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Proceedings Paper

Efficient segmentation algorithm for 3D medical image data using a region-growing-based tracking technique
Author(s): Sunyoung Ko; Jaeyoun Yi; Jung Eun Lim; Jong Beom Ra
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Paper Abstract

In this paper, we propose an efficient semi-automatic algorithm to segment a 3-D object by using a given segmentation result in a single slice. In the proposed algorithm, the segmentation is performed slice-by-slice using z correlation as well as xy correlation based on the assumption that the region to be segmented is homogeneous and has discernable boundaries. We first estimate a parametric motion model of the organ from the previous slice to the current slice, and find an estimated boundary of the organ by projecting the previous result. Then, we extract 3 kinds of seeds in the current slice by using the projected boundaries and the pixel luminance values. All extracted seeds are grown to produce the precise boundary of the organ. And wrong boundary portions due to region growing at low gradient areas are corrected by the post-processing based on a Fourier descriptor. Finally, to catch up on newly appearing areas, a two-way tracking method is applied. The proposed algorithm provides satisfactory results in segmenting kidneys from an X- ray CT body image set of 82 slices.

Paper Details

Date Published: 6 June 2000
PDF: 8 pages
Proc. SPIE 3979, Medical Imaging 2000: Image Processing, (6 June 2000); doi: 10.1117/12.387753
Show Author Affiliations
Sunyoung Ko, Korea Advanced Institute of Science and Technology (South Korea)
Jaeyoun Yi, Korea Advanced Institute of Science and Technology (South Korea)
Jung Eun Lim, Korea Advanced Institute of Science and Technology (South Korea)
Jong Beom Ra, Korea Advanced Institute of Science and Technology (South Korea)


Published in SPIE Proceedings Vol. 3979:
Medical Imaging 2000: Image Processing
Kenneth M. Hanson, Editor(s)

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