Database-Guided Segmentation of Anatomical Structures with Complex Appearance

The segmentation of anatomical structures has been traditionally formulated as a perceptual grouping task, and solved through clustering and variational approaches. However, such strategies require the a priori knowledge to be explicitly defined in the optimization criterion, e.g., “high-gradient border”, “smoothness”, or “similar intensity or texture”. This approach is limited by the validity of underlying assumptions and cannot capture complex structure appearance. This paper introduces database-guided segmentation as a new data-driven paradigm that directly exploits expert annotation of interest structures in large medical databases. Segmentation is formulated as a twostep learning problem. The first step is structure detection where we learn how to discriminate between the object of interest and background. The resulting classifier based on a boosted cascade of simple features also provides a global rigid transformation of the structure. The second step is shape inf...

• Type: Conference
• Year: 2005
• Where: CVPR
• Authors: Bogdan Georgescu, Xiang Sean Zhou, Dorin Comaniciu, Alok Gupta
• Keywords: Complex Structure Appearance, Computer Vision, CVPR 2005, Perceptual Grouping Task, Twostep Learning Problem