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Healthc Inform Res > Volume 13(2); 2007 > Article
Journal of Korean Society of Medical Informatics 2007;13(2):171-176.
DOI: https://doi.org/10.4258/jksmi.2007.13.2.171    Published online June 30, 2007.
Semiautomatic Segmentation of Lung Region from Three Dimensional Color Images of Visible Human
Hideaki Kido, Kunihiko Kaneko, Akifumi Makinouchi
1Graduate School of Systems Life Sciences Kyushu University, Fukuoka, Japan.
2Faculty of Information Science and Electrical Engineering, Kyushu University, Fukuoka, Japan.
3Graduate School of Information Science and Electrical Engineering, Fukuoka, Japan.
Abstract

OBJECTIVE: Watershed algorithm is image segmentation algorithm divides the image into numerous small regions. This paper proposes a new approach to extract the lung region from the three dimensional color image of Frozen Human Body (Visible Human Male) based on watershed algorithm.

METHODS: After applying this algorithm to input image and getting the small regions, we merge these small regions into one region with three measures based on color, edge marker, and SURFACE respectively.

RESULTS: We can say that the smaller number of FALSE-POSITIVE and TRUE NEGATIVE voxels and the larger number of FALSE POSITIVE voxels are better result. Graph shows change in the number of voxel in above groups of the left lung detection when tau color change with tau em is 0.7. We think that the result at the range of tau color from 110 to 180 are better than the other results in Graph.

CONCLUSION: Comparing with our previous work, we newly use Canny edge filter for edge marker and define SURFACE-based dissimilarity to relax the problem of its step. The users must select a point within the lung region and some thresholds (taucolor, tauem, tauhigh, taulow, delta) to detect the target region.

Key Words: Semiautomatic Segmentation, Three Dimensional Image, Lung Region
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