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

Kohei Murao; Youichirou Ninomiya; Changhee Han; Kento Aida; Shin'ichi Satoh

doi:10.1117/12.2543521

2 March 2020 Cloud platform for deep learning-based CAD via collaboration between Japanese medical societies and institutes of informatics

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

Author Affiliations +

Proceedings Volume 11318, Medical Imaging 2020: Imaging Informatics for Healthcare, Research, and Applications; 113180T (2020) https://doi.org/10.1117/12.2543521
Event: SPIE Medical Imaging, 2020, Houston, Texas, United States

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.

Conference Presentation

Citation Download Citation

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", Proc. SPIE 11318, Medical Imaging 2020: Imaging Informatics for Healthcare, Research, and Applications, 113180T (2 March 2020); https://doi.org/10.1117/12.2543521

ACCESS THE FULL ARTICLE

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
6 PAGES + PRESENTATION

DOWNLOAD PAPER SAVE TO MY LIBRARY

WATCH
PRESENTATION

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Clouds

Image segmentation

Medical imaging

Computer aided diagnosis and therapy

Information science

Medical research

Pathology

Show All Keywords

Keywords/Phrases

Search In:

Publication Years