segmentation of Chest X-Ray Images Using Free Form Deformations,
ICIAR05(958-965).
Springer DOI 0509
BibRef

Shojaii, R., Alirezaie, J., Babyn, P.,
Automatic Lung Segmentation in CT Images using Watershed Transform,
ICIP05(II: 1270-1273).
IEEE DOI 0512
BibRef

Zrimec, T., Busayarat, S., Wilson, P.,
A 3D model of the human lung with lung regions characterization,
ICIP04(II: 1149-1152).
IEEE DOI 0505
BibRef

Zrimec, T., Busayarat, S.,
3D modelling and visualization of the human lung,
3DPVT04(110-115).
IEEE DOI 0412
BibRef

Yim, Y.[Yeny], Hong, H.[Helen],
Smoothing Segmented Lung Boundary in Chest CT Images Using Scan Line Search,
CIARP06(147-156).
Springer DOI 0611
BibRef

Hong, H.[Helen], Lee, J.J.[Jeong-Jin], Yim, Y.[Yeni], Shin, Y.G.[Yeong Gil],
Automatic Segmentation and Registration of Lung Surfaces in Temporal Chest CT Scans,
IbPRIA05(II:463).
Springer DOI 0509
BibRef

Hong, H.[Helen], Lee, J.J.[Jeong-Jin],
Digital Subtraction CT Lung Perfusion Image Based on 3D Affine Registration,
DAGM05(393).
Springer DOI 0509
BibRef

Benjelloun, M.[Mohammed],
Segmentation and Feature Extraction to Evaluate the Stomach Dynamic,
CRV05(437-443).
IEEE DOI 0505
BibRef

Mitani, Y., Matsunaga, N., Hamamoto, Y.,
Artificial images for classifying diffuse lung opacities in thin section computed tomography images,
ICPR04(III: 530-533).
IEEE DOI 0409
BibRef

Mitani, Y., Yasuda, H., Kido, S., Ueda, K., Matsunaga, N., Hamamoto, Y.,
Combining the gabor and histogram features for classifying diffuse lung opacities in thin-section computed tomography,
ICPR02(I: 53-56).
IEEE DOI 0211
BibRef

Ericsson, A.[Anders], Huart, A.[Amelié], Ekefjärd, A.[Andreas], Ĺström, K.[Kalle], Holst, H.[Holger], Evander, E.[Eva], Wollmer, P.[Per], Edenbrandt, L.[Lars],
Automated Interpretation of Ventilation-Perfusion Lung Scintigrams for the Diagnosis of Pulmonary Embolism Using Support Vector Machines,
SCIA03(415-421).
Springer DOI 0310
BibRef

Benmansour, F.[Fethallah], Cohen, L.D.[Laurent D.],
Tubular Anisotropy Segmentation,
SSVM09(14-25).
Springer DOI 0906
BibRef

Hirano, Y., Toriwaki, J., Hasegawa, J.I., Eguchi, K., Ohmatsu, H.,
Quantification of shrinkage of lung lobe from chest ct images using the 3d extended voronoi division and its application to the benign/malignant discrimination of tumor shadows,
ICPR02(I: 751-754).
IEEE DOI 0211
BibRef

Hirano, Y.S.[Yasu-Shi], Mekada, Y.[Yoshito], Hasegawa, J.I.[Jun-Ichi], Toriwaki, J.I.[Jun-Ichiro],
Quantification of the Spatial Distributionof Line Segments with Applications to CAD of Chest X-Ray CT Images,
WTRCV02(389-412). 0204
BibRef

Ugurlu, Y.[Yucel], Ohkura, K.[Keiko], Obi, T.[Takashi], Hasegawa, A.[Akira], Yamaguchi, M.[Masahiro], Ohyama, N.[Nagaaki],
Detection of Increasing Profusion of Opacities from a Sequence of Personal Chest Radiographs,
ICIP99(III:402-406).
IEEE DOI BibRef 9900

Kitasaka, T., Mori, K., Suenaga, Y., Toriwaki, J.I., Saito, T., Hasegawa, J.I.,
Extraction of Lung Region From 3D Chest X-ray CT Images by Using Shape Model Information of Lung,
SCIA99(Biological Applications). BibRef 9900

Hasegawa, J.I.[Jun-Ichi], Hirano, Y.S.[Yasu-Shi], Toriwaki, J.I.[Jun-Ichiro], Ohmatsu, N.[Nobuhiro], Mekada, Y.[Yoshito], Eguchi, K.[Kenji],
Three Dimensional Concentration Index: A Local Feature for Analyzing Three Dimensional Digital Line Patterns and Its Application to Chest X-Ray CT Images,
ICPR98(Vol II: 1040-1043).
IEEE DOI 9808
BibRef

Mori, K., Hasegawa, J.I., Toriwaki, J.I., Anno, H., Katada, K.,
Automated Extraction and Visualization of Bronchus from 3D CT Images of Lung,
CVRMed95(XX-YY) BibRef 9500

Luo, H.,
Automatic Segmentation of Lung Regions in Chest Radiographs: A Model Guided Approach,
ICIP00(Vol II: 483-486).
IEEE DOI 0008
BibRef

Wei, J.[Jun], Hagihara, Y.[Yoshihiro], Kobatake, H.[Hidefumi],
Detection of Cancerous Tumors on Chest X-ray Images: Candidate Detection Filter and Its Evaluation,
ICIP99(III:397-401).
IEEE DOI BibRef 9900

Yamamoto, S., Jiang, H., Matsumoto, M., Tateno, Y., Iinuma, T., and Matsumoto, T.,
Image Processing for Computer-Aided Diagnosis of Lung Cancer by CT (LSCT),
WACV96(236-241).
IEEE DOI 9609
BibRef

Thimm, G.[Georg],
Tracking Articulators in X-ray Movies of the Vocal Tract,
CAIP99(126-133).
Springer DOI 9909
BibRef

Wei, J.[Jun], Hagihara, Y., Kobatake, H.,
Detection of rounded opacities on chest radiographs using convergence index filter,
CIAP99(757-761).
IEEE DOI 9909
BibRef

Hara, T., Fujita, H., Lee, Y.B.[Yong-Bum], Yoshimura, H., Kido, S.,
Automated lesion detection methods for 2D and 3D chest X-ray images,
CIAP99(768-773).
IEEE DOI 9909
BibRef

Okumura, T.[Toshiaki], Miwa, T.[Tomoko], Kako, J.I.[Jun-Ichi], Yamamoto, S.[Shinji], Matsumoto, M.[Mitsuomi], Tateno, Y.[Yukio], Iinuma, T.[Takeshi], Matsumoto, T.[Tohru],
Automatic Detection of Lung Cancers in Chest CT Images by Variable N-Quoit Filter,
ICPR98(Vol II: 1671-1673).
IEEE DOI 9808
BibRef

Hayashibe, R., Asano, N., Hirohata, H., Okumura, K., Kondo, S., Handa, S., Takizawa, M., Sone, S., Oshita, S.,
An automatic lung cancer detection from X-ray images obtained through yearly serial mass survey,
ICIP96(I: 343-346).
IEEE DOI 9610
BibRef

Tozaki, T., Kawata, Y., Niki, N., Ohmatsu, H., Eguchi, K., Moriyama, N.,
3D image analysis of the lung area using thin section CT images and its application to differential diagnosis,
ICIP96(II: 281-284).
IEEE DOI 9610
BibRef

Young, S.,
Fourier-Based Dose Calculation in Radiation Brachytherapy,
ICIP97(II: 132-135).
IEEE DOI BibRef 9700

Sammouda, M.[Mohamed], Sammouda, R.[Rachid], Niki, N.[Noboru], Mukai, K.[Kyoshi],
Segmentation and Analysis of Liver Cancer Pathological Color Images based on Artificial Neural Networks,
ICIP99(III:392-396).
IEEE DOI BibRef 9900

Taher, F.[Fatma], Sammouda, R.[Rachid],
Artificial Neural Network and Fuzzy Clustering Methods in Segmenting Sputum Color Images for Lung Cancer Diagnosis,
ICISP10(513-520).
Springer DOI 1006
BibRef

Sammouda, R.[Rachid], Niki, N.[Noboru], Nishitani, H.[Hiromu], Nakamura, S., Mori, S.,
Segmentation of sputum color image for lung cancer diagnosis based on neural networks,
CIAP97(II: 461-468).
Springer DOI 9709
BibRef
And:
Segmentation of sputum color image for lung cancer diagnosis,
ICIP97(I: 243-246).
IEEE DOI 9710
BibRef

Chmielewski, L., Chmielewska, E., Sklodowski, M., Cudny, W., Skoczylas, J.,
Finding postirradiation reaction in lungs from digitized X-rays,
CAIP95(850-855).
Springer DOI 9509
BibRef

Kim, N.H., Aggarwal, S.J., Bovik, A.C., Diller, K.R.,
Computing shape changes in SOLANUM tuberosa slices viewed through a stereo microscope,
ICPR88(II: 1213-1215).
IEEE DOI 8811
BibRef

Zhang, Y.Q., Loew, M.H., Pickholtz, R.L.,
On modeling the distribution of chest X-ray images and their stochastic properties,
ICPR90(II: 218-223).
IEEE DOI 9208
BibRef

Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Lung Motion Analysis, Respiration, Breathing .


Last update:Sep 12, 2021 at 22:38:33