Machine learning-based colon deformation estimation method for colonoscope tracking

Masahiro Oda, Takayuki Kitasaka, Kazuhiro Furukawa, Ryoji Miyahara, Yoshiki Hirooka, Hidemi Goto, Nassir Navab, Kensaku Mori

研究成果: Conference contribution

2 被引用数 (Scopus)


This paper presents a colon deformation estimation method, which can be used to estimate colon deformations during colonoscope insertions. Colonoscope tracking or navigation system that navigates a physician to polyp positions during a colonoscope insertion is required to reduce complications such as colon perforation. A previous colonoscope tracking method obtains a colonoscope position in the colon by registering a colonoscope shape and a colon shape. The colonoscope shape is obtained using an electromagnetic sensor, and the colon shape is obtained from a CT volume. However, large tracking errors were observed due to colon deformations occurred during colonoscope insertions. Such deformations make the registration difficult. Because the colon deformation is caused by a colonoscope, there is a strong relationship between the colon deformation and the colonoscope shape. An estimation method of colon deformations occur during colonoscope insertions is necessary to reduce tracking errors. We propose a colon deformation estimation method. This method is used to estimate a deformed colon shape from a colonoscope shape. We use the regression forests algorithm to estimate a deformed colon shape. The regression forests algorithm is trained using pairs of colon and colonoscope shapes, which contains deformations occur during colonoscope insertions. As a preliminary study, we utilized the method to estimate deformations of a colon phantom. In our experiments, the proposed method correctly estimated deformed colon phantom shapes.

ホスト出版物のタイトルMedical Imaging 2018
ホスト出版物のサブタイトルImage-Guided Procedures, Robotic Interventions, and Modeling
編集者Baowei Fei, Robert J. Webster
出版ステータスPublished - 2018
イベントMedical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling - Houston, United States
継続期間: 12-02-201815-02-2018


名前Progress in Biomedical Optics and Imaging - Proceedings of SPIE


ConferenceMedical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling
国/地域United States

All Science Journal Classification (ASJC) codes

  • 電子材料、光学材料、および磁性材料
  • 生体材料
  • 原子分子物理学および光学
  • 放射線学、核医学およびイメージング


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