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Issue title: Fuzzy Systems for Medical Image Analysis
Guest editors: Weiping Zhang
Article type: Research Article
Affiliations: College of Human Movement Science, Jilin Sport University, Changchun, Jilin, China
Correspondence: [*] Corresponding author. Na Liu, College of Human Movement Science, Jilin Sport University, Changchun, Jilin 130000, China. E-mail: ln000326ln@126.com.
Abstract: Medical image segmentation is an important step of medical image processing, which divides medical image into thousands of regions and extracts the regions of tissues and organs of interest. The accuracy of segmentation is very important for the follow-up processing of medical image and doctors’ judgment of the real situation of diseases. Medical image segmentation is a classic problem in the field of image segmentation. 3D image reconstruction technology is to obtain 3D structure information from 2D images of objects, to provide users with realistic 3D graphics, and to restore the prototype of objects, so that users can observe and analyze from multiple perspectives, which greatly improves the accuracy of measurement and the scientific accuracy of medical diagnosis, and plays a very important role in assisting doctors in clinical diagnosis. Based on the three-dimensional image model of MRI, the load variation of the internal oblique muscle can be applied to the finite element analysis of the near end of the patellar tendon.
Keywords: Three-dimensional reconstruction technology, medical image, MRI
DOI: 10.3233/JIFS-179611
Journal: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 4, pp. 3877-3883, 2020
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