第21回計算解剖学セミナー

開催概要

プログラム

  • 講演1
    • 講師
      A-Wittek-Photograph.jpg
      • Professor Adam WITTEK, PhD
        School of Mechanical and Chemical Engineering
        The University of Western Australia
    • タイトル
      • Computational Biomechanics of the Brain for Image-Guided Neurosurgery
    • 概要
      • Long computation times of non-linear (i.e. accounting for geometric and material nonlinearity) biomechanical models have been regarded as one of the key factors preventing application of such models in predicting organ deformation for image-guided surgery.

        This talk presents real-time (i.e. within the real-time constraints of image-guided neurosurgery) patient-specific computations of the deformation field within the brain for 33 cases of brain shift induced by craniotomy (i.e. surgical opening of the skull). We used patient-specific finite element meshes (computational grids) consisting of hexahedral and non-locking tetrahedral elements, together with realistic material properties for the brain tissue and appropriate contact conditions at the boundaries. The loading was defined by prescribing deformations on the brain surface under the craniotomy. Application of the computed deformation fields to register (i.e. align) the pre-operative images with the intraoperative ones indicated that the models very accurately predict the intra-operative deformation within the brain. For each surgery case, computing the brain deformation field took less than 40 s using a standard personal computer and less than 4 s using a graphics processing unit (GPU). Comparison with both rigid registration and non-rigid BSpline registration favours the biomechanics-based approach.

        Biomechanics-based approach does not require an intraoperative image for a target. Just a measurement of the current, intraoperative position of the exposed (due to craniotomy) brain surface is sufficient. Thus, computational biomechanics in the operating theatre has a potential to significantly change the way surgical planning is conducted and bring substantial benefits to patients.
  • 略歴
    • Professor Adam Wittek is a Deputy Director of Intelligent Systems for Medicine Laboratory and Chair of Mechanical Engineering Programme at the University of Western Australia (in Perth).

      He received a Masters of Engineering degree in Applied Mechanics from Warsaw University of Technology in Poland, and a PhD in Engineering (Injury Prevention) from Chalmers University of Technology in Sweden.

      Prof. Wittek’s career includes over 9 years of research in computational biomechanics of the brain at the Intelligent Systems for Medicine Laboratory (The University of Western Australia) and 5 years of research in injury prevention (including head injury) in automotive impacts at the Japan Automobile Research Institute and Toyota Central Research and Development Laboratories in Japan.

      Prof. Wittek is a recipient of Engineers Australia Sir George Julius Medal (awarded by the Mechanical Engineering College of Engineers Australia for the best publication in the field of Mechanical Engineering) and Society of Automotive Engineers SAE Ralph H. Isbrandt Automotive Safety Engineering Award (for outstanding contribution to the literature which advances the field of automotive safety engineering).


  • 講演2
    • 講師
      Guoyan_photo.jpg
      • Dr. Guoyan Zheng, PhD PD
        Institute for Surgical Technology and Biomechanics
        University of Bern
        Switzerland
    • タイトル
      • 3D Personalized Reconstruction of Shape and Intensity from 2D X-ray Images: Statistical Model-based Solutions
    • 概要
      • The applications of two-dimensional (2D) X-ray imaging in orthopedics are pervasive, both pre-operatively and intra-operatively. However, due to the projective characteristics of 2D X-ray imaging, the accuracy of an X-ray image based application is restricted. One way to address this limitation is to learn a statistical model and to adapt the learned model to the patient’s individual anatomy based on a limited number of calibrated X-ray images. The reconstructed model can then provide detailed 3D information for the considered anatomical structure. In this talk, I will present various solutions that have been developed in my team for reconstructing 3D personalized shape and intensity from 2D X-ray images. I will start with a solution that can reconstruct the shape of an anatomical structure with none or mild degree of pathology even when a statistical model learned from a normal population is used. Challenges and adaptations of applying this method to various pre-operative and intra-operative scenarios will be discussed. Our more recent work focuses on reconstructing not only the shape but also the internal intensity distribution. Applications of our solutions are pre-operative planning, intra-operative surgical interventions, and post-operative treatment evaluation.
  • 略歴
    • PD Dr. Guoyan Zheng received his Ph.D. degree in Biomedical Engineering from University of Bern in 2002. Since 2005 he has been the head of the Information Processing in Medical Interventions (IPMI) group at the Institute of Surgical Technology and Biomechanics of the same University. In 2010, he did his habilitation on medical image computing and received the venia decendi from the University of Bern. He has won several national and international awards including the best basic science paper published in the Journal of Laryngology and Otology in year 2011, the 2009 Ypsomed Innovation Prize, and the best technical paper award in the 2006 annual conference of the International Society of Computer Assisted Orthopaedic Surgery. He is a member of the IEEE and the MICCAI societies. He is on the program committee of the 16th International Conference on Medical Image Computing and Computer Assisted Interventions (MICCAI 2013) and on the program committee of International Conference on Image Analysis and Recognition (ICIAR) since 2006. He is also the co-chair of the 6th International Workshop on Medical Imaging and Augmented Reality (MIAR 2013).

問い合わせ先

  • 佐藤 嘉伸 (大阪大学 大学院医学系研究科 放射線医学教室 准教授)
    • 電話 06(6879)3562
    • 電子メール yoshi @ image.med.osaka-u.ac.jp

当日の様子

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Last-modified: 2013-09-27 (Fri) 14:43:11 (1366d)