村尾特任准教授、佐藤センター長らによる、RCMBの研究開発に関する発表がSPIE Medical Imaging 2020に採択されました。

RCMBでは、医学系学会を通じて広く医療画像データを収集し、画像解析研究者と協同で課題を解決するためのクラウド基盤を構築し、運用しています。このRCMBの活動を紹介し、従来の医療AI研究開発との違いを議論します。

Kohei Murao, Youichirou Ninomiya, Changhee Han, Kento Aida and Shin’ichi Satoh

Cloud platform for deep learning-based CAD via collaboration between Japanese medical societies and institutes of informatics

SPIE Medical Imaging 2020, 15-20 February 2020, Houston, Texas, United States

発表は口頭で、2020年2月17日の予定です。

Update - 3 March 2020

口頭発表の内容を論文化しました。

Kohei Murao, Youichirou Ninomiya, Changhee Han, Kento Aida and Shin’ichi Satoh

Cloud platform for deep learning-based CAD via collaboration between Japanese medical societies and institutes of informatics

Proceedings SPIE Volume 11318, Medical Imaging 2020: Imaging Informatics for Healthcare, Research, and Applications; 113180T (2020)

Abstract

Deep Learning-based medical imaging research has been actively conducted thanks to its high diagnostic accuracy comparable to that of expert physicians. However, to apply developed Computer Aided Diagnosis (CAD) systems to various data collected from different hospitals, we should prepare sufficient training data in terms of quality/quantity; unfortunately, especially in Japan, we need to overcome each hospital’s different ethical codes to obtain such multi-institutional data. Therefore, we built a cloud platform for (i) collecting multi-modal large- scale medical images from hospitals through medical societies and (ii) conducting various Deep Learning-based CAD research via collaboration between Japanese medical societies and institutes of informatics. Each hospital first provides the data to the corresponding medical society among 6 societies (e.g., Japan Radiological Society and Japanese Society of Pathology) based on their modality among 8 modalities (e.g., Computed Tomography and Whole Slide Imaging (WSI)); then, each society uploads them, possibly with annotation, to our cloud plat- form established in November 2017. We have collected over 80 million medical images by December 2019, and over 60 registered researchers have conducted CAD research on the platform. We presented the achieved results at major international conferences/in medical journals; their ongoing clinical applications include remote WSI diagnosis. We plan to further increase the number of images/modalities and apply our research results to a clinical environment.

DOI: 10.1117/12.2543521