Database-Guided Simultaneous Multi-slice 3D Segmentation for Volumetric Data

Abstract. Automatic delineation of anatomical structures in 3-D volumetric data is a challenging task due to the complexity of the object appearance as well as the quantity of information to be processed. This makes it increasingly difficult to encode prior knowledge about the object segmentation in a traditional formulation as a perceptual grouping task. We introduce a fast shape segmentation method for 3-D volumetric data by extending the 2-D database-guided segmentation paradigm which directly exploits expert annotations of the interest object in large medical databases. Rather than dealing with 3-D data directly, we take advantage of the observation that the information about position and appearance of a 3-D shape can be characterized by a set of 2-D slices. Cutting these multiple slices simultaneously from the 3-D shape allows us to represent and process 3-D data as efficiently as 2-D images while keeping most of the information about the 3-D shape. To cut slices consistently for ...

• Type: Conference
• Year: 2006
• Where: ECCV
• Authors: Wei Hong, Bogdan Georgescu, Xiang Sean Zhou, Sriram Krishnan, Yi Ma, Dorin Comaniciu
• Keywords: 3-D Data, 3-D Non-rigid Shape, 3-D Shape, 3-D Volumetric Data, Computer Vision, ECCV 2006, Shape Segmentation Method