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

  • Wei Hong
  • Bogdan Georgescu
  • Xiang Sean Zhou
  • Sriram Krishnan
  • Yi Ma
  • Dorin Comaniciu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3954)

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 all shapes, an iterative 3-D non-rigid shape alignment method is also proposed for building local coordinates for each shape. Features from all the slices are jointly used to learn to discriminate between the object appearance and background and to learn the association between appearance and shape. The resulting procedure is able to perform shape segmentation in only a few seconds. Extensive experiments on cardiac ultrasound images demonstrate the algorithm’s accuracy and robustness in the presence of large amounts of noise.

Keywords

Segmentation Method Volumetric Data Active Appearance Model Object Appearance Multiple Slice 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Wei Hong
    • 2
  • Bogdan Georgescu
    • 1
  • Xiang Sean Zhou
    • 3
  • Sriram Krishnan
    • 3
  • Yi Ma
    • 2
  • Dorin Comaniciu
    • 1
  1. 1.Integrated Data Systems DepartmentSiemens Corporate ResearchPrincetonUSA
  2. 2.Department of Electrical and Computer EngineeringUniversity of Illinois at Urbana-ChampaignUrbanaUSA
  3. 3.Siemens Medical SolutionsMalvernUSA

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