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Committee Date Time Place Paper Title / Authors Abstract Paper #
MICT, MI 2020-11-04
Online Online Finding effective image features for estimating postmortem time for Ai-CT using Deep Learning
Jun Matsumoto, Yasushi Hirano (Yamaguchi-u), Tadahiro Inai (Fukui Univ), Sakon Noriki (Fukui Pref. Univ) MICT2020-18 MI2020-44
 [more] MICT2020-18 MI2020-44
MI 2018-09-28
Tokyo Tokyo Women's Medical University Estimation of postmortem time for CT images by using texture analysis
Yasushi Hirano, Shoji Kido (Yamaguchi Univ.), Kazuyuki Kinoshita, Kunihiro Inai, Sakon Noriki (Univ. of Fukui) MI2018-35
The dissection rate for dead human bodies with suspicious death is about 11% in Japan. This rate is markedly lower than ... [more] MI2018-35
MI 2018-07-24
Iwate aiina (Morioka, Iwate) Estimation of postmortem time for Ai-CT images by using Deep Learning
Shota Chai, Yasushi Hirano, Shoji Kido (Yamaguchi Univ.), Kazuyuki Kinoshita, Kunihiro Inai, Sakon Noriki (Univ. of Fukui) MI2018-28
Although estimation of postmortem time is important for criminal investigation or sudden in-hospital death in the middle... [more] MI2018-28
MI 2014-01-26
Okinawa Bunka Tenbusu Kan Segmentation of organ regions by deformation of ante-mortem CT images to post-mortem CT images
Ryota Akiyama, Kyohei Mikami, Yasushi Hirano, Shoji Kido (Yamaguchi Univ.), Kunihiro Inai, Sakon Noriki (Univ. of Fukui) MI2013-67
Autopsy imaging (Ai) plays a key role to reduce the imposition of doctors
and to improve the reliability of cause of de... [more]
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