Automatic ovarian follicle quantification from 3D ultrasound data using global/local context with database guided segmentation

Proceedings of the IEEE International Conference on Computer Vision

Volumn , Issue , 2009, Pages 795-802

  Chen, Terrence ^a   Zhang, Wei ^a   Good, Sara ^a   Zhou, Kevin S ^a   Comaniciu, Dorin ^a  

^a SIEMENS CORPORATE RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

3-D ULTRASOUND; CLINICAL WORKFLOW; DATABASE-GUIDED SEGMENTATION; GLOBAL/LOCAL; HIGH DIMENSIONAL SPACES; HIGH ROBUSTNESS; MARGINAL SPACE LEARNING; MULTIPLE OBJECTS; OVARIAN FOLLICLES; PROBABILISTIC FRAMEWORK;

COMPUTER VISION; LOCATION; MANAGEMENT; THREE DIMENSIONAL; ULTRASONICS;

ULTRASONIC APPLICATIONS;

EID: 77953203983     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCV.2009.5459243     Document Type: Conference Paper

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