An efficient method for deformable segmentation of 3D us prostate images

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3150, Issue , 2004, Pages 103-112

  Zhan, Yiqiang ^a,b,c   Shen, Dinggang ^a,b  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

^b JOHNS HOPKINS UNIVERSITY   (United States)

^c Johns Hopkins University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AUGMENTED REALITY; CLASSIFICATION (OF INFORMATION); DEFORMATION; FILTER BANKS; GABOR FILTERS; IMAGE TEXTURE; MEDICAL IMAGING; SUPPORT VECTOR MACHINES; TISSUE; UROLOGY;

BOUNDARY IDENTIFICATION; BOUNDARY INFORMATION; DEFORMABLE MODELING; DEFORMABLE SEGMENTATION; FUTURE APPLICATIONS; SEGMENTATION ACCURACY; TISSUE CLASSIFICATION; TRAINING METHODS;

IMAGE SEGMENTATION;

EID: 35048812740     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-28626-4_13     Document Type: Article

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