Robust automated detection, segmentation and classification of hepatic tumors from CT data

Progress in Biomedical Optics and Imaging - Proceedings of SPIE

Volumn 8317, Issue , 2012, Pages

  Linguraru, Marius George ^a,b   Richbourg, William J ^a   Pamulapati, Vivek ^a   Wang, Shijun ^a   Summers, Ronald M ^a  

^a NATIONAL INSTITUTES OF HEALTH   (United States)

^b CHILDREN'S NATIONAL MEDICAL CENTER   (United States)

Author keywords

Classification; CT; Detection; Liver; Segmentation; Tumor

Indexed keywords

ACQUISITION PARAMETERS; AUTOMATED DETECTION; AUTOMATED METHODS; CT; CT DATA; CT IMAGE; FALSE DETECTIONS; FALSE POSITIVE; FEATURE SPACE; GRAPH CUT; GROUND TRUTH; HEPATIC TUMORS; INITIAL SEGMENTATION; LIVER TUMORS; TEST DATA; TRAINING AND TESTING; TUMOR DETECTION;

CLASSIFICATION (OF INFORMATION); COMPUTERIZED TOMOGRAPHY; ERROR DETECTION; FEATURE EXTRACTION; IMAGE SEGMENTATION; LIVER; MEDICAL APPLICATIONS; MOLECULAR IMAGING; TUMORS;

DIAGNOSIS;

EID: 84860752779     PISSN: 16057422     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.910617     Document Type: Conference Paper

References (20)

1. American Cancer Society, [Cancer Facts and Figures 2011], American Cancer Society, Atlanta (2011)
2. Lewis, R.L., [Liver and Biliary Tract Tumors], Saunders Elsevier Cecil Medicine. 23rd ed., Philadelphia, (2007)
3. Deng, X. Du, G., "Editorial: 3D Segmentation in the Clinic: A Grand Challenge II - Liver Tumor Segmentation," MICCAI Workshop on 3D Segmentation in the Clinic: a Grand Challenge II, (2008)
4. Stawiaski, J. Decenciere E. Bidault, F., "Interactive Liver Tumor Segmentation Using Graph-cuts and Watershed," MICCAI Workshop on 3D Segmentation in the Clinic: a Grand Challenge II (2008)
5. Moltz, J. Bornemann, L. Dicken V. Peitgen, H., "Segmentation of Liver Metastases in CT Scans by Adaptive Thresholding and Morphological Processing," MICCAI Workshop on 3D Segmentation in the Clinic: a Grand Challenge II (2008)
6. Zhou, J. et al., "Semi-automatic Segmentation of 3D Liver Tumors from CT Scans Using Voxel Classification and Propagational Learning," MICCAI Workshop on 3D Segmentation in the Clinic: a Grand Challenge II (2008)
7. Smeets, D. Stijnen, B. Loeckx, D. Dobbelaer, B. Suetens, P., "Segmentation of Liver Metastases Using a Level Set Method with Spiral-Scanning Technique and Supervised Fuzzy Pixel Classification," MICCAI Workshop on 3D Segmentation in the Clinic: a Grand Challenge II (2008)
8. Schmidt, G. Binnig, G. Kietzmann, M. Kim, J., "Cognition Network Technology for a Fully Automated 3D Segmentation of Liver Tumors," MICCAI Workshop on 3D Segmentation in the Clinic: a Grand Challenge II,(2008)
9. Shimizu, A. et al., "Ensemble segmentation using AdaBoost with application to liver lesion extraction from a CT volume," MICCAI Workshop on 3D Segmentation in the Clinic: a Grand Challenge II,(2008)
10. Häme, Y. Pollari, M., "Semi-automatic liver tumor segmentation with hidden Markov measure field model and non-parametric distribution estimation," Med Image Anal. 16(1), 140-9 (2011)
11. Freiman, M. Cooper, O. Lischinski, D. Joskowicz, L., "Liver tumors segmentation from CTA images using voxels classification and affinity constraint propagation," Int J Comput Assist Radiol Surg 6(2), 247-55 (2011)
12. Xu, J.W., Suzuki, K., "Computer-Aided Detection of Hepatocellular Carcinoma in Hepatic CC: False Positive Reduction with Feature Selection," IEEE Int Sym Biomed Im., 1097-1100 (2011)
13. Linguraru, M.G. Richbourg, W.J. Watt, J.M. Pamulapati, V. Summers, R.M., "Liver and Tumor Segmentation and Analysis from CT of Diseased Patients via a Generic Affine Invariant Shape Parameterization and Graph Cuts," MICCAI Workshop on Computational and Clinical Applications in Abdominal Imaging LNCS 7029, (2012) (in press)
14. Boykov, Y. Kolmogorov, V., "An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision," IEEE TPAMI 26(9), 1124-1137 (2004)
15. Linguraru, M.G. et al., "Multi-Organ Segmentation from Multi-Phase Abdominal CT via 4D Graphs using Enhancement, Shape and Location Optimization," MICCAI 2010 LNCS 6363, 89-96 (2010)
16. Caselles, V. Kimmel, R. Sapiro, G., "Geodesic Active Contours," International journal on Computer Vision 22(1), 61-97 (1997)
17. Peng, H.C., Long, F.H., Ding, C., "Feature selection based on mutual information: Criteria of max-dependency, max-relevance, and min-redundancy," IEEE Transactions on Pattern Analysis and Machine Intelligence 27, 1226-1238 (2005) (Pubitemid 41245053)
18. Metz, C.E. Herman, B.A. Roe, C.A., "Statistical comparison of two ROC curve estimates obtained from partially-paired datasets," Med Decis Making 18, 110-121 (1998) (Pubitemid 28041647)
19. Haralick, R.M. Shanmugam, K. Dinstein. I., "Textural features for image classification", IEEE Transactions on Systems, Man and Cybernetics 3(6), 610-621 (1973)
20. Burges, C. J. C., "A tutorial on Support Vector Machines for pattern recognition," Data Mining and Knowledge Discovery 2, 121-167 (1998) (Pubitemid 128695475)