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Editorial: 3D Segmentation in the Clinic: A Grand Challenge II - Liver Tumor Segmentation
X. Deng and G. Du
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An Entropy Based Multi-Thresholding Method for Semi-Automatic Segmentation of Liver Tumors
A. Choudhary, N. Moretto, F. Pizzorni, and G. Zamboni
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Interactive Liver Tumor Segmentation Using Graph-cuts and Watershed
J. Stawiaski, E. Decenciere and F. Bidault
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Cognition Network Technology for a Fully Automated 3D Segmentation of Liver Tumors
G. Schmidt, G. Binnig, M. Kietzmann and J. Kim
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Efficient Automated Detection and Segmentation of Medium and Large Liver Tumors: CAD Approach
T. Kubota
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An iterative Bayesian approach for liver analysis: tumors validation study
Y. Taieb, O. Eliassaf, M. Freiman, L. Joskowicz and J. Sosna
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Ensemble segmentation using AdaBoost with application to liver lesion extraction from a CT volume
A. Shimizu, T. Narihira, D. Furukawa, H. Kobatake, S. Nawano and K. Shinozaki
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Segmentation of Liver Metastases Using a Level Set Method with Spiral-Scanning Technique and Supervised Fuzzy Pixel Classification
D. Smeets, B. Stijnen, D. Loeckx, B. Dobbelaer and P. Suetens
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Segmentation of Liver Metastases in CT Scans by Adaptive Thresholding and Morphological Processing
J. Moltz, L. Bornemann, V. Dicken and H. Peitgen
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A semi-automated method for liver tumor segmentation based on 2D region growing with knowledge-based constraints
D. Wong, J. Liu, Y. Fengshou, Q. Tian, W. Xiong, J. Zhou, Y. Qi, T. Han, S. Venkatesh and S. Wang
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Semi-automatic Segmentation of 3D Liver Tumors from CT Scans Using Voxel Classification and Propagational Learning
J. Zhou, W. Xiong, Q. Tian, Y. Qi, J. Liu, W. Leow, T. Han, S. Venkatesh and S. Wang
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Semi-automatic Segmentation of Liver Tumors from CT Scans Using Bayesian Rule-based 3D Region Growing
Y. Qi, W. Xiong, W. Leow, Q. Tian, J. Zhou, J. Liu, T. Han, S. Venkatesh and S. Wang
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Contrast Enhancement for Liver Tumor Identification
H. Nugroho, D. Ihtatho and H. Nugroho
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Liver Tumor Segmentation Using Implicit Surface Evolution
Y. Häme
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Liver Tumor segmentation in CT images using probabilistic methods
I. Ben-Dan and E. Shenhav
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