Zobrazeno 1 - 10
of 74
pro vyhledávání: '"Koichiro Yasaka"'
Autor:
Jun Kamohara, MD, Takatoshi Kubo, MD, PhD, Koichiro Yasaka, MD, PhD, Hiroshi Kobayashi, MD, PhD, Osamu Abe, MD, PhD
Publikováno v:
Radiology Case Reports, Vol 19, Iss 10, Pp 4650-4653 (2024)
Trabectedin is an antineoplastic drug used to treat soft tissue sarcomas. Trabectedin is mainly infused from the central venous port (CVP) because trabectedin leakage causes serious skin and soft tissue complications. Characteristic sterile inflammat
Externí odkaz:
https://doaj.org/article/fe29faab054846a8af66459a9ba845ac
Autor:
Tsuyoshi Hamada, Koichiro Yasaka, Yousuke Nakai, Rintaro Fukuda, Ryunosuke Hakuta, Kazunaga Ishigaki, Sachiko Kanai, Kensaku Noguchi, Hiroki Oyama, Tomotaka Saito, Tatsuya Sato, Tatsunori Suzuki, Naminatsu Takahara, Hiroyuki Isayama, Osamu Abe, Mitsuhiro Fujishiro
Publikováno v:
Endoscopy International Open, Vol 12, Iss 06, Pp E772-E780 (2024)
Externí odkaz:
https://doaj.org/article/54f7e52ddac64e2aab0cac5849c2873d
Autor:
Hiroyuki Akai, Koichiro Yasaka, Haruto Sugawara, Taku Tajima, Masaru Kamitani, Toshihiro Furuta, Masaaki Akahane, Naoki Yoshioka, Kuni Ohtomo, Osamu Abe, Shigeru Kiryu
Publikováno v:
BMC Medical Imaging, Vol 23, Iss 1, Pp 1-6 (2023)
Abstract Purpose To evaluate whether deep learning reconstruction (DLR) accelerates the acquisition of 1.5-T magnetic resonance imaging (MRI) knee data without image deterioration. Materials and methods Twenty-one healthy volunteers underwent MRI of
Externí odkaz:
https://doaj.org/article/23d47d92440441e8aaf6ce53afb74b87
Autor:
Nobukiyo Yoshida, Hajime Kageyama, Hiroyuki Akai, Koichiro Yasaka, Haruto Sugawara, Yukinori Okada, Akira Kunimatsu
Publikováno v:
PLoS ONE, Vol 17, Iss 9, p e0274576 (2022)
Voxel-based specific region analysis systems for Alzheimer's disease (VSRAD) are clinically used to measure the atrophied hippocampus captured by magnetic resonance imaging (MRI). However, motion artifacts during acquisition of images may distort the
Externí odkaz:
https://doaj.org/article/e876da20867642f5bc59c67a2048f18c
Autor:
Eriko Maeda, Nobuo Tomizawa, Shigeaki Kanno, Koichiro Yasaka, Takatoshi Kubo, Kenji Ino, Rumiko Torigoe, Kuni Ohtomo
Publikováno v:
Data in Brief, Vol 10, Iss C, Pp 210-214 (2017)
The data presented in this articles are related to the research article entitled “The feasibility of Forward-projected model-based Iterative Reconstruction SoluTion (FIRST) for coronary 320-row computed tomography angiography: a pilot study” (E.
Externí odkaz:
https://doaj.org/article/c58ea9560ca64df59862cc41575baf6f
Autor:
Koichiro Yasaka, Osamu Abe
Publikováno v:
PLoS Medicine, Vol 15, Iss 11, p e1002707 (2018)
Externí odkaz:
https://doaj.org/article/658ef84c48f64ed6932c325c3251faa5
Publikováno v:
Abdominal Radiology. 48:1280-1289
Purpose This study aimed to compare the hepatocellular carcinoma (HCC) detection performance, interobserver agreement for Liver Imaging Reporting and Data System (LI-RADS) categories, and image quality between deep learning reconstruction (DLR) and c
Publikováno v:
Journal of Computer Assisted Tomography; Nov/Dec2023, Vol. 47 Issue 6, p996-1001, 6p
Autor:
Shigeru Kiryu, Hiroyuki Akai, Koichiro Yasaka, Taku Tajima, Akira Kunimatsu, Naoki Yoshioka, Masaaki Akahane, Osamu Abe, Kuni Ohtomo
Publikováno v:
RadioGraphics. 43
Autor:
Koichiro Yasaka, Sosuke Hatano, Masumi Mizuki, Naomasa Okimoto, Takatoshi Kubo, Eisuke Shibata, Takeyuki Watadani, Osamu Abe
Publikováno v:
The British Journal of Radiology.
Objective: To investigate the effectiveness of a deep learning model in helping radiologists or radiology residents detect esophageal cancer on contrast-enhanced CT images. Methods: This retrospective study included 250 and 25 patients with and witho