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Automatic segmentation algorithms and personalized geometric modelling for a human knee

  • Victoria Yu. Salamatova , Alexandra S. Yurova , Yuri V. Vassilevski EMAIL logo and Lin Wang
Published/Copyright: December 26, 2019

Abstract

Human knee is one of the most complex joints. Different reasons may lead to knee instability. A personalized mathematical model of the knee may improve both diagnostic procedure and knee surgery outcomes. Such models require accurate geometric representation of bones and attachment sites of ligaments and tendons. This paper addresses automatic segmentation of knee bones and detection of origins and insertions for tendons and ligaments. The approach is based on anatomical features of bones and landmarks of tendons/ligaments attachments on the CT images. It provides a tool for the design of patient-specific geometrical knee models.

MSC 2010: 92C10; 68U10
  1. Funding: The work was supported in part by the world-class research center ‘Moscow Center for Fundamental and Applied Mathematics’, RFBR grant 17-01-00886, the 2019 International Collaboration Special Plan, Chinese Academy of Sciences, grants of Guangdong Province, China, 2018A030313065 and Shenzhen, China, JCYJ20170818163445670.

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Received: 2019-11-06
Accepted: 2019-11-08
Published Online: 2019-12-26
Published in Print: 2019-12-18

© 2019 Walter de Gruyter GmbH, Berlin/Boston

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