20.7.2.4 Pulmonary Nodules, Lung Nodules

Chapter Contents (Back)
Pulmonary Nodules. Lungs. Lung Nodules. Medical, Applications.

Engvall, J.L.[John L.], Greenberg, S.D., Spjut, H.J., Estrada, R., Subach, J., Kimzey, S.L., King, J.F., DiTrapani, P.M.,
Development of a mathematical model to analyze color and density as discriminant features for pulmonary squamous epithelial cells,
PR(13), No. 1, 1981, pp. 37-47.
WWW Link. 0309
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Lin, J.S.[Jyh-Shyan], Lo, S.C.B., Hasegawa, A., Freedman, M.T., Mun, S.K.,
Reduction of false positives in lung nodule detection using a two-level neural classification,
MedImg(15), No. 2, April 1996, pp. 206-217.
IEEE Top Reference. 0203
BibRef

Lee, Y.B.[Yong-Bum], Hara, T., Fujita, H., Itoh, S., Ishigaki, T.,
Automated detection of pulmonary nodules in helical CT images based on an improved template-matching technique,
MedImg(20), No. 7, July 2001, pp. 595-604.
IEEE Top Reference. 0110
BibRef

Brown, M.S., McNitt-Gray, M.F., Goldin, J.G., Suh, R.D., Sayre, J.W., Aberle, D.R.,
Patient-specific models for lung nodule detection and surveillance in CT images,
MedImg(20), No. 12, December 2001, pp. 1242-1250.
IEEE Top Reference. 0201
BibRef

Kostis, W.J., Reeves, A.P., Yankelevitz, D.F., Henschke, C.I.,
Three-dimensional segmentation and growth-rate estimation of small pulmonary nodules in helical CT images,
MedImg(22), No. 10, October 2003, pp. 1259-1274.
IEEE Abstract. 0310
BibRef

Paik, D.S., Beaulieu, C.F., Rubin, G.D., Acar, B., Jeffrey, R.B., Yee, J., Dey, J., Napel, S.,
Surface Normal Overlap: A Computer-Aided Detection Algorithm with Application to Colonic Polyps and Lung Nodules in Helical CT,
MedImg(23), No. 6, June 2004, pp. 661-675.
IEEE Abstract. 0406
BibRef

Okada, K.[Kazunori], Comaniciu, D.[Dorin], Krishnan, A.[Arun],
Robust Anisotropic Gaussian Fitting for Volumetric Characterization of Pulmonary Nodules in Multislice CT,
MedImg(24), No. 3, March 2005, pp. 409-423.
IEEE Abstract. 0501
BibRef
Earlier:
Scale Selection for Anisotropic Scale-Space: Application to Volumetric Tumor Characterization,
CVPR04(I: 594-601).
IEEE DOI 0408
BibRef

Okada, K.[Kazunori], Akdemir, U.[Umut], Krishnan, A.[Arun],
Blob Segmentation Using Joint Space-Intensity Likelihood Ratio Test: Application to 3D Tumor Segmentation,
CVPR05(II: 437-444).
IEEE DOI 0507
BibRef

Okada, K.[Kazunori], Comaniciu, D.[Dorin], Dalal, N.[Navneet], Krishnan, A.[Arun],
A Robust Algorithm for Characterizing Anisotropic Local Structures,
ECCV04(Vol I: 549-561).
Springer DOI 0405
BibRef

Okada, K.[Kazunori], Singh, M.[Maneesh], Ramesh, V.[Visvanathan],
Prior-Constrained Scale-Space Mean Shift,
BMVC06(II:829).
PDF File. 0609
Semi-automatic 3D segmentation of lung nodules in CT data. BibRef

Suzuki, K., Li, F., Sone, S., Doi, K.,
Computer-Aided Diagnostic Scheme for Distinction Between Benign and Malignant Nodules in Thoracic Low-Dose CT by Use of Massive Training Artificial Neural Network,
MedImg(24), No. 9, September 2005, pp. 1138-1150.
IEEE DOI 0509
BibRef

Agam, G., Armato, III, S.G., Wu, C.,
Vessel Tree Reconstruction in Thoracic CT Scans With Application to Nodule Detection,
MedImg(24), No. 4, April 2005, pp. 486-499.
IEEE Abstract. 0501
BibRef

Reeves, A.P., Chan, A.B., Yankelevitz, D.F., Henschke, C.I., Kressler, B., Kostis, W.J.,
On Measuring the Change in Size of Pulmonary Nodules,
MedImg(25), No. 4, April 2006, pp. 435-450.
IEEE DOI 0604
BibRef

Campadelli, P., Casiraghi, E., Artioli, D.,
A Fully Automated Method for Lung Nodule Detection From Postero-Anterior Chest Radiographs,
MedImg(25), No. 12, December 2006, pp. 1588-1603.
IEEE DOI 0701
BibRef

Dehmeshki, J., Amin, H., Valdivieso, M., Ye, X.J.[Xu-Jiong],
Segmentation of Pulmonary Nodules in Thoracic CT Scans: A Region Growing Approach,
MedImg(27), No. 4, April 2008, pp. 467-480.
IEEE DOI 0804
BibRef

Dehmeshki, J., Ye, X.J.[Xu-Jiong], Costello, J.,
Shape based region growing using derivatives of 3D medical images: application to semi-automated detection of pulmonary nodules,
ICIP03(I: 1085-1088).
IEEE DOI 0312
BibRef

Takizawa, H.[Hotaka], Shigemoto, K.[Kanae], Yamamoto, S.[Shinji], Matsumoto, T.[Tohru], Tateno, Y.[Yukio], Iinuma, T.[Takeshi], Matsumoto, M.[Mitsuomi],
A Recognition Method of Lung Nodule Shadows in X-ray Ct Images Using 3d Object Models,
IJIG(3), No. 4, October 2003, pp. 533-545. 0310
BibRef

El-Baz, A.[Ayman], Gimel'farb, G.L.[Georgy L.], Falk, R.[Robert], El-Ghar, M.A.[Mohamed Abo],
Automatic analysis of 3D low dose CT images for early diagnosis of lung cancer,
PR(42), No. 6, June 2009, pp. 1041-1051.
Elsevier DOI 0902
BibRef
Earlier:
A new approach for automatic analysis of 3D low dose CT images for accurate monitoring the detected lung nodules,
ICPR08(1-4).
IEEE DOI 0812
BibRef
Earlier:
A New CAD System for Early Diagnosis of Detected Lung Nodules,
ICIP07(II: 461-464).
IEEE DOI 0709
BibRef
And:
A Novel Approach for Automatic Follow-Up of Detected Lung Nodules,
ICIP07(V: 501-504).
IEEE DOI 0709
Computed tomography; Growth rate estimation; Global registration; Local registration; Segmentation; Pulmonary nodules; Early diagnosis; Lung cancer See also New CAD System for Early Diagnosis of Dyslexic Brains, A. BibRef

El-Baz, A., Sethu, P., Gimel'farb, G.L., Khalifa, F., Elnakib, A., Falk, R., El-Ghar, M.A.[M. Abo],
A new validation approach for the growth rate measurement using elastic phantoms generated by state-of-the-art microfluidics technology,
ICIP10(4381-4384).
IEEE DOI 1009
For early diagnosis of pulmonary nodules. BibRef

El-Baz, A.[Ayman], Farag, A.A.[Aly A.], Ali, A.M.[Asem M.], Gimel'farb, G.L.[Georgy L.], Casanova, M.[Manuel],
A Framework for Unsupervised Segmentation of Multi-modal Medical Images,
CVAMIA06(120-131).
Springer DOI 0605
BibRef

El-Baz, A.[Ayman], Farag, A.A.[Aly A.], Gimel'farb, G.L.[Georgy L.], Falk, R.[Robert], El-Ghar, M.A.[Mohamed A.], Eldiasty, T.[Tarek],
A Framework for Automatic Segmentation of Lung Nodules from Low Dose Chest CT Scans,
ICPR06(III: 611-614).
IEEE DOI 0609
BibRef

El-Baz, A.[Ayman], Gimel'farb, G.L.[Georgy L.], El-Ghar, M.A.[Mohamed Abou], Falk, R.[Robert],
Appearance-based diagnostic system for early assessment of malignant lung nodules,
ICIP12(533-536).
IEEE DOI 1302
BibRef

Farag, A., Gimel'farb, G.L.[Georgy L.], El-Baz, A.[Ayman], Falk, R.[Robert],
Detection and recognition of lung nodules in spiral CT images using deformable templates and Bayesian post-classification,
ICIP04(V: 2921-2924).
IEEE DOI 0505
BibRef
And:
Detection and recognition of lung abnormalities using deformable templates,
ICPR04(III: 738-741).
IEEE DOI 0409
BibRef

van Rikxoort, E.M., de Hoop, B., van de Vorst, S., Prokop, M., van Ginneken, B.,
Automatic Segmentation of Pulmonary Segments From Volumetric Chest CT Scans,
MedImg(28), No. 4, April 2009, pp. 621-630.
IEEE DOI 0904
BibRef

Lo, P., van Ginneken, B., Reinhardt, J.M., Yavarna, T., de Jong, P.A., Irving, B., Fetita, C., Ortner, M., Pinho, R., Sijbers, J., Feuerstein, M., Fabijanska, A., Bauer, C., Beichel, R., Mendoza, C.S., Wiemker, R., Lee, J., Reeves, A.P., Born, S., Weinheimer, O., van Rikxoort, E.M., Tschirren, J., Mori, K., Odry, B., Naidich, D.P., Hartmann, I., Hoffman, E.A., Prokop, M., Pedersen, J.H., de Bruijne, M.,
Extraction of Airways From CT (EXACT'09),
MedImg(31), No. 11, November 2012, pp. 2093-2107.
IEEE DOI 1211
BibRef

Pu, J.T.[Jian-Tao], Leader, J.K., Zheng, B.[Bin], Knollmann, F., Fuhrman, C., Sciurba, F.C., Gur, D.,
A Computational Geometry Approach to Automated Pulmonary Fissure Segmentation in CT Examinations,
MedImg(28), No. 5, May 2009, pp. 710-719.
IEEE DOI 0905
BibRef

Pu, J.T.[Jian-Tao], Zheng, B., Leader, J.K., Fuhrman, C., Knollmann, F., Klym, A., Gur, D.,
Pulmonary Lobe Segmentation in CT Examinations Using Implicit Surface Fitting,
MedImg(28), No. 12, December 2009, pp. 1986-1996.
IEEE DOI 0912
BibRef

Pu, J.T.[Jian-Tao], Fuhrman, C., Good, W.F., Sciurba, F.C., Gur, D.,
A Differential Geometric Approach to Automated Segmentation of Human Airway Tree,
MedImg(30), No. 2, February 2011, pp. 266-278.
IEEE DOI 1102
BibRef

Diciotti, S., Lombardo, S., Coppini, G., Grassi, L., Falchini, M., Mascalchi, M.,
The LoG Characteristic Scale: A Consistent Measurement of Lung Nodule Size in CT Imaging,
MedImg(29), No. 2, February 2010, pp. 397-409.
IEEE DOI 1002
BibRef

Wu, D.[Dijia], Lu, L.[Le], Bi, J.[Jinbo], Shinagawa, Y.[Yoshihisa], Boyer, K.L.[Kim L.], Krishnan, A.[Arun], Salganicoff, M.[Marcos],
Stratified learning of local anatomical context for lung nodules in CT images,
CVPR10(2791-2798).
IEEE DOI 1006
BibRef

Gavrielides, M.A., Zeng, R.[Rongping], Kinnard, L.M., Myers, K.J., Petrick, N.,
Information-Theoretic Approach for Analyzing Bias and Variance in Lung Nodule Size Estimation With CT: A Phantom Study,
MedImg(29), No. 10, October 2010, pp. 1795-1807.
IEEE DOI 1011
BibRef

Iyengar, S, Li, X.[Xin], Xu, H.[Huanhuan], Mukhopadhyay, S.[Supratik], Balakrishnan, N., Sawant, A.[Amit], Iyengar, P.[Puneeth],
Toward More Precise Radiotherapy Treatment of Lung Tumors,
Computer(45), No. 1, January 2012, pp. 59-65.
IEEE DOI 1201
Model respiratory motion of the tumors to guide radiotherapy. BibRef

Lee, S.L.A., Kouzani, A.Z., Hu, E.J.,
Automated detection of lung nodules in computed tomography images: a review,
MVA(23), No. 1, January 2012, pp. 151-163.
WWW Link. 1201
BibRef

Netto, S.M.B.[Stelmo Magalhães Barros], Silva, A.C.[Aristófanes Corrêa], Nunes, R.A.[Rodolfo Acatauassú], Gattass, M.[Marcelo],
Analysis of directional patterns of lung nodules in computerized tomography using Getis statistics and their accumulated forms as malignancy and benignity indicators,
PRL(33), No. 13, 1 October 2012, pp. 1734-1740.
Elsevier DOI 1208
Medical image; Computer-aided diagnosis (CADx); Lung nodules; Getis? statistics; Image processing BibRef

Zhao, W.[Wei], Xu, R.[Rui], Hirano, Y.S.[Yasu-Shi], Tachibana, R.[Rie], Kido, S.[Shoji], Suganuma, N.[Narufumi],
Classification of Pneumoconiosis on HRCT Images for Computer-Aided Diagnosis,
IEICE(E96-D), No. 4, April 2013, pp. 836-844.
WWW Link. 1304
BibRef

Bab-Hadiashar, A., Tennakoon, R.B., de Bruijne, M.,
Quantification of Smoothing Requirement for 3D Optic Flow Calculation of Volumetric Images,
IP(22), No. 6, 2013, pp. 2128-2137.
IEEE DOI 1307
dynamic lung CT imaging; 3D optic flow BibRef

Tennakoon, R.B., Bab-Hadiashar, A., Cao, Z., de Bruijne, M.,
Nonrigid Registration of Volumetric Images Using Ranked Order Statistics,
MedImg(33), No. 2, February 2014, pp. 422-432.
IEEE DOI 1403
computerised tomography BibRef

Jung, Y.H.[Youn-Hyun], Kim, J.M.[Jin-Man], Eberl, S.[Stefan], Fulham, M.J.[Micheal J.], Feng, D.D.[David Dagan],
Visibility-driven PET-CT visualisation with region of interest (ROI) segmentation,
VC(29), No. 6-8, June 2013, pp. 805-815.
Springer DOI 1306
BibRef

Ballangan, C.[Cherry], Wang, X.Y.[Xiu-Ying], Fulham, M.J.[Michael J.], Eberl, S.[Stefan], Feng, D.D.[David Dagan],
Lung tumor delineation in PET-CT images using a downhill region growing and a Gaussian mixture model,
ICIP11(2173-2176).
IEEE DOI 1201
BibRef

Lin, P.L.[Phen-Lan], Huang, P.W.[Po-Whei], Lee, C.H.[Cheng-Hsiung], Wu, M.T.[Ming-Ting],
Automatic classification for solitary pulmonary nodule in CT image by fractal analysis based on fractional Brownian motion model,
PR(46), No. 12, 2013, pp. 3279-3287.
Elsevier DOI 1308
Classification BibRef

Mi, H., Petitjean, C., Dubray, B., Vera, P., Ruan, S.,
Prediction of Lung Tumor Evolution During Radiotherapy in Individual Patients With PET,
MedImg(33), No. 4, April 2014, pp. 995-1003.
IEEE DOI 1404
Brain modeling BibRef

Ciompi, F., Jacobs, C., Scholten, E.T., Wille, M.M.W., de Jong, P.A., Prokop, M., van Ginneken, B.,
Bag-of-Frequencies: A Descriptor of Pulmonary Nodules in Computed Tomography Images,
MedImg(34), No. 4, April 2015, pp. 962-973.
IEEE DOI 1504
Biomedical imaging BibRef

Song, J., Yang, C., Fan, L., Wang, K., Yang, F., Liu, S., Tian, J.,
Lung Lesion Extraction Using a Toboggan Based Growing Automatic Segmentation Approach,
MedImg(35), No. 1, January 2016, pp. 337-353.
IEEE DOI 1601
Accuracy BibRef

Setio, A.A.A., Ciompi, F., Litjens, G., Gerke, P., Jacobs, C., van Riel, S.J., Wille, M.M.W., Naqibullah, M., Sánchez, C.I., van Ginneken, B.,
Pulmonary Nodule Detection in CT Images: False Positive Reduction Using Multi-View Convolutional Networks,
MedImg(35), No. 5, May 2016, pp. 1160-1169.
IEEE DOI 1605
Cancer BibRef

Dhara, A.K., Mukhopadhyay, S., Chakrabarty, S., Garg, M., Khandelwal, N.,
Quantitative evaluation of margin sharpness of pulmonary nodules in lung CT images,
IET-IPR(10), No. 9, 2016, pp. 631-637.
DOI Link 1609
cancer BibRef

Shen, W.[Wei], Zhou, M.[Mu], Yang, F.[Feng], Yu, D.[Dongdong], Dong, D.[Di], Yang, C.[Caiyun], Zang, Y.[Yali], Tian, J.[Jie],
Multi-crop Convolutional Neural Networks for lung nodule malignancy suspiciousness classification,
PR(61), No. 1, 2017, pp. 663-673.
Elsevier DOI 1705
Lung nodule BibRef

Cirujeda, P.[Pol], Müller, H.[Henning], Rubin, D.[Daniel], Aguilera, T.A.[Todd A.], Loo, B.W.[Billy W.], Diehn, M.[Maximilian], Binefa, X.[Xavier], Depeursinge, A.[Adrien],
A 3-D Riesz-Covariance Texture Model for Prediction of Nodule Recurrence in Lung CT,
MedImg(35), No. 12, December 2016, pp. 2620-2630.
IEEE DOI 1612
Biomedical imaging BibRef

Dicente Cid, Y., Müller, H., Platon, A., Poletti, P.A., Depeursinge, A.,
3D Solid Texture Classification Using Locally-Oriented Wavelet Transforms,
IP(26), No. 4, April 2017, pp. 1899-1910.
IEEE DOI 1704
Biomedical imaging BibRef

Tajbakhsh, N.[Nima], Suzuki, K.[Kenji],
Comparing two classes of end-to-end machine-learning models in lung nodule detection and classification: MTANNs vs. CNNs,
PR(63), No. 1, 2017, pp. 476-486.
Elsevier DOI 1612
Deep learning BibRef

Cao, P.[Peng], Liu, X.L.[Xiao-Li], Yang, J.Z.[Jin-Zhu], Zhao, D.[Dazhe], Li, W.[Wei], Huang, M.[Min], Zaiane, O.[Osmar],
A multi-kernel based framework for heterogeneous feature selection and over-sampling for computer-aided detection of pulmonary nodules,
PR(64), No. 1, 2017, pp. 327-346.
Elsevier DOI 1701
Lung nodule detection BibRef

Chen, S., Qin, J., Ji, X., Lei, B., Wang, T., Ni, D., Cheng, J.Z.,
Automatic Scoring of Multiple Semantic Attributes With Multi-Task Feature Leverage: A Study on Pulmonary Nodules in CT Images,
MedImg(36), No. 3, March 2017, pp. 802-814.
IEEE DOI 1703
Computational modeling BibRef

Liu, K.[Kui], Kang, G.[Guixia],
Multiview convolutional neural networks for lung nodule classification,
IJIST(27), No. 1, 2017, pp. 12-22.
DOI Link 1704
lung nodule classification BibRef

Farhangi, M.M., Frigui, H., Seow, A., Amini, A.A.,
3-D Active Contour Segmentation Based on Sparse Linear Combination of Training Shapes (SCoTS),
MedImg(36), No. 11, November 2017, pp. 2239-2249.
IEEE DOI 1711
Active contours, Cancer, Image segmentation, Level set, Lungs, Shape, Adaptive shape prior, X-ray CT, dictionary learning, level set segmentation, lung nodules, sparse, representation BibRef


Luo, Z., Brubaker, M.A.[Marcus A.], Brudno, M.,
Size and Texture-Based Classification of Lung Tumors with 3D CNNs,
WACV17(806-814)
IEEE DOI 1609
Biological neural networks, Cancer, Computed tomography, Lungs, Three-dimensional displays, Tumors BibRef

Yan, X.J.[Xing-Jian], Pang, J.N.[Jia-Ning], Qi, H.[Hang], Zhu, Y.X.[Yi-Xin], Bai, C.X.[Chun-Xue], Geng, X.[Xin], Liu, M.[Mina], Terzopoulos, D.[Demetri], Ding, X.W.[Xiao-Wei],
Classification of Lung Nodule Malignancy Risk on Computed Tomography Images Using Convolutional Neural Network: A Comparison Between 2D and 3D Strategies,
MCBMIIA16(III: 91-101).
Springer DOI 1704
BibRef

Bobadilla, J.C.M.[Julio Cesar Mendoza], Pedrini, H.[Helio],
Lung Nodule Classification Based on Deep Convolutional Neural Networks,
CIARP16(117-124).
Springer DOI 1703
BibRef

Ishihara, M.[Masaki], Matsuda, Y.[Yuji], Sugimura, M.[Masahiko], Endo, S.[Susumu], Takebe, H.[Hiroaki], Baba, T.[Takayuki], Uehara, Y.[Yusuke],
An Image Registration Method with Radial Feature Points Sampling: Application to Follow-Up CT Scans of a Solitary Pulmonary Nodule,
PSIVT15(512-525).
Springer DOI 1602
BibRef

Novo, J.[Jorge], Goncalves, L.[Luis], Mendonca, A.M.[Ana Maria], Campilho, A.[Aurelio],
3D lung nodule candidate detection in multiple scales,
MVA15(61-64)
IEEE DOI 1507
Cancer BibRef

Kumar, D.[Devinder], Wong, A.[Alexander], Clausi, D.A.[David A.],
Lung Nodule Classification Using Deep Features in CT Images,
CRV15(133-138)
IEEE DOI 1507
Accuracy BibRef

Duggan, N.[Nóirín], Bae, E.[Egil], Shen, S.[Shiwen], Hsu, W.[William], Bui, A.[Alex], Jones, E.[Edward], Glavin, M.[Martin], Vese, L.[Luminita],
A Technique for Lung Nodule Candidate Detection in CT Using Global Minimization Methods,
EMMCVPR15(478-491).
Springer DOI 1504
BibRef

Liu, Y.[Yang], Wang, Z.Q.[Zhong-Qiu], Guo, M.[Maozu], Li, P.[Ping],
Hidden conditional random field for lung nodule detection,
ICIP14(3518-3521)
IEEE DOI 1502
Biomedical imaging BibRef

Forsberg, D.[Daniel], Monsef, N.[Nastaran],
Evaluating Cell Nuclei Segmentation for Use on Whole-Slide Images in Lung Cytology,
ICPR14(3380-3385)
IEEE DOI 1412
BibRef

Kaya, A.[Aydln], Can, A.B.[Ahmet Burak],
eFis: A Fuzzy Inference Method for Predicting Malignancy of Small Pulmonary Nodules,
ICIAR14(II: 255-262).
Springer DOI 1410
BibRef

Gonçalves, L.[Luis], Novo, J.[Jorge], Campilho, A.[Aurélio],
Central Medialness Adaptive Strategy for 3D Lung Nodule Segmentation in Thoracic CT Images,
ICIAR16(583-590).
Springer DOI 1608
BibRef

Novo, J., Rouco, J., Mendonça, A., Campilho, A.[Aurélio],
Reliable Lung Segmentation Methodology by Including Juxtapleural Nodules,
ICIAR14(II: 227-235).
Springer DOI 1410
BibRef

Papiez, B.W.[Bartlomiej W.], Tapmeier, T.[Thomas], Heinrich, M.P.[Mattias P.], Muschel, R.J.[Ruth J.], Schnabel, J.A.[Julia A.],
Motion Correction of Intravital Microscopy of Preclinical Lung Tumour Imaging Using Multichannel Structural Image Descriptor,
WBIR14(164-173).
Springer DOI 1407
BibRef

Lam, M., Doppa, J.R., Hu, X.[Xu], Todorovic, S., Dietterich, T., Reft, A., Daly, M.,
Learning to Detect Basal Tubules of Nematocysts in SEM Images,
AccBio13(190-196)
IEEE DOI 1403
biology computing BibRef

Li, Y.[Yang], Wen, D.[Dunwei], Wang, K.[Ke], Hou, A.[A'lin],
Mixed Kernel Function SVM for Pulmonary Nodule Recognition,
CIAP13(II:449-458).
Springer DOI 1309
BibRef

Aggarwal, P.[Preeti], Sardana, H.K., Vig, R.[Renu],
Correlation between Biopsy Confirmed Cases and Radiologist's Annotations in the Detection of Lung Nodules by Expanding the Diagnostic Database Using Content Based Image Retrieval,
CAIP13(531-538).
Springer DOI 1308
BibRef

Vinay, K., Rao, A., Kumar, G.H.,
Computerized Analysis of Classification of Lung Nodules and Comparison between Homogeneous and Heterogeneous Ensemble of Classifier Model,
NCVPRIPG11(231-234).
IEEE DOI 1205
BibRef

Acharya, M.[Mekhala], Kinser, J.[Jason], Nathan, S.[Steven], Albano, M.C.[Marcia C.], Schlegel, L.[Lori],
An image analysis method for quantification of idiopathic pulmonary fibrosis,
AIPR11(1-5).
IEEE DOI 1204
BibRef

Farag, A.A.[Amal A.], Abd el Munim, H.E.[Hossam E.], Graham, J.[James], Farag, A.A.[Aly A.], Elshazly, S.[Salwa], El-Mogy, S.[Sabry], El-Mogy, M.[Mohamed], Falk, R.[Robert], Al-Jafary, S.[Sahar], Mahdi, H.[Hani], Milam, R.[Rebecca],
Variational approach for segmentation of lung nodules,
ICIP11(2157-2160).
IEEE DOI 1201
BibRef

Zinoveva, O.[Olga], Zinovev, D.[Dmitriy], Siena, S.A.[Stephen A.], Raicu, D.S.[Daniela S.], Furst, J.[Jacob], Armato, S.G.[Samuel G.],
A Texture-Based Probabilistic Approach for Lung Nodule Segmentation,
ICIAR11(II: 21-30).
Springer DOI 1106
BibRef

Farag, A.[Amal], Ali, A.M.[Asem M.], Graham, J.[James], Elhabian, S.Y.[Shireen Y.], Farag, A.A.[Aly A.], Falk, R.[Robert],
Feature-Based Lung Nodule Classification,
ISVC10(III: 79-88).
Springer DOI 1011
BibRef

Choi, W.J.[Wook-Jin], Choi, T.S.[Tae-Sun],
Computer-aided detection of pulmonary nodules using genetic programming,
ICIP10(4353-4356).
IEEE DOI 1009
BibRef

Farag, A.A.[Amal A.], Graham, J.[James], Elshazly, S.[Salwa], Farag, A.A.[Aly A.],
Statistical modeling of the lung nodules in low dose computed tomography scans of the chest,
ICIP10(4281-4284).
IEEE DOI 1009
BibRef

Farag, A.A.[Amal A.], Graham, J.[James], Elshazly, S.[Salwa], Farag, A.A.[Aly A.],
Data-Driven Lung Nodule Models for Robust Nodule Detection in Chest CT,
ICPR10(2588-2591).
IEEE DOI 1008
BibRef

Farag, A.A.[Amal A.], Graham, J.[James], Farag, A.A.[Aly A.], Falk, R.[Robert],
Lung Nodule Modeling: A Data-Driven Approach,
ISVC09(I: 347-356).
Springer DOI 0911
BibRef

Tolouee, A., Abrishami-Moghaddam, H., Garnavi, R., Forouzanfar, M., Giti, M.,
Texture Analysis in Lung HRCT Images,
DICTA08(305-311).
IEEE DOI 0812
BibRef

Shi, Z.H.[Zheng-Hao], Bai, J.[Jun], He, L.F.[Li-Feng], Nakamura, T., Yao, Q.Z.[Quan-Zhu], Itoh, H.,
A Method for Enhancing Lung Nodules in Chest Radiographs by Use of LoG Filter,
CISP09(1-4).
IEEE DOI 0910
BibRef

Zheng, Y.J.[Yuan-Jie], Kambhamettu, C.[Chandra], Bauer, T.[Thomas], Steiner, K.[Karl],
Accurate estimation of pulmonary nodule's growth rate in CT images with nonrigid registration and precise nodule detection and segmentation,
MMBIA09(101-108).
IEEE DOI 0906
BibRef

Wei, E.[Erling], Yan, J.[Jiayong], Xu, M.[Mantao], Zhang, J.W.[Ji-Wu],
A novel segmentation algorithm for pulmonary nodule in chest radiograph,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Suzuki, K.[Kenji], Shi, Z.H.[Zheng-Hao], Zhang, J.[Jun],
Supervised enhancement of lung nodules by use of a massive-training artificial neural network (MTANN) in computer-aided diagnosis (CAD),
ICPR08(1-4).
IEEE DOI 0812
BibRef

Bauer, C.[Christian], Bischof, H.[Horst],
A Novel Approach for Detection of Tubular Objects and Its Application to Medical Image Analysis,
DAGM08(xx-yy).
Springer DOI 0806
BibRef

Zheng, Y.J.[Yuan-Jie], Steiner, K.[Karl], Bauer, T.[Thomas], Yu, J.Y.[Jing-Yi], Shen, D.G.[Ding-Gang], Kambhamettu, C.[Chandra],
Lung Nodule Growth Analysis from 3D CT Data with a Coupled Segmentation and Registration Framework,
MMBIA07(1-8).
IEEE DOI 0710
BibRef

Antonelli, M.[Michela], Yang, G.Z.[Guang-Zhong],
Lung Nodule Detection using Eye-Tracking,
ICIP07(II: 457-460).
IEEE DOI 0709
BibRef

Memarian, N., Alirezaie, J., Babyn, P.,
Computerized Detection of Lung Nodules with an Enhanced False Positive Reduction Scheme,
ICIP06(1921-1924).
IEEE DOI 0610
BibRef

Sousa, A.V.[António V.], Mendonça, A.M.[Ana Maria], Campilho, A.[Aurélio],
Chromatographic Pattern Recognition Using Optimized One-Class Classifiers,
IbPRIA09(449-456).
Springer DOI 0906
BibRef
Earlier:
Minimizing the Imbalance Problem in Chromatographic Profile Classification with One-Class Classifiers,
ICIAR08(xx-yy).
Springer DOI 0806
BibRef
Earlier:
The Class Imbalance Problem in TLC Image Classification,
ICIAR06(II: 513-523).
Springer DOI 0610
BibRef

Pereira, C.S.[Carlos S.], Fernandes, H.[Hugo], Mendonça, A.M.[Ana Maria], Campilho, A.[Aurélio],
Detection of Lung Nodule Candidates in Chest Radiographs,
IbPRIA07(II: 170-177).
Springer DOI 0706
BibRef

Pereira, C.S.[Carlos S.], Mendonça, A.M.[Ana Maria], Campilho, A.[Aurélio],
Evaluation of Contrast Enhancement Filters for Lung Nodule Detection,
ICIAR07(878-888).
Springer DOI 0708
BibRef

Pereira, C.S.[Carlos S.], Alexandre, L.A.[Luís A.], Mendonça, A.M.[Ana Maria], Campilho, A.[Aurélio],
A Multiclassifier Approach for Lung Nodule Classification,
ICIAR06(II: 612-623).
Springer DOI 0610
BibRef

Kubota, T.[Toshiro], Okada, K.[Kazunori],
Estimating Diameters of Pulmonary Nodules with Competition-Diffusion and Robust Ellipsoid Fit,
CVBIA05(324-334).
Springer DOI 0601
BibRef

Campadelli, P., Casiraghi, E., Valentini, G.,
Lung Nodules Detection and Classification,
ICIP05(I: 1117-1120).
IEEE DOI 0512
BibRef

Corrêa Silva, A.[Aristófanes], Cardoso de Paiva, A.[Anselmo], Carvalho, P.C.P.[Paulo C.P.], Gattass, M.[Marcelo],
Semivariogram and SGLDM Methods Comparison for the Diagnosis of Solitary Lung Nodule,
IbPRIA05(II:479).
Springer DOI 0509
BibRef

Silva, J.S.[José Silvestre], Santos, B.S.[Beatriz Sousa], Silva, A.[Augusto], Madeira, J.[Joaquim],
A Level-Set Based Volumetric CT Segmentation Technique: A Case Study with Pulmonary Air Bubbles,
ICIAR04(II: 68-75).
Springer DOI 0409
BibRef

Nakamura, Y., Fukano, G., Takizawa, H., Mizuno, S., Yamamoto, S., Matsumoto, T., Tateno, Y., Iinuma, T.,
Eigen nodule: view-based recognition of lung nodule in chest X-ray CT images using subspace method,
ICPR04(IV: 681-684).
IEEE DOI 0409
BibRef

Takizawa, H., Yamamoto, S., Matsumoto, T., Tateno, Y., Iinuma, T., Matsumoto, M.,
Recognition of lung nodules from x-ray ct images using 3d markov random field models,
ICPR02(I: 99-102).
IEEE DOI 0211
BibRef

Mousa, W.A.H., Khan, M.A.U.,
Lung nodule classification utilizing support vector machines,
ICIP02(III: 153-156).
IEEE DOI 0210
BibRef

Kawata, Y., Niki, N., Ohrnatsu, H., Kusumato, M., Kakinuma, R., Mori, K., Nishiyama, H., Eguchi, K., Kaneko, M., Moriyama, N.,
Three-dimensional CT image retrieval in a database of pulmonary nodules,
ICIP02(III: 149-152).
IEEE DOI 0210
BibRef

Kawata, Y., Niki, N., Ohmatsu, H., Kakinuma, R., Mori, K., Eguchi, K., Kaneko, M., Moriyama, N.,
Curvature based analysis of internal structure of pulmonary nodules using thin-section CT images,
ICIP98(III: 851-855).
IEEE DOI 9810
BibRef

Minami, K., Kawata, Y., Niki, N., Mori, K., Ohmatsu, H., Kakinuma, R., Eguchi, K., Kusumoto, M., Kaneko, M., Moriyama, N.,
Computerized Characterization of Contrast Enhancement Patterns for Classifying Pulmonary Nodules,
ICIP01(II: 897-900).
IEEE DOI 0108
BibRef
Earlier: Takagi, N., A2, A3 only: ICIP00(Vol I: 188-191).
IEEE DOI 0008
BibRef

Kawata, Y., Niki, N., Ohmatsu, H., Kusumoto, M., Kakinuma, R., Mori, K., Nishiyama, H., Eguchi, K., Kaneko, M., Moriyama, N.,
Computerized Analysis of 3-d Pulmonary Nodule Images in Surrounding and Internal Structure Feature Spaces,
ICIP01(II: 889-892).
IEEE DOI 0108
BibRef

Kubo, M., Kawata, Y., Niki, N., Eguchi, K., Ohmatsu, H., Kakinuma, R., Kaneko, M., Kusumoto, M., Moriyama, N., Mori, K., Nishiyama, H.,
Automatic Extraction of Pulmonary Fissures from Multidetector-row CT Images,
ICIP01(III: 1091-1094).
IEEE DOI 0108
BibRef

Kubota, K., Kubo, M., Kawata, Y., Niki, N., Eguchi, K., Omatsu, H., Kakinuma, R., Kaneko, M., Moriyama, N.,
The Results in the Clinical Trial of CAD System for Lung Cancer Using Helical CT Images,
ICIP01(I: 313-316).
IEEE DOI 0108
BibRef

Kawata, Y., Niki, N.,
Surrounding Structures Analysis of Pulmonary Nodules Using Differential Geometry Based Vector Fields,
ICIP00(Vol III: 424-427).
IEEE DOI 0008
BibRef
And:
Internal Structure Analysis of Pulmonary Nodules in Topological and Histogram Feature Spaces,
ICIP00(Vol I: 168-171).
IEEE DOI 0008
BibRef

Sammouda, M., Niki, N.,
Analysis of Color Images of Tissues Derived from Patients with Adenocarcinoma of the Lung,
ICIP00(Vol I: 192-195).
IEEE DOI 0008
BibRef

Kubo, M., Niki, N., Eguchi, K., Kaneko, M., Kusumoto, M., Moriyama, N., Omatsu, H., Kakinuma, R., Nishiyama, H., Mori, K., Yamaguchi,
Extraction of Pulmonary Fissures from HRCT Images Based on Surface Curvatures Analysis and Morphology Filters,
ICPR00(Vol I: 490-493).
IEEE DOI 0009
BibRef

Yamamoto, T., Ukai, Y., Kubo, M., Niki, N.,
Computer Aided Diagnosis System with Functions to Assist Comparative Reading for Lung Cancer Based on Helical CT Image,
ICIP00(Vol I: 180-183).
IEEE DOI 0008
BibRef

Kubo, M., Niki, N.,
Extraction of Pulmonary Fissures from Thin-section CT Images Using Calculation of Surface-curvatures and Morphology Filters,
ICIP00(Vol II: 637-640).
IEEE DOI 0008
BibRef

Kubo, M., Tozaki, T., Niki, N., Nakagawa, S., Yamaguchi, N., Eguchi, K., Kaneko, M., Omatsu, H., and Moriyama, N.,
Bias Field Correction of Chest Thin Section CT Images,
ICIP97(III: 551-554).
IEEE DOI BibRef 9700

Kawata, Y., Niki, N., Ohmatsu, H., Kusumoto, M., Kakinuma, R., Mori, K., Nishiyama, H., Eguchi, K., Kaneko, M., Moriyama, N.,
Computerized Analysis of Pulmonary Nodules in Topological and Histogram Feature Spaces,
ICPR00(Vol IV: 332-335).
IEEE DOI 0009
BibRef

Kawata, Y., Niki, N., Ohmatsu, H., Kusumoto, M., Kakinuma, R., Mori, K., Nishiyama, H., Eguchi, K., Kaneko, M., Moriyama, N.,
Computer aided differential diagnosis of pulmonary nodules using curvature based analysis,
CIAP99(470-475).
IEEE DOI 9909
BibRef

Ohmatsu, H.[Hironobu], Kawata, Y.[Yoshiki], Niki, N.[Noboru], Kaneko, M., Satoh, H.[Hitoshi], Kanazawa, K., Eguchi, K.[Kenji], Moriyama, N.[Noriyuki], Kakinuma, Y.,
Computer-Aided Diagnosis for Pulmonary Nodules Based on Helical CT Images,
ICPR98(Vol II: 1683-1685).
IEEE DOI 9808
BibRef

Kawata, Y., Kanazawa, K., Toshioka, S., Niki, N., Satoh, H., Ohmatsu, H., Eguchi, K., Moriyama, N.,
Computer Aided Diagnosis System for Lung Cancer Based on Helical CT Images,
CIAP97(II: 420-427).
Springer DOI 9709
BibRef
Earlier: Only: A2, A4, Add: Kubo, M., A5, A6, A7, A8: ICPR96(III: 381-385).
IEEE DOI 9608
(Univ. of Tokushima, J) BibRef

Tozaki, T., Kawata, Y., Niki, N., Ohmatsu, H., Eguchi, K., Moriyama, N.,
Three Dimensional Analysis of Lung Areas Using Thin Slice CT Images,
ICPR96(III: 548-552).
IEEE DOI 9608
(Univ. of Tokushima, J) BibRef

Kawata, Y., Niki, N., Ohmatsu, H., Kakinuma, R., Kushmoto, M., Mori, K., Nishiyama, N., Eguchi, K., Kaneko, M., Moriyama, N.,
Classification of Pulmonary Nodules in Thin-section CT Images by Using Multi-scale Curvature Indexes,
ICIP99(II:197-201).
IEEE DOI BibRef 9900

Kawata, Y., Niki, N., Ohmatsu, H., Eguchi, K., Kaneko, M., and Moriyama, N.,
Classification of Pulmonary Nodules in Thin Section CT Images Based on Shape Characterization,
ICIP97(III: 528-530).
IEEE DOI BibRef 9700

Kawata, Y.[Yoshiki], Kaneko, M., Eguchi, K.[Kenji], Kakinuma, R., Moriyama, N.[Noriyuki], Niki, N.[Noboru], Ohmatsu, H.[Hironobu],
Curvature Based Analysis of Pulmonary Nodules Using Thin-Section CT Images,
ICPR98(Vol I: 361-363).
IEEE DOI 9808
BibRef

Takagi, N., Kawata, Y., Niki, N., Mori, K., Ohmatsu, H., Kakinuma, R., Eguchi, K., Kusumoto, M., Kaneko, M., Moriyama, N.,
3D analysis of solitary pulmonary nodules based on contrast enhanced dynamic CT,
ICIP99(III:416-420).
IEEE DOI BibRef 9900

Tanaka, A., Tozaki, T., Kawata, Y., Niki, N., Ohmatsu, H., Kakimura, R., Kaneko, M., Eguchi, K., Moriyama, N.,
Pulmonary Organs Analysis Method and Its Evaluation Based on Thoracic Thin-section CT Images,
ICIP99(III:421-425).
IEEE DOI BibRef 9900

Mukaibo, T., Kawata, Y., Niki, N., Ohmatsu, H., Kakinuma, R., Kaneko, M., Eguchi, K., Moriyama, K.,
Classification of Pulmonary Blood Vessel Using Multidetector-row CT Images,
ICIP01(II: 841-844).
IEEE DOI 0108
BibRef

Chen, X.[Xuan], Hasegawa, J.I., Toriwaki, J.I.,
Quantitative diagnosis of pneumoconiosis based on recognition of small rounded opacities in chest X-ray images,
ICPR88(I: 462-464).
IEEE DOI 8811
BibRef

Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Tuberculosis Analysis, Tuberculosis Bacilli .


Last update:Nov 11, 2017 at 13:31:57