A Deep Learning Aided Drowning Diagnosis for Forensic Investigations using Post-Mortem Lung CT Images

Noriyasu Homma, Xiaoyong Zhang, Amber Qureshi, Takuya Konno, Yusuke Kawasumi, Akihito Usui, Masato Funayama, Ivo Bukovsky, Kei Ichiji, Norihiro Sugita, Makoto Yoshizawa

研究成果: Conference contribution

抄録

Feasibility of computer-aided diagnosis (CAD) systems has been demonstrated in the field of medical image diagnosis. Especially, deep learning based CAD systems showed high performance thanks to its capability of image recognition. However, there is no CAD system developed for post-mortem imaging diagnosis and thus it is still unclear if the CAD system is effective for this purpose. Particulally, the drowning diagnosis is one of the most difficult tasks in the field of forensic medicine because findings of the post-mortem image diagnosis are not specific. To address this issue, we develop a CAD system consisting of a deep convolution neural network (DCNN) to classify post-mortem lung computed tomography (CT) images into two categories of drowning and non-drowning cases. The DCNN was trained by means of transfer learning and performance evaluation was conducted by 10-fold cross validation using 140 drowning cases and 140 non-drowning cases of the CT images. The area under the receiver operating characteristic curve (AUC-ROC) for the DCNN was achieved 0.88 in average. This high performance clearly demonstrated that the proposed DCNN based CAD system has a potential for post-mortem image diagnosis of drowning.

本文言語English
ホスト出版物のタイトル42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society
ホスト出版物のサブタイトルEnabling Innovative Technologies for Global Healthcare, EMBC 2020
出版社Institute of Electrical and Electronics Engineers Inc.
ページ1262-1265
ページ数4
ISBN(電子版)9781728119908
DOI
出版ステータスPublished - 2020 7
イベント42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020 - Montreal, Canada
継続期間: 2020 7 202020 7 24

出版物シリーズ

名前Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
2020-July
ISSN(印刷版)1557-170X

Conference

Conference42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020
CountryCanada
CityMontreal
Period20/7/2020/7/24

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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