Real-time tumor tracking using fluoroscopic imaging with deep neural network analysis.

Journal: Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)

Published Date: Mar 1, 2019

Abstract

PURPOSE: To improve respiratory gating accuracy and treatment throughput, we developed a fluoroscopic markerless tumor tracking algorithm based on a deep neural network (DNN).

Authors

Ryusuke Hirai

Corporate Research and Development Center, Toshiba Corporation, Kanagawa 212-8582, Japan. Electronic address: ryusuke.hirai@toshiba.co.jp.
Yukinobu Sakata

Corporate Research and Development Center, Toshiba Corporation, Kanagawa 212-8582, Japan.
Akiyuki Tanizawa

Corporate Research and Development Center, Toshiba Corporation, Kanagawa 212-8582, Japan.
Shinichiro Mori

Research Center for Charged Particle Therapy, National Institute of Radiological Sciences, Inage-ku, Chiba 263-8555, Japan.. Electronic address: mori.shinichiro@qst.go.jp.

Keywords

Fluoroscopy Four-Dimensional Computed Tomography Humans Image Processing, Computer-Assisted Liver Neoplasms Lung Neoplasms Neural Networks, Computer Retrospective Studies Time Factors

External Resources

View on PubMed Access via DOI PubMed (30928062)

Real-time tumor tracking using fluoroscopic imaging with deep neural network analysis.

Abstract

Authors

Keywords

External Resources

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