Deep monocular 3D reconstruction for assisted navigation in bronchoscopy.

Journal: International journal of computer assisted radiology and surgery
Published Date:

Abstract

PURPOSE: In bronchoschopy, computer vision systems for navigation assistance are an attractive low-cost solution to guide the endoscopist to target peripheral lesions for biopsy and histological analysis. We propose a decoupled deep learning architecture that projects input frames onto the domain of CT renderings, thus allowing offline training from patient-specific CT data.

Authors

  • Marco Visentini-Scarzanella
    Multimedia Laboratory, Toshiba Corporate Research and Development Center, 1, Komukai-Toshiba-cho, Kawasaki, 212-8582, Japan. marco.visentiniscarzanella@gmail.com.
  • Takamasa Sugiura
    Multimedia Laboratory, Toshiba Corporate Research and Development Center, 1, Komukai-Toshiba-cho, Kawasaki, 212-8582, Japan.
  • Toshimitsu Kaneko
    Multimedia Laboratory, Toshiba Corporate Research and Development Center, 1, Komukai-Toshiba-cho, Kawasaki, 212-8582, Japan.
  • Shinichiro Koto
    Multimedia Laboratory, Toshiba Corporate Research and Development Center, 1, Komukai-Toshiba-cho, Kawasaki, 212-8582, Japan.