A02-1 Pre/intra-operative Diagnostic and Navigational Assistance Based on Multidisciplinary Computational Anatomy

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  • Primary Investigator
    Kensaku Mori (Nagoya University, Professor)
  • Co-Investigator
    Masahiro Oda (Nagoya University, Assistant Professor)
    Yoshito Mekada (Chukyo University,Professor)
    Takayuki Kitasaka (Aichi Institute of Technology, Associate Professor)
    Kazunari Misawa (Aichi Cancer Center Hospital, Researcher)
    Yoshihiko Nakamura (National Institute of Technology Tomakomai College, Assistant Professor)
  •  Corporative Researcher
    Michitaka Fujiwara (Nagoya University, Associate Professor)
    Kazuhiro Furukawa (Nagoya University, Assistant Professor)
    Shu ichihara (Nagoya Medical center, Chief)


The goal of this project is to develop methods to seamlessly understand multimodal medical images, describing spatial, temporal and functional distributions of anatomy and physiology across the population, including pathology, based on multi-disciplinary computational anatomical models. This project aims to develop intelligent diagnosis and surgery assistance systems, which display information required during the diagnostic process and surgical interventions. The human body has to be considered at multiple scales and medical images reflect this. For example, when we think about the spatial scale, there is the human-body scale, the organ scale, the scale of an organ’s internal-structure, and the cellular scale. In the time scale, we may consider cardiac motion, respiratory motion or the much longer time scale of tumor growth along the time axis. It is also possible to define the meta-anatomy scale, which is a logical scale that can be expressed by a set of anatomical names. In endoscopic diagnosis or surgery, medical doctors are utilizing medical images of different modalities and resolutions including endoscopic ultrasound images with a resolution of a few hundred micro-meters or microscopic images with resolution down to several micro-meters. If we consider a possible system to aid data fusion for diagnostics and surgical guidance then to fully understand the image data we are required to develop an integrated scheme tat can handle such axes in a seamless way. From this viewpoint we have decided to perform the research project that develops an intelligent diagnostic and surgical assistance system, which enables us to seamlessly navigate the multi-dimensional space including descriptions of pathology, and variations across the population, i.e. the meta-anatomy. The system’s ultimate goal is to provide medical doctors with the information they really need to make decisions on their patients’ care.

Project Design

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