18 January 2005 Assessment of body fat based on potential function clustering segmentation of computed tomography images
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Abstract
In this paper, a new method of body fat and its distribution testing is proposed based on CT image processing. As it is more sensitive to slight differences in attenuation than standard radiography, CT depicts the soft tissues with better clarity. And body fat has a distinct grayness range compared with its neighboring tissues in a CT image. An effective multi-thresholds image segmentation method based on potential function clustering is used to deal with multiple peaks in the grayness histogram of a CT image. The CT images of abdomens of 14 volunteers with different fatness are processed with the proposed method. Not only can the result of total fat area be got, but also the differentiation of subcutaneous fat from intra-abdominal fat has been identified. The results show the adaptability and stability of the proposed method, which will be a useful tool for diagnosing obesity.
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Lixin Zhang, Lixin Zhang, Min Lin, Min Lin, Baikun Wan, Baikun Wan, Yu Zhou, Yu Zhou, Yizhong Wang, Yizhong Wang, } "Assessment of body fat based on potential function clustering segmentation of computed tomography images", Proc. SPIE 5630, Optics in Health Care and Biomedical Optics: Diagnostics and Treatment II, (18 January 2005); doi: 10.1117/12.575945; https://doi.org/10.1117/12.575945
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