A
Atsushi Saito
Researcher at Tokyo University of Agriculture and Technology
Publications - 28
Citations - 185
Atsushi Saito is an academic researcher from Tokyo University of Agriculture and Technology. The author has contributed to research in topics: Statistical model & Segmentation. The author has an hindex of 6, co-authored 28 publications receiving 129 citations. Previous affiliations of Atsushi Saito include University of Tokyo.
Papers
More filters
Journal ArticleDOI
Joint optimization of segmentation and shape prior from level-set-based statistical shape model, and its application to the automated segmentation of abdominal organs.
TL;DR: The proposed algorithm solves the well-known open problem, in which a shape prior may not be optimal in terms of an objective functional that needs to be minimized during segmentation, and finds an optimal solution by considering all possible shapes generated from an SSM.
Journal ArticleDOI
Automated measurement of bone scan index from a whole-body bone scintigram
Akinobu Shimizu,Hayato Wakabayashi,Takumi Kanamori,Atsushi Saito,Kazuhiro Nishikawa,Hiromitsu Daisaki,Shigeaki Higashiyama,Joji Kawabe +7 more
TL;DR: A deep learning-based BSI measurement system for a whole-body bone scintigram followed by automated measurement of a bone scan index (BSI) is proposed and proved effectiveness by threefold cross-validation study using 246 whole- body bone scints.
Journal ArticleDOI
Critical Growth Processes for the Midfacial Morphogenesis in the Early Prenatal Period.
Motoki Katsube,Shigehito Yamada,Yutaka Yamaguchi,Tetsuya Takakuwa,Akira Yamamoto,Hirohiko Imai,Atsushi Saito,Akinobu Shimizu,Shigehiko Suzuki +8 more
TL;DR: The development of the midface, especially of the zygoma, before 13 weeks of gestation played an essential role in the midfacial development, and the growth centers had a strong association with midf facial forward growth before birth.
Journal ArticleDOI
Automated liver segmentation from a postmortem CT scan based on a statistical shape model
TL;DR: An algorithm for automated liver segmentation from a PMCT volume is proposed, in which an SSM-guided expectation–maximization (EM) algorithm estimated the location and shape parameters of a liver in a given volume accurately.
Journal ArticleDOI
A Spatiotemporal Statistical Model for Eyeballs of Human Embryos
Masashi Kishimoto,Atsushi Saito,Tetsuya Takakuwa,Shigehito Yamada,Hiroshi Matsuzoe,Hidekata Hontani,Akinobu Shimizu +6 more
TL;DR: An algorithm to construct a spatiotemporal statistical model of the eyeballs of a human embryo and tested its performance using the Kyoto Collection and suggested that information geometry-based interpolation under the assumption of a q-Gaussian distribution is the best modeling method.