Rule-based ventral cavity multi-organ automatic segmentation in CT scans

CEUR Workshop Proceedings

Volumn 1194, Issue , 2014, Pages 16-21

  Spanier, Assaf B ^a   Joskowicz, Leo ^a  

^a HEBREW UNIVERSITY OF JERUSALEM   (Israel)

Author keywords

[No Author keywords available]

Indexed keywords

D REGION; IMAGE SEGMENTATION; MATHEMATICAL MORPHOLOGY; MEDICAL IMAGING; RESPIRATORY SYSTEM;

AUTOMATIC SEGMENTATIONS; BLOOD CONTENT; MORPHOLOGICAL OPERATIONS; REGION GROWING; REGION OF INTEREST; SEGMENTATION PROCESS; SIMILARITY SCORES; TRAINING DATA SETS;

COMPUTERIZED TOMOGRAPHY;

EID: 84925266451     PISSN: 16130073     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (6)

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3. Schmidt G. et al. Cognition network technology for a fully automated 3D segmentation of the liver. Proc. MICCAI Workshop on 3D Segmentation in the Clinic: A Grand Challenge, pp 125-133, 2007.
4. Mharib AM, Rahman A, Mashohor S, Binti R. Survey of liver CT image segmentation methods. Artificial Intelligence Review, pp 37-42, 2012.
5. Sluimer I, Schilham A, Prokop M, van Ginneken B. Computer analysis of computed tomography scans of the lung: A survey. IEEE Transactions on Medical Imaging Vol 25(4), pp. 385, 2006.
6. Freiman M, Kronman A, Esses SJ, Joskowicz L, Sosna J. Non-parametric iterative model constraint graph min-cut for automatic kidney segmentation. Proc. MICCAI, LNCS 3217, pp. 73-80, 2010.