Zobrazeno 1 - 10
of 150
pro vyhledávání: '"Bise, Ryoma"'
Publikováno v:
Medical Image Analysis 2024
Automatic image-based severity estimation is an important task in computer-aided diagnosis. Severity estimation by deep learning requires a large amount of training data to achieve a high performance. In general, severity estimation uses training dat
Externí odkaz:
http://arxiv.org/abs/2409.04952
Autor:
Kubo, Shunsuke, Matsuo, Shinnosuke, Suehiro, Daiki, Terada, Kazuhiro, Ito, Hiroaki, Yoshizawa, Akihiko, Bise, Ryoma
Learning from label proportions (LLP) is a kind of weakly supervised learning that trains an instance-level classifier from label proportions of bags, which consist of sets of instances without using instance labels. A challenge in LLP arises when th
Externí odkaz:
http://arxiv.org/abs/2408.14130
Autor:
Matsuo, Shinnosuke, Suehiro, Daiki, Uchida, Seiichi, Ito, Hiroaki, Terada, Kazuhiro, Yoshizawa, Akihiko, Bise, Ryoma
In this paper, we address the segmentation of tumor subtypes in whole slide images (WSI) by utilizing incomplete label proportions. Specifically, we utilize `partial' label proportions, which give the proportions among tumor subtypes but do not give
Externí odkaz:
http://arxiv.org/abs/2405.09041
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
3D cell tracking in a living organism has a crucial role in live cell image analysis. Cell tracking in C. elegans has two difficulties. First, cell migration in a consecutive frame is large since they move their head during scanning. Second, cell det
Externí odkaz:
http://arxiv.org/abs/2403.13412
The paper proposes a novel problem in multi-class Multiple-Instance Learning (MIL) called Learning from the Majority Label (LML). In LML, the majority class of instances in a bag is assigned as the bag's label. LML aims to classify instances using ba
Externí odkaz:
http://arxiv.org/abs/2403.13370
Learning from label proportions (LLP) is a promising weakly supervised learning problem. In LLP, a set of instances (bag) has label proportions, but no instance-level labels are given. LLP aims to train an instance-level classifier by using the label
Externí odkaz:
http://arxiv.org/abs/2308.08822
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
Autor:
Liu, Xiaoqing, Araki, Kengo, Harada, Shota, Yoshizawa, Akihiko, Terada, Kazuhiro, Kurata, Mariyo, Nakajima, Naoki, Abe, Hiroyuki, Ushiku, Tetsuo, Bise, Ryoma
The domain shift in pathological segmentation is an important problem, where a network trained by a source domain (collected at a specific hospital) does not work well in the target domain (from different hospitals) due to the different image feature
Externí odkaz:
http://arxiv.org/abs/2304.13513
The development of medical image segmentation using deep learning can significantly support doctors' diagnoses. Deep learning needs large amounts of data for training, which also requires data augmentation to extend diversity for preventing overfitti
Externí odkaz:
http://arxiv.org/abs/2304.13490