18 citations · 22 across the 14 of their papers we have counts for
7 papers · 1 filter
Statistical Testing for Multiple Instance Learning via Selective Inference with Applications to Computational Pathology
Noriaki Hashimoto, Shuichi Nishino, Teruyuki Katsuoka +7
Multiple instance learning (MIL) is widely used in computational pathology because it enables weakly supervised analysis of whole-slide images (WSIs) without requiring patch-level…
Multi-Scale Representation of Follicular Lymphoma Pathology Images in a Single Hyperbolic Space
Kei Taguchi, Kazumasa Ohara, Tatsuya Yokota +4
We propose a method for representing malignant lymphoma pathology images, from high-resolution cell nuclei to low-resolution tissue images, within a single hyperbolic space using s…
Explainable Classifier for Malignant Lymphoma Subtyping via Cell Graph and Image Fusion
Daiki Nishiyama, Hiroaki Miyoshi, Noriaki Hashimoto +4
Malignant lymphoma subtype classification directly impacts treatment strategies and patient outcomes, necessitating classification models that achieve both high accuracy and suffic…
Mixing Histopathology Prototypes into Robust Slide-Level Representations for Cancer Subtyping
Joshua Butke, Noriaki Hashimoto, Ichiro Takeuchi +3
Whole-slide image analysis via the means of computational pathology often relies on processing tessellated gigapixel images with only slide-level labels available. Applying multipl…
Case-based Similar Image Retrieval for Weakly Annotated Large Histopathological Images of Malignant Lymphoma Using Deep Metric Learning
Noriaki Hashimoto, Yusuke Takagi, Hiroki Masuda +20
In the present study, we propose a novel case-based similar image retrieval (SIR) method for hematoxylin and eosin (H&E)-stained histopathological images of malignant lymphoma. Whe…
Multi-scale Domain-adversarial Multiple-instance CNN for Cancer Subtype Classification with Unannotated Histopathological Images
Noriaki Hashimoto, Daisuke Fukushima, Ryoichi Koga +7
We propose a new method for cancer subtype classification from histopathological images, which can automatically detect tumor-specific features in a given whole slide image (WSI).…
Computing Valid p-values for Image Segmentation by Selective Inference
Kosuke Tanizaki, Noriaki Hashimoto, Yu Inatsu +2
Image segmentation is one of the most fundamental tasks of computer vision. In many practical applications, it is essential to properly evaluate the reliability of individual segme…