Zobrazeno 1 - 10
of 187
pro vyhledávání: '"Shoji Kido"'
Autor:
Daiki Nishigaki, Yuki Suzuki, Tadashi Watabe, Daisuke Katayama, Hiroki Kato, Tomohiro Wataya, Kosuke Kita, Junya Sato, Noriyuki Tomiyama, Shoji Kido
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract Fluorine-18-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) is widely used for the detection, diagnosis, and clinical decision-making in oncological diseases. However, in daily medical practice, it is
Externí odkaz:
https://doaj.org/article/1fb7ffeb3b2d4c37b0c6dd47935d2abe
Autor:
Satomi Hatta, Yoshihito Ichiuji, Shingo Mabu, Mauricio Kugler, Hidekata Hontani, Tadakazu Okoshi, Haruki Fuse, Takako Kawada, Shoji Kido, Yoshiaki Imamura, Hironobu Naiki, Kunihiro Inai
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-12 (2023)
Abstract Despite the dedicated research of artificial intelligence (AI) for pathological images, the construction of AI applicable to histopathological tissue subtypes, is limited by insufficient dataset collection owing to disease infrequency. Here,
Externí odkaz:
https://doaj.org/article/c621af8e71764a4898053d29b79e04fe
Autor:
Kosuke Kita, Takahito Fujimori, Yuki Suzuki, Yuya Kanie, Shota Takenaka, Takashi Kaito, Takuyu Taki, Yuichiro Ukon, Masayuki Furuya, Hirokazu Saiwai, Nozomu Nakajima, Tsuyoshi Sugiura, Hiroyuki Ishiguro, Takashi Kamatani, Hiroyuki Tsukazaki, Yusuke Sakai, Haruna Takami, Daisuke Tateiwa, Kunihiko Hashimoto, Tomohiro Wataya, Daiki Nishigaki, Junya Sato, Masaki Hoshiyama, Noriyuki Tomiyama, Seiji Okada, Shoji Kido
Publikováno v:
iScience, Vol 26, Iss 10, Pp 107900- (2023)
Summary: We proposed a bimodal artificial intelligence that integrates patient information with images to diagnose spinal cord tumors. Our model combines TabNet, a state-of-the-art deep learning model for tabular data for patient information, and a c
Externí odkaz:
https://doaj.org/article/da9530a80d524da8b0e3b8ae70fa06cc
Autor:
Takahito Fujimori, Yuki Suzuki, Shota Takenaka, Kosuke Kita, Yuya Kanie, Takashi Kaito, Yuichiro Ukon, Tadashi Watabe, Nozomu Nakajima, Shoji Kido, Seiji Okada
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-11 (2022)
Abstract Cervical sagittal alignment is an essential parameter for the evaluation of spine disorders. Manual measurement is time-consuming and burdensome to measurers. Artificial intelligence (AI) in the form of convolutional neural networks has begu
Externí odkaz:
https://doaj.org/article/e4e2f51a27d14d598bead2f899fed52f
Autor:
Junya Sato, Yuki Suzuki, Tomohiro Wataya, Daiki Nishigaki, Kosuke Kita, Kazuki Yamagata, Noriyuki Tomiyama, Shoji Kido
Publikováno v:
iScience, Vol 26, Iss 7, Pp 107086- (2023)
Summary: In this study, we present a self-supervised learning (SSL)-based model that enables anatomical structure-based unsupervised anomaly detection (UAD). The model employs an anatomy-aware pasting (AnatPaste) augmentation tool that uses a thresho
Externí odkaz:
https://doaj.org/article/8c944889635c444b862a97cbf8d5c80a
Autor:
Atsushi Nakamoto, Masatoshi Hori, Hiromitsu Onishi, Takashi Ota, Hideyuki Fukui, Kazuya Ogawa, Jun Masumoto, Akira Kudo, Yoshiro Kitamura, Shoji Kido, Noriyuki Tomiyama
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-8 (2022)
Abstract Virtual thin-slice (VTS) technique is a generative adversarial network-based algorithm that can generate virtual 1-mm-thick CT images from images of 3–10-mm thickness. We evaluated the performance of VTS technique for assessment of the spi
Externí odkaz:
https://doaj.org/article/c04dfeb9cbc340d98886c12cab9eb36b
Autor:
Yuta Suganuma, Atsushi Teramoto, Kuniaki Saito, Hiroshi Fujita, Yuki Suzuki, Noriyuki Tomiyama, Shoji Kido
Publikováno v:
Applied Sciences, Vol 13, Iss 19, p 10765 (2023)
PET/CT can scan low-dose computed tomography (LDCT) images with morphological information and PET images with functional information. Because the whole body is targeted for imaging, PET/CT examinations are important in cancer diagnosis. However, the
Externí odkaz:
https://doaj.org/article/be9d5ed016fe4e0390b3d2c66bc091bc
Autor:
Shoji Kido, Shunske Kidera, Yasushi Hirano, Shingo Mabu, Tohru Kamiya, Nobuyuki Tanaka, Yuki Suzuki, Masahiro Yanagawa, Noriyuki Tomiyama
Publikováno v:
Frontiers in Artificial Intelligence, Vol 5 (2022)
In computer-aided diagnosis systems for lung cancer, segmentation of lung nodules is important for analyzing image features of lung nodules on computed tomography (CT) images and distinguishing malignant nodules from benign ones. However, it is diffi
Externí odkaz:
https://doaj.org/article/944e8c47754f4653b9b25c53f90f15ed
Publikováno v:
Applied Sciences, Vol 12, Iss 17, p 8542 (2022)
The temporal subtraction technique is a useful tool for computer aided diagnosis (CAD) in visual screening. The technique subtracts the previous image set from the current one for the same subject to emphasize temporal changes and/or new abnormalitie
Externí odkaz:
https://doaj.org/article/2f340cb011b147b1ba65d1c9f5b0626c
Publikováno v:
Diagnostic and Interventional Radiology, Vol 24, Iss 3, Pp 139-145 (2018)
PURPOSE:We aimed to evaluate the usefulness of histograms of lung perfused blood volume (HLPBV) based on the presence of pulmonary thromboembolism (PTE) and the pulmonary embolic burden.METHODS:A total of 168 patients (55 males; mean age, 62.9 years)
Externí odkaz:
https://doaj.org/article/ca34b2ebdd4d495abc34574cf10ba1ad