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Proceedings Paper

Interacting with image hierarchies for fast and accurate object segmentation
Author(s): David Volk Beard; David H. Eberly; Bradley M. Hemminger; Stephen M. Pizer; R. E. Faith; Charles Kurak; Mark Livingston
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Paper Abstract

Object definition is an increasingly important area of medical image research. Accurate and fairly rapid object definition is essential for measuring the size and, perhaps more importantly, the change in size of anatomical objects such as kidneys and tumors. Rapid and fairly accurate object definition is essential for 3D real-time visualization including both surgery planning and Radiation oncology treatment planning. One approach to object definition involves the use of 3D image hierarchies, such as Eberly's Ridge Flow. However, the image hierarchy segmentation approach requires user interaction in selecting regions and subtrees. Further, visualizing and comprehending the anatomy and the selected portions of the hierarchy can be problematic. In this paper we will describe the Magic Crayon tool which allows a user to define rapidly and accurately various anatomical objects by interacting with image hierarchies such as those generated with Eberly's Ridge Flow algorithm as well as other 3D image hierarchies. Preliminary results suggest that fairly complex anatomical objects can be segmented in under a minute with sufficient accuracy for 3D surgery planning, 3D radiation oncology treatment planning, and similar applications. Potential modifications to the approach for improved accuracy are summarized.

Paper Details

Date Published: 11 May 1994
PDF: 8 pages
Proc. SPIE 2167, Medical Imaging 1994: Image Processing, (11 May 1994); doi: 10.1117/12.175055
Show Author Affiliations
David Volk Beard, Univ. of North Carolina/Chapel Hill (United States)
David H. Eberly, Univ. of North Carolina/Chapel Hill (United States)
Bradley M. Hemminger, Univ. of North Carolina/Chapel Hill (United States)
Stephen M. Pizer, Univ. of North Carolina/Chapel Hill (United States)
R. E. Faith, Univ. of North Carolina/Chapel Hill (United States)
Charles Kurak, Univ. of North Carolina/Chapel Hill (United States)
Mark Livingston, Univ. of North Carolina/Chapel Hill (United States)


Published in SPIE Proceedings Vol. 2167:
Medical Imaging 1994: Image Processing
Murray H. Loew, Editor(s)

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