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Committee Date Time Place Paper Title / Authors Abstract Paper #
MI 2016-07-26
10:30		 Hokkaido Tomakomai Civic Hall Automatic blood vessel-based liver segmentation through the portal phase CT
Ahmed Maklad, Mikio Matsuhiro, Hidenobu Suzuki, Yoshiki Kawata, Noboru Niki, Mitsuo Shimada (Tokushima University), Gen Iinuma (National cancer center hospital) MI2016-41		 Blood vessel (BV) has showed high performance at liver segmentation achieving rank 1 on sliver07. This method was semi-a... [more] MI2016-41
pp.29-34
MI 2016-01-20
13:05		 Okinawa Bunka Tenbusu Kan Abdominal Blood Vessel Analysis using Contrast Enhanced CT Images -Artery, Portal and Delay Phases-
Takatoshi Kakeda, Ryota Imura, Kosuke Ozawa, Hidenobu Suzuki, Yoshiki Kawata, Noboru Niki, Mitsuo Simada (Tokushima Univ), Gen iinuma (National Cancer center Hospital) MI2015-122		 In Japan, the death rate of the colon cancer increases every year. In the death of the colon cancer, women are ranked fi... [more] MI2015-122
pp.237-240
PRMU, MI, IE, SIP 2015-05-15
14:30		 Mie   Automatic blood vessel-based liver segmentation through the portal phase abdominal CT dataset
Ahmed S. Maklad, Mikio Matsuhiro, Hidenobu Suzuki, Yoshiki Kawata, Noboru Niki (Tokushima Univ.), Mitsuo Satake (National Cancer Center Hospital East), Noriyuki Moriyama (Tokyo Midtown Clinic), Toru Utsunomiya, Mitsuo Shimada (Tokushima Univ.) SIP2015-24 IE2015-24 PRMU2015-24 MI2015-24		 Blood vessel has showed high performance at liver segmentation (rank 1 on the official website for liver segmentation). ... [more] SIP2015-24 IE2015-24 PRMU2015-24 MI2015-24
pp.127-132
MI 2014-01-26
13:30		 Okinawa Bunka Tenbusu Kan Abdomial blood vessel extraction algorithm using contrast-enhanced CT image
Yusuke Yamauchi, Yohei Kawano, Ahmed Shawky Mohamed Maklad, Mikio Matsuhiro, Hidenobu Suzuki, Yoshiki Kawata, Noboru Niki, Toru Utsunomiya, Mitsuo Shimada (Univ. of Tokushima) MI2013-71		 It is extremely important to diagnose presence, the level, and the state of the metastasis in lymph nodes in diagnosing ... [more] MI2013-71
pp.83-84
MI 2012-01-20
11:25		 Okinawa   Detection of the liver hemangioma from 3D abdominal CT images by using local intensity features and multi-class classifier
Yoshitaka Sakamoto, Masahiro Oda (Nagoya Univ), Takayuki Kitasaka (AIT), Shigeru Nawano (IHW), Kensaku Mori (Nagoya Univ) MI2011-146		 In this paper, we propose a method for detecting hemangioma from four-phases contrasted 3D abdominal CT images.
In our ... [more]		 MI2011-146
pp.383-388
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