20.8.3.1 Liver Disease, Tomography, CAT Analysis

Chapter Contents (Back)
Reconstruction. Liver Disease. Tomography.

Bleck, J.S., Ranft, U., Gebel, M., Hecker, H., Westhoff-Bleck, M., Thiesemann, C., Wagner, S., Manns, M.,
Random field models in the textural analysis of ultrasonic images of the liver,
MedImg(15), No. 6, December 1996, pp. 796-801.
IEEE Top Reference. 0203
BibRef

Kadah, Y.M., Farag, A.A., Zurada, J.M., Badawi, A.M., Youssef, A.B.M.,
Classification algorithms for quantitative tissue characterization of diffuse liver disease from ultrasound images,
MedImg(15), No. 4, August 1996, pp. 466-478.
IEEE Top Reference. 0203
BibRef

Wu, C.M., Chen, Y.C.,
Multi-Threshold Dimension Vector for Texture Analysis and Its Application to Liver Tissue Classification,
PR(26), No. 1, January 1993, pp. 137-144.
WWW Link. BibRef 9301

Carrillo, A., Duerk, J.L., Lewin, J.S., Wilson, D.L.,
Semiautomatic 3-D image registration as applied to interventional MRI liver cancer treatment,
MedImg(19), No. 3, March 2000, pp. 175-185.
IEEE Top Reference. 0110
BibRef

Meyer, C.R., Park, H.[Hyunjin], Balter, J.M., Bland, P.H.,
Method for quantifying volumetric lesion change in interval liver CT examinations,
MedImg(22), No. 6, June 2003, pp. 776-781.
IEEE Abstract. 0308
BibRef

Bauer, C., Aurich, V., Arzhaeva, Y., Styner, M.A., van Ginneken, B., Heimann, T., Beichel, R., Chi, Y.[Ying], Cordova, A., Dawant, B.M., Fidrich, M., Furst, J.D., Furukawa, D., Grenacher, L., Hornegger, J., Kainmueller, D., Kitney, R.I., Kobatake, H., Lamecker, H., Lange, T., Lee, J.J.[Jeong-Jin], Lennon, B., Li, R.[Rui], Li, S.[Senhu], Meinzer, H.P., Nemeth, G., Raicu, D.S., Rau, A.M., van Rikxoort, E.M., Rousson, M., Rusko, L., Saddi, K.A., Schmidt, G., Seghers, D., Shimizu, A., Slagmolen, P., Sorantin, E., Soza, G., Susomboon, R., Becker, C., Beck, A., Bekes, G., Bello, F., Binnig, G., Bischof, H., Bornik, A., Cashman, P., Waite, J.M., Wimmer, A., Wolf, I.,
Comparison and Evaluation of Methods for Liver Segmentation From CT Datasets,
MedImg(28), No. 8, August 2009, pp. 1251-1265.
IEEE DOI 0909
Survey, Liver Segmentation. Evaluation, Liver Segmentation. BibRef

Lee, W.L.[Wen-Li], Chen, Y.C.[Yung-Chang], Hsieh, K.S.[Kai-Sheng],
Ultrasonic liver tissues classification by fractal feature vector based on M -band wavelet transform,
MedImg(22), No. 3, March 2003, pp. 382-392.
IEEE Abstract. 0306
BibRef

Chen, S.R.[Si-Rong], Ho, C., Feng, D.[Dagan], Chi, Z.[Zheru],
Tracer kinetic modeling of C11-acetate applied in the liver with positron emission tomography,
MedImg(23), No. 4, April 2004, pp. 426-432.
IEEE Abstract. 0406
BibRef

Blackall, J.M., Penney, G.P., King, A.P., Hawkes, D.J.,
Alignment of sparse freehand 3-D ultrasound with preoperative images of the liver using models of respiratory motion and deformation,
MedImg(24), No. 11, November 2005, pp. 1405-1416.
IEEE DOI 0512
BibRef

Lim, S.J.[Seong-Jae], Jeong, Y.Y.[Yong-Yeon], Ho, Y.S.[Yo-Sung],
Automatic liver segmentation for volume measurement in CT Images,
JVCIR(17), No. 4, August 2006, pp. 860-875.
WWW Link. 0711
Liver segmentation; Volume measurement; Morphological filtering; Deformable contouring; Computer-aided diagnosis BibRef

Casiraghi, E.[Elena], Campadelli, P.[Paola], Pratissoli, S.[Stella], Lombardi, G.[Gabriele],
Automatic Abdominal Organ Segmentation from CT images,
ELCVIA(8), No. 1, July 2009, pp. xx-yy.
WWW Link. 0909
BibRef
Earlier: A2, A1, A4, Only:
Automatic liver segmentation from abdominal CT scans,
CIAP07(731-736).
IEEE DOI 0709
BibRef

Bharathi, V.S.[V. Subbiah], Ganesan, L.,
Orthogonal moments based texture analysis of CT liver images,
PRL(29), No. 13, 1 October 2008, pp. 1868-1872.
WWW Link. 0804
Orthogonal moments; Texture; Feature selection; Classifier BibRef

Feuerstein, M., Mussack, T., Heining, S.M., Navab, N.,
Intraoperative Laparoscope Augmentation for Port Placement and Resection Planning in Minimally Invasive Liver Resection,
MedImg(27), No. 3, March 2008, pp. 355-369.
IEEE DOI 0803
BibRef

Feuerstein, M., Reichl, T., Vogel, J., Traub, J., Navab, N.,
Magneto-Optical Tracking of Flexible Laparoscopic Ultrasound: Model-Based Online Detection and Correction of Magnetic Tracking Errors,
MedImg(28), No. 6, June 2009, pp. 951-967.
IEEE DOI 0906
BibRef

Reichl, T., Gardiazabal, J., Navab, N.,
Electromagnetic Servoing: A New Tracking Paradigm,
MedImg(32), No. 8, 2013, pp. 1526-1535.
IEEE DOI 1308
Instrument and patient localization and tracking BibRef

Mescam, M., Kretowski, M., Bezy-Wendling, J.,
Multiscale Model of Liver DCE-MRI Towards a Better Understanding of Tumor Complexity,
MedImg(29), No. 3, March 2010, pp. 699-707.
IEEE DOI 1003
BibRef

Buerger, C., Clough, R.E., King, A.P., Schaeffter, T., Prieto, C.,
Nonrigid Motion Modeling of the Liver From 3-D Undersampled Self-Gated Golden-Radial Phase Encoded MRI,
MedImg(31), No. 3, March 2012, pp. 805-815.
IEEE DOI 1203
BibRef

Bakas, S.[Spyridon], Chatzimichail, K.[Katerina], Hoppe, A.[Andreas], Galariotis, V.[Vasileios], Hunter, G.[Gordon], Makris, D.[Dimitrios],
Histogram-based Motion Segmentation and Characterisation of Focal Liver Lesions in CEUS,
BMVA(2012), No. 7, 2012, pp. 1-14.
PDF File. 1209
BibRef

Bakas, S.[Spyridon], Hoppe, A.[Andreas], Chatzimichail, K.[Katerina], Galariotis, V.[Vasileios], Hunter, G.[Gordon], Makris, D.[Dimitrios],
Focal Liver Lesion Tracking in Ceus for Characterisation Based on Dynamic Behaviour,
ISVC12(I: 32-41).
Springer DOI 1209
BibRef

Linguraru, M.G., Richbourg, W.J., Liu, J.F.[Jian-Fei], Watt, J.M., Pamulapati, V., Wang, S.J.[Shi-Jun], Summers, R.M.,
Tumor Burden Analysis on Computed Tomography by Automated Liver and Tumor Segmentation,
MedImg(31), No. 10, October 2012, pp. 1965-1976.
IEEE DOI 1210
BibRef

Ho, H., Sorrell, K., Peng, L., Yang, Z., Holden, A., Hunter, P.,
Hemodynamic Analysis for Transjugular Intrahepatic Portosystemic Shunt (TIPS) in the Liver Based on a CT-Image,
MedImg(32), No. 1, January 2013, pp. 92-98.
IEEE DOI 1301
BibRef

Kumar, S.S., Moni, R.S., Rajeesh, J.,
Automatic liver and lesion segmentation: A primary step in diagnosis of liver diseases,
SIViP(7), No. 1, January 2013, pp. 163-172.
WWW Link. 1301
BibRef

Foruzan, A.H.[Amir H.], Chen, Y.W.[Yen-Wei], Zoroofi, R.A.[Reza A.], Furukawa, A.[Akira], Sato, Y.[Yoshinobu], Hori, M.[Masatoshi], Tomiyama, N.[Noriyuki],
Segmentation of Liver in Low-Contrast Images Using K-Means Clustering and Geodesic Active Contour Algorithms,
IEICE(E96-D), No. 4, April 2013, pp. 798-807.
WWW Link. 1304
BibRef

Shimizu, A.[Akinobu], Narihira, T.[Takuya], Kobatake, H.[Hidefumi], Furukawa, D.[Daisuke], Nawano, S.[Shigeru], Shinozaki, K.[Kenji],
Ensemble Learning Based Segmentation of Metastatic Liver Tumours in Contrast-Enhanced Computed Tomography,
IEICE(E96-D), No. 4, April 2013, pp. 864-868.
WWW Link. 1304
BibRef

Cifor, A., Risser, L., Chung, D., Anderson, E.M., Schnabel, J.A.,
Hybrid Feature-Based Diffeomorphic Registration for Tumor Tracking in 2-D Liver Ultrasound Images,
MedImg(32), No. 9, 2013, pp. 1647-1656.
IEEE DOI 1309
Block-matching; diffeomorphic registration; tumor tracking; ultrasound BibRef

Rucker, D.C., Wu, Y.[Yifei], Clements, L.W., Ondrake, J.E., Pheiffer, T.S., Simpson, A.L., Jarnagin, W.R., Miga, M.I.,
A Mechanics-Based Nonrigid Registration Method for Liver Surgery Using Sparse Intraoperative Data,
MedImg(33), No. 1, January 2014, pp. 147-158.
IEEE DOI 1402
biological tissues BibRef

Peng, J.[Jialin], Wang, Y.[Ye], Kong, D.[Dexing],
Liver segmentation with constrained convex variational model,
PRL(43), No. 1, 2014, pp. 81-88.
Elsevier DOI 1404
Liver segmentation BibRef

Peng, J.L.[Jia-Lin], Wang, J.W.[Jin-Wei], Kong, D.X.[De-Xing],
A new convex variational model for liver segmentation,
ICPR12(3754-3757).
WWW Link. 1302
Award, ICPR. BibRef

Depeursinge, A., Kurtz, C., Beaulieu, C.F., Napel, S., Rubin, D.L.,
Predicting Visual Semantic Descriptive Terms From Radiological Image Data: Preliminary Results With Liver Lesions in CT,
MedImg(33), No. 8, August 2014, pp. 1669-1676.
IEEE DOI 1408
Computational modeling BibRef

Lamb, P., Sahani, D.V., Fuentes-Orrego, J.M., Patino, M., Ghosh, A., Mendonca, P.R.S.,
Stratification of Patients With Liver Fibrosis Using Dual-Energy CT,
MedImg(34), No. 3, March 2015, pp. 807-815.
IEEE DOI 1503
biological tissues BibRef

Krishnan, K.R.[K. Raghesh], Radhakrishnan, S.,
Focal and diffused liver disease classification from ultrasound images based on isocontour segmentation,
IET-IPR(9), No. 4, 2015, pp. 261-270.
DOI Link 1505
biodiffusion BibRef

Virmani, J.[Jitendra], Kumar, V.[Vinod], Kalra, N.[Naveen], Khandelwal, N.[Niranjan],
PCA-SVM based CAD System for Focal Liver Lesions using B-Mode Ultrasound Images,
DefenceScience(63), No. 5, September 2013, pp. 478-486. 1506
BibRef

Virmani, J.[Jitendra], Kumar, V.[Vinod], Kalra, N.[Naveen], Khandelwal, N.[Niranjan],
Neural Network Ensemble Based CAD System for Focal Liver Lesions from B-Mode Ultrasound,
DigitalImaging(), April, 2014.
Springer DOI 1506
Incomplete Reference. BibRef

Virmani, J.[Jitendra], Kumar, V.[Vinod], Kalra, N.[Naveen], Khandelwal, N.[Niranjan],
SVM-Based Characterization of Liver Ultrasound Images Using Wavelet Packet Texture Descriptors,
DigitalImaging(26), No. 3, October, 2012, pp. 530-543.
Springer DOI 1506
BibRef

Virmani, J.[Jitendra], Kumar, V.[Vinod], Kalra, N.[Naveen], Khandelwal, N.[Niranjan],
SVM-based characterisation of liver cirrhosis by singular value decomposition of GLCM matrix,
AISC(3), No. 3, 2013, pp. 276-296. 1506
BibRef

Virmani, J.[Jitendra], Kumar, V.[Vinod], Kalra, N.[Naveen], Khandelwal, N.[Niranjan],
Prediction of liver cirrhosis based on multiresolution texture descriptors from B-mode ultrasound,
ConvergenceComputing(1), No. 1, 2013 pp. 19-37. 1506
BibRef

Virmani, J.[Jitendra], Kumar, V.[Vinod], Kalra, N.[Naveen], Khandelwal, N.[Niranjan],
Characterization of Primary and Secondary Malignant Liver Lesions from B-Mode Ultrasound,
DigitalImaging(), February, 2013.
Springer DOI 1506
Incomplete Reference. BibRef

Virmani, J.[Jitendra], Kumar, V.[Vinod], Kalra, N.[Naveen], Khandelwal, N.[Niranjan],
A comparative study of computer-aided classification systems for focal hepatic lesions from B-mode ultrasound,
MedEngTech(37), No. 4, 2013, pp. 202-306.
DOI Link 1506
BibRef

Manth, N.[Nimisha], Virmani, J.[Jitendra], Bhadauria, H.S.,
Despeckle Filtering: Performance Evaluation for Malignant Focal Hepatic Lesions,
ICCSGD15(1897-1902). BibRef 1500

Virmani, J.[Jitendra], Kumar, V.[Vinod], Kalra, N.[Naveen], Khandelwal, N.[Niranjan],
Prediction of cirrhosis from liver ultrasound B-mode images based on Laws' masks analysis,
ICIIP11(1-5).
IEEE DOI 1112
BibRef

Virmani, J.[Jitendra], Kumar, V.[Vinod], Kalra, N.[Naveen], Khandelwal, N.[Niranjan],
A Rapid Approach for Prediction of Liver Cirrhosis based on First Order Statistics,
MSPCT11(212-215). 1506
BibRef

Virmani, J.[Jitendra], Kumar, V.[Vinod], Kalra, N.[Naveen], Khandelwal, N.[Niranjan],
Prediction of Cirrhosis Based on Singular Value Decomposition of Gray Level Co-Occurence Matrix and a Neural Network Classifier,
E-Systems11(146-151).
DOI Link 1506
BibRef

Audigier, C., Mansi, T., Delingette, H., Rapaka, S., Mihalef, V., Carnegie, D., Boctor, E., Choti, M., Kamen, A., Ayache, N., Comaniciu, D.,
Efficient Lattice Boltzmann Solver for Patient-Specific Radiofrequency Ablation of Hepatic Tumors,
MedImg(34), No. 7, July 2015, pp. 1576-1589.
IEEE DOI 1507
Biological system modeling BibRef

Shi, C.F.[Chang-Fa], Cheng, Y.Z.[Yuan-Zhi], Liu, F.[Fei], Wang, Y.D.[Ya-Dong], Bai, J.[Jing], Tamura, S.[Shinichi],
A hierarchical local region-based sparse shape composition for liver segmentation in CT scans,
PR(50), No. 1, 2016, pp. 88-106.
Elsevier DOI 1512
Liver segmentation BibRef

Li, G.D.[Guo-Dong], Chen, X.J.[Xin-Jian], Shi, F.[Fei], Zhu, W.[Weifang], Tian, J.[Jie], Xiang, D.[Dehui],
Automatic Liver Segmentation Based on Shape Constraints and Deformable Graph Cut in CT Images,
IP(24), No. 12, December 2015, pp. 5315-5329.
IEEE DOI 1512
computerised tomography BibRef

Dakua, S.P.[Sarada Prasad], Abinahed, J.[Julien], Al-Ansari, A.A.[Abdulla A.],
Pathological liver segmentation using stochastic resonance and cellular automata,
JVCIR(34), No. 1, 2016, pp. 89-102.
Elsevier DOI 1601
CT BibRef

Christofides, D., Leen, E., Averkiou, M.A.,
Evaluation of the Accuracy of Liver Lesion DCEUS Quantification With Respiratory Gating,
MedImg(35), No. 2, February 2016, pp. 622-629.
IEEE DOI 1602
Imaging BibRef

Liang, X., Lin, L., Cao, Q., Huang, R., Wang, Y.,
Recognizing Focal Liver Lesions in CEUS With Dynamically Trained Latent Structured Models,
MedImg(35), No. 3, March 2016, pp. 713-727.
IEEE DOI 1603
Cancer BibRef

McDermott, J.[James], Forsyth, R.S.[Richard S.],
Diagnosing a disorder in a classification benchmark,
PRL(73), No. 1, 2016, pp. 41-43.
Elsevier DOI 1604
Machine learning. Liver disorder database. BibRef

Norajitra, T.[Tobias], Maier-Hein, K.H.[Klaus H.],
3D Statistical Shape Models Incorporating Landmark-Wise Random Regression Forests for Omni-Directional Landmark Detection,
MedImg(36), No. 1, January 2017, pp. 155-168.
IEEE DOI 1701
Adaptation models BibRef

Chaieb, F.[Faten], Said, T.B.[Tarek Ben], Mabrouk, S.[Sabra], Ghorbel, F.[Faouzi],
Accelerated liver tumor segmentation in four-phase computed tomography images,
RealTimeIP(13), No. 1, March 2017, pp. 121-133.
Springer DOI 1704
BibRef


Borga, M., Andersson, T., Leinhard, O.D.,
Semi-supervised learning of anatomical manifolds for atlas-based segmentation of medical images,
ICPR16(3146-3149)
IEEE DOI 1705
Biomedical imaging, Image segmentation, Liver, Magnetic resonance imaging, Manifolds, Prototypes, Silicon BibRef

Xu, Y., Lin, L., Hu, H., Wang, D., Liu, Y., Wang, J., Han, X., Chen, Y.W.,
Bag of temporal co-occurrence words for retrieval of focal liver lesions using 3D multiphase contrast-enhanced CT images,
ICPR16(2282-2287)
IEEE DOI 1705
Computed tomography, Feature extraction, Frequency locked loops, Lesions, Liver, Visualization, Vocabulary, Computer-aided diagnosis (CAD) systems, bag of temporal co-occurrence words (BoTCoW), bag of visual words (BoVW), enhancement pattern, multiphase, contrast-enhanced, CT, images BibRef

Han, X.H.[Xian-Hua], Wang, J.[Jian], Konno, Y.[Yuu], Chen, Y.W.[Yen-Wei],
Bayesian Saliency Model for Focal Liver Lesion Enhancement and Detection,
MCBMIIA16(III: 32-45).
Springer DOI 1704
BibRef

Gueziri, H.E.[Houssem-Eddine], Tremblay, S.[Sebastien], Laporte, C.[Catherine], Brooks, R.[Rupert],
Graph-Based 3D-Ultrasound Reconstruction of the Liver in the Presence of Respiratory Motion,
RAMBO16(48-57).
Springer DOI 1703
BibRef

Batool, N.,
Detection and spatial analysis of hepatic steatosis in histopathology images using sparse linear models,
IPTA16(1-6)
IEEE DOI 1703
blood vessels BibRef

Sedlar, J., Bajger, M., Caon, M., Lee, G.,
Model-Guided Segmentation of Liver in CT and PET-CT Images of Child Patients Based on Statistical Region Merging,
DICTA16(1-8)
IEEE DOI 1701
Computational modeling BibRef

Conegliano, A.[Andrew], Schulze, J.P.[Jürgen P.],
Realistic 3D Modeling of the Liver from MRI Images,
ISVC16(II: 223-232).
Springer DOI 1701
BibRef

Al-Kadi, O.S.,
Multiscale Nakagami parametric imaging for improved liver tumor localization,
ICIP16(3384-3388)
IEEE DOI 1610
Estimation BibRef

Fenwa, O.D., Ajala, F.A., Aku, A.M.,
Performance evaluation of support vector machine and artificial neural network in the classification of liver cirhosis and hemachromatosis,
ICCVIA15(1-6)
IEEE DOI 1603
image classification BibRef

Kitrungrotsakul, T.[Titinunt], Han, X.H.[Xian-Hua], Chen, Y.W.[Yen-Wei],
Liver segmentation using superpixel-based graph cuts and restricted regions of shape constrains,
ICIP15(3368-3371)
IEEE DOI 1512
estimated shape constrain BibRef

Chen, B.[Bin], Chen, Y.[Yang], Yang, G.[Guanyu], Meng, J.Y.[Jing-Yu], Zeng, R.[Rui], Luo, L.M.[Li-Min],
Segmentation of liver tumor via nonlocal active contours,
ICIP15(3745-3748)
IEEE DOI 1512
BibRef

Conze, P.H.[Pierre-Henri], Rousseau, F.[Franēois], Noblet, V.[Vincent], Heitz, F.[Fabrice], Memeo, R.[Riccardo], Pessaux, P.[Patrick],
Semi-automatic Liver Tumor Segmentation in Dynamic Contrast-Enhanced CT Scans Using Random Forests and Supervoxels,
MLMI15(212-219).
Springer DOI 1511
BibRef

Domingo, J.[Juan], Dura, E.[Esther], Ayala, G.[Guillermo], Ruiz-Espańa, S.[Silvia],
Means of 2D and 3D Shapes and Their Application in Anatomical Atlas Building,
CAIP15(I:522-533).
Springer DOI 1511
BibRef

Dura, E.[Esther], Domingo, J.[Juan], Rojas-Arboleda, A.F., Marti-Bonmati, L.,
Mean sets for building 3D probabilistic liver atlas from perfusion MR images,
IPTA12(186-191)
IEEE DOI 1503
biomedical MRI BibRef

Goceri, E., Unlu, M.Z., Guzelis, C., Dicle, O.,
An automatic level set based liver segmentation from MRI data sets,
IPTA12(192-197)
IEEE DOI 1503
approximation theory BibRef

Li, X.[Xuhui], Huang, C.[Cheng], Jia, F.C.[Fu-Cang], Li, Z.M.[Zong-Min], Fang, C.H.[Chi-Hua], Fan, Y.F.[Ying-Fang],
Automatic Liver Segmentation Using Statistical Prior Models and Free-form Deformation,
MCV14(181-188).
Springer DOI 1501
BibRef

Deng, J.P.[Jun-Ping], Han, X.H.[Xian-Hua], Xu, G.[Gang], Chen, Y.W.[Yen-Wei],
Sparse and Low Rank Matrix Decomposition Based Local Morphological Analysis and Its Application to Diagnosis of Cirrhosis Livers,
ICPR14(3363-3368)
IEEE DOI 1412
Accuracy BibRef

Yan, Z.N.[Zhen-Nan], Tan, C.W.[Chao-Wei], Zhang, S.T.[Shao-Ting], Zhou, Y.[Yan], Belaroussi, B.[Boubakeur], Yu, H.J.[Hui Jing], Miller, C.[Colin], Metaxas, D.N.[Dimitris N.],
Automatic Liver Segmentation and Hepatic Fat Fraction Assessment in MRI,
ICPR14(3280-3285)
IEEE DOI 1412
Accuracy BibRef

Garnier, M.[Mickaėl], Ali, M.A.[Maya Alsheh], Seguin, J.[Johanne], Mignet, N.[Nathalie], Hurtut, T.[Thomas], Wendling, L.[Laurent],
Grading Cancer from Liver Histology Images Using Inter and Intra Region Spatial Relations,
ICIAR14(II: 247-254).
Springer DOI 1410
BibRef

Anter, A.M., Hassanien, A.E., Schaefer, G.,
Automatic Segmentation and Classification of Liver Abnormalities Using Fractal Dimension,
ACPR13(937-941)
IEEE DOI 1408
computerised tomography BibRef

Ogihara, H., Fujita, Y., Hamamoto, Y., Iizuka, N., Oka, M.,
Classification Based on Boolean Algebra and Its Application to the Prediction of Recurrence of Liver Cancer,
ACPR13(838-841)
IEEE DOI 1408
Boolean algebra BibRef

Thiriet, M.[Marc], Solovchuk, M.[Maxim], Sheu, T.W.H.[Tony Wen-Hann],
HIFU Treatment of Liver Cancer: Reciprocal Effect of Blood Flow and US Studied from a Patient-Specific Configuration,
CompIMAGE14(1-11).
Springer DOI 1407
BibRef

Luo, J.[Jie], Chen, Y.W.[Yen-Wei], Han, X.H.[Xian-Hua], Tateyama, T.[Tomoko], Furukawa, A.[Akira], Kanasaki, S.[Shuzo],
Pilot study of applying shape analysis to liver cirrhosis diagnosis,
ICIP13(3537-3541)
IEEE DOI 1402
Computer-Aided Diagnosis BibRef

Chen, Y.W.[Yen-Wei], Luo, J.[Jie], Han, X.H.[Xian-Hua], Tateyama, T.[Tomoko], Furukawa, A.[Akira], Kanasaki, S.[Shuzo],
A Morphologic Analysis of Cirrhotic Liver in CT Images,
ICIAR13(494-501).
Springer DOI 1307
BibRef

Ribeiro, R.[Ricardo], Marinho, R.T.[Rui Tato], Sanches, J.M.[Joćo Miguel],
Cirrhosis Prognostic Quantification with Ultrasound: An Approximation to Model for End-Stage Liver Disease,
IbPRIA13(551-558).
Springer DOI 1307
BibRef

Wu, D.[Dijia], Liu, D.[David], Suehling, M.[Michael], Zhou, K.S.[Kevin S.], Tietjen, C.[Christian],
A Cascade Learning Method for Liver Lesion Detection in CT Images,
MCVM12(206-214).
Springer DOI 1305
BibRef

Weon, C.J.[Chi Jun], Nam, W.H.[Woo Hyun], Lee, D.[Duhgoon], Hwang, Y.[Youngkyoo], Kim, J.B.[Jung-Bae], Bang, W.C.[Won-Chul], Ra, J.B.[Jong Beom],
Position estimation of moving liver lesion based on registration between 2D ultrasound and 4D MR images,
ICIP12(1677-1680).
IEEE DOI 1302
BibRef

Gloger, O.[Oliver], Toennies, K.[Klaus], Kuehn, J.P.[Jens-Peter],
Fully Automatic Liver Volumetry Using 3D Level Set Segmentation for Differentiated Liver Tissue Types in Multiple Contrast MR Datasets,
SCIA11(512-523).
Springer DOI 1105
BibRef

Kohara, S.[Shinya], Tateyama, T.[Tomoko], Foruzan, A.H.[Amir Hossein], Furukawa, A.[Akira], Kanasaki, S.[Shuzo], Wakamiya, M.[Makoto], Wei, X.[Xiong], Chen, Y.W.[Yen-Wei],
Preliminary study on statistical shape model applied to diagnosis of liver cirrhosis,
ICIP11(2921-2924).
IEEE DOI 1201
BibRef

Masuda, Y.[Yu], Tateyama, T.[Tomoko], Xiong, W.[Wei], Zhou, J.[Jiayin], Wakamiya, M.[Makoto], Kanasaki, S.[Syuzo], Furukawa, A.[Akira], Chen, Y.W.[Yen Wei],
Liver tumor detection in CT images by adaptive contrast enhancement and the EM/MPM algorithm,
ICIP11(1421-1424).
IEEE DOI 1201
BibRef

Lee, J.G.[June-Goo], Cai, W.L.[Wen-Li], Singh, A.[Anand], Yoshida, H.[Hiroyuki],
Estimation of Necrosis Volumes in Focal Liver Lesions Based on Multi-phase Hepatic CT Images,
VirtualColon10(60-67).
Springer DOI 1112
BibRef

Li, C.Y.[Chang-Yang], Wang, X.Y.[Xiu-Ying], Eberl, S.[Stefan], Fulham, M.J.[Michael J.], Yin, Y.[Yong], Feng, D.[Dagan],
Fully automated liver segmentation for low- and high- contrast CT volumes based on probabilistic atlases,
ICIP10(1733-1736).
IEEE DOI 1009
BibRef

Badakhshannoory, H.[Hossein], Saeedi, P.[Parvaneh],
Automatic Liver Segmentation from CT Scans Using Multi-layer Segmentation and Principal Component Analysis,
ISVC10(II: 342-350).
Springer DOI 1011
BibRef

Badakhshannoory, H.[Hossein], Saeedi, P.[Parvaneh], Qayumi, K.[Karim],
Liver segmentation based on deformable registration and multi-layer segmentation,
ICIP10(2549-2552).
IEEE DOI 1009
BibRef

Wu, D.[Dijia], Liu, D.[David], Suehling, M.[Michael], Tietjen, C.[Christian], Soza, G.[Grzegorz], Zhou, K.S.[Kevin S.],
Automatic detection of liver lesion from 3D computed tomography images,
MCV12(31-37).
IEEE DOI 1207
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Militzer, A.[Arne], Hager, T.[Tobias], Jager, F.[Florian], Tietjen, C.[Christian], Hornegger, J.[Joachim],
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Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Kidney Disease, Tomography, CAT Analysis, Other Methods .


Last update:May 25, 2017 at 22:18:08