Zobrazeno 1 - 10
of 149
pro vyhledávání: '"Nishimura, Kazuya"'
Autor:
Okuo, Takumi, Nishimura, Kazuya, Ito, Hiroaki, Terada, Kazuhiro, Yoshizawa, Akihiko, Bise, Ryoma
The PD-L1 rate, the number of PD-L1 positive tumor cells over the total number of all tumor cells, is an important metric for immunotherapy. This metric is recorded as diagnostic information with pathological images. In this paper, we propose a propo
Externí odkaz:
http://arxiv.org/abs/2405.04815
Detection of mitosis events plays an important role in biomedical research. Deep-learning-based mitosis detection methods have achieved outstanding performance with a certain amount of labeled data. However, these methods require annotations for each
Externí odkaz:
http://arxiv.org/abs/2307.04113
Publikováno v:
Medical Image Analysis 2022
Cell detection is an important task in biomedical research. Recently, deep learning methods have made it possible to improve the performance of cell detection. However, a detection network trained with training data under a specific condition (source
Externí odkaz:
http://arxiv.org/abs/2303.05269
Autor:
Ito, Hiroaki, Yoshizawa, Akihiko, Terada, Kazuhiro, Nakakura, Akiyoshi, Rokutan-Kurata, Mariyo, Sugimoto, Tatsuhiko, Nishimura, Kazuya, Nakajima, Naoki, Sumiyoshi, Shinji, Hamaji, Masatsugu, Menju, Toshi, Date, Hiroshi, Morita, Satoshi, Bise, Ryoma, Haga, Hironori
Publikováno v:
In Modern Pathology June 2024 37(6)
Cell detection is an essential task in cell image analysis. Recent deep learning-based detection methods have achieved very promising results. In general, these methods require exhaustively annotating the cells in an entire image. If some of the cell
Externí odkaz:
http://arxiv.org/abs/2107.09289
The domain shift problem is an important issue in automatic cell detection. A detection network trained with training data under a specific condition (source domain) may not work well in data under other conditions (target domain). We propose an unsu
Externí odkaz:
http://arxiv.org/abs/2107.08653
Cell detection is the task of detecting the approximate positions of cell centroids from microscopy images. Recently, convolutional neural network-based approaches have achieved promising performance. However, these methods require a certain amount o
Externí odkaz:
http://arxiv.org/abs/2107.08639
Autor:
Nishimura, Kazuya, Nakano, Eiji, Iida, Kei, Tajima, Hiroyuki, Miyakawa, Takahiko, Yabu, Hiroyuki
Publikováno v:
Phys. Rev. A 103, 033324 (2021)
An impurity atom immersed in an ultracold atomic Fermi gas can form a quasiparticle, so-called Fermi polaron, due to impurity-fermion interaction. We consider a three-dimensional homogeneous dipolar Fermi gas as a medium, where the interatomic dipole
Externí odkaz:
http://arxiv.org/abs/2010.15558
We propose a weakly-supervised cell tracking method that can train a convolutional neural network (CNN) by using only the annotation of "cell detection" (i.e., the coordinates of cell positions) without association information, in which cell position
Externí odkaz:
http://arxiv.org/abs/2007.15258
Autor:
Nishimura, Kazuya, Bise, Ryoma
Automated mitotic detection in time-lapse phasecontrast microscopy provides us much information for cell behavior analysis, and thus several mitosis detection methods have been proposed. However, these methods still have two problems; 1) they cannot
Externí odkaz:
http://arxiv.org/abs/2004.12531