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Proceedings Paper

Automated segmentations of skin, soft-tissue, and skeleton, from torso CT images
Author(s): Xiangrong Zhou; Takeshi Hara; Hiroshi Fujita; Ryujiro Yokoyama; Takuji Kiryu; Hiroaki Hoshi
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Paper Abstract

We have been developing a computer-aided diagnosis (CAD) scheme for automatically recognizing human tissue and organ regions from high-resolution torso CT images. We show some initial results for extracting skin, soft-tissue and skeleton regions. 139 patient cases of torso CT images (male 92, female 47; age: 12-88) were used in this study. Each case was imaged with a common protocol (120kV/320mA) and covered the whole torso with isotopic spatial resolution of about 0.63 mm and density resolution of 12 bits. A gray-level thresholding based procedure was applied to separate the human body from background. The density and distance features to body surface were used to determine the skin, and separate soft-tissue from the others. A 3-D region growing based method was used to extract the skeleton. We applied this system to the 139 cases and found that the skin, soft-tissue and skeleton regions were recognized correctly for 93% of the patient cases. The accuracy of segmentation results was acceptable by evaluating the results slice by slice. This scheme will be included in CAD systems for detecting and diagnosing the abnormal lesions in multi-slice torso CT images.

Paper Details

Date Published: 12 May 2004
PDF: 6 pages
Proc. SPIE 5370, Medical Imaging 2004: Image Processing, (12 May 2004); doi: 10.1117/12.534843
Show Author Affiliations
Xiangrong Zhou, Gifu Univ. Graduate School of Medicine (Japan)
Takeshi Hara, Gifu Univ. Graduate School of Medicine (Japan)
Hiroshi Fujita, Gifu Univ. Graduate School of Medicine (Japan)
Ryujiro Yokoyama, Gifu Univ. School of Medicine and Univ. Hospital (Japan)
Takuji Kiryu, Gifu Univ. School of Medicine and Univ. Hospital (Japan)
Hiroaki Hoshi, Gifu Univ. School of Medicine and Univ. Hospital (Japan)


Published in SPIE Proceedings Vol. 5370:
Medical Imaging 2004: Image Processing
J. Michael Fitzpatrick; Milan Sonka, Editor(s)

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