6 June 2000 Efficient segmentation algorithm for 3D medical image data using a region-growing-based tracking technique
Author Affiliations +
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.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sunyoung Ko, Jaeyoun Yi, Jung Eun Lim, and Jong Beom Ra "Efficient segmentation algorithm for 3D medical image data using a region-growing-based tracking technique", Proc. SPIE 3979, Medical Imaging 2000: Image Processing, (6 June 2000); doi: 10.1117/12.387753; https://doi.org/10.1117/12.387753
PROCEEDINGS
8 PAGES


SHARE
Advertisement
Advertisement
RELATED CONTENT


Back to Top