K
Kazuaki Nakane
Researcher at Osaka University
Publications - 41
Citations - 434
Kazuaki Nakane is an academic researcher from Osaka University. The author has contributed to research in topics: Hyperbolic partial differential equation & Quenching. The author has an hindex of 8, co-authored 40 publications receiving 304 citations. Previous affiliations of Kazuaki Nakane include Osaka Institute of Technology.
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Fast and accurate tumor segmentation of histology images using persistent homology and deep convolutional features
Talha Qaiser,Yee-Wah Tsang,Daiki Taniyama,Naoya Sakamoto,Kazuaki Nakane,David Epstein,Nasir M. Rajpoot,Nasir M. Rajpoot,Nasir M. Rajpoot +8 more
TL;DR: In this paper, the authors proposed a tumor segmentation framework based on the novel concept of persistent homology profiles (PHPs), which can distinguish tumor regions from their normal counterparts by modeling the atypical characteristics of tumor nuclei.
Journal ArticleDOI
Persistent Homology for Fast Tumor Segmentation in Whole Slide Histology Images
Talha Qaiser,Korsuk Sirinukunwattana,Kazuaki Nakane,Yee-Wah Tsang,David B. A. Epstein,Nasir M. Rajpoot +5 more
TL;DR: This work proposes a novel tumor segmentation approach for a histology whole-slide image (WSI) by exploring the degree of connectivity among nuclei using the novel idea of persistent homology profiles.
Posted Content
Fast and Accurate Tumor Segmentation of Histology Images using Persistent Homology and Deep Convolutional Features
Talha Qaiser,Yee-Wah Tsang,Daiki Taniyama,Naoya Sakamoto,Kazuaki Nakane,David Epstein,Nasir M. Rajpoot,Nasir M. Rajpoot,Nasir M. Rajpoot +8 more
TL;DR: Wang et al. as discussed by the authors proposed a tumor segmentation framework based on the novel concept of persistent homology profiles (PHPs), which can distinguish tumor regions from their normal counterparts by modeling the atypical characteristics of tumor nuclei.
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A simple mathematical model utilizing topological invariants for automatic detection of tumor areas in digital tissue images
TL;DR: Developing computer assisted diagnostic system for a pathologist will be one of the effective solutions to improve the situation in Japan with respect to the large number of clinical cases that require pathological diagnosis.
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Homology-based method for detecting regions of interest in colonic digital images.
TL;DR: The mathematical system proposed by the group successfully detects ROIs and is a potentially useful tool for differentiating tumor areas in microscopic examination very quickly and could be used to screen for not only colon cancer but other cancers as well.