1 code implementation • 7 Apr 2023 • Shusuke Takahama, Yusuke Kurose, Yusuke Mukuta, Hiroyuki Abe, Akihiko Yoshizawa, Tetsuo Ushiku, Masashi Fukayama, Masanobu Kitagawa, Masaru Kitsuregawa, Tatsuya Harada
We conducted experiments on the pathological image dataset we created for this study and showed that the proposed method significantly improves the classification performance compared to existing methods.
1 code implementation • 7 Mar 2023 • Kazuma Kobayashi, Lin Gu, Ryuichiro Hataya, Takaaki Mizuno, Mototaka Miyake, Hirokazu Watanabe, Masamichi Takahashi, Yasuyuki Takamizawa, Yukihiro Yoshida, Satoshi Nakamura, Nobuji Kouno, Amina Bolatkan, Yusuke Kurose, Tatsuya Harada, Ryuji Hamamoto
As a result, our SBMIR system enabled users to overcome previous challenges, including image retrieval based on fine-grained image characteristics, image retrieval without example images, and image retrieval for isolated samples.
no code implementations • 25 Jan 2022 • Antonio Tejero-de-Pablos, Hiroaki Yamane, Yusuke Kurose, Junichi Iho, Youji Tokunaga, Makoto Horie, Keisuke Nishizawa, Yusaku Hayashi, Yasushi Koyama, Tatsuya Harada
In this paper, we propose a novel methodology for segmenting calcified and non-calcified plaques in CCTA-CPR scans of coronary arteries.
no code implementations • 23 Mar 2021 • Kazuma Kobayashi, Ryuichiro Hataya, Yusuke Kurose, Mototaka Miyake, Masamichi Takahashi, Akiko Nakagawa, Tatsuya Harada, Ryuji Hamamoto
To support comparative diagnostic reading, content-based image retrieval (CBIR), which can selectively utilize normal and abnormal features in medical images as two separable semantic components, will be useful.
no code implementations • 12 Nov 2020 • Kazuma Kobayashi, Ryuichiro Hataya, Yusuke Kurose, Tatsuya Harada, Ryuji Hamamoto
Medical images can be decomposed into normal and abnormal features, which is considered as the compositionality.
1 code implementation • 26 May 2020 • Kazuma Kobayashi, Ryuichiro Hataya, Yusuke Kurose, Amina Bolatkan, Mototaka Miyake, Hirokazu Watanabe, Masamichi Takahashi, Jun Itami, Tatsuya Harada, Ryuji Hamamoto
In addition, we devise a metric to evaluate the anatomical fidelity of the reconstructed images and confirm that the overall detection performance is improved when the image reconstruction network achieves a higher score.
no code implementations • 27 Feb 2020 • Kaikai Huang, Antonio Tejero-de-Pablos, Hiroaki Yamane, Yusuke Kurose, Junichi Iho, Youji Tokunaga, Makoto Horie, Keisuke Nishizawa, Yusaku Hayashi, Yasushi Koyama, Tatsuya Harada
In this paper, we propose a novel boundary detection method for coronary arteries that focuses on the continuity and connectivity of the boundaries.
no code implementations • ICCV 2019 • Shusuke Takahama, Yusuke Kurose, Yusuke Mukuta, Hiroyuki Abe, Masashi Fukayama, Akihiko Yoshizawa, Masanobu Kitagawa, Tatsuya Harada
If we consider the relationship of neighboring patches and global features, we can improve the classification performance.