Enhancing automatic classification of hepatocellular carcinoma images through image masking, tissue changes and trabecular features-Reference-Cited by-同舟云学术

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Enhancing automatic classification of hepatocellular carcinoma images through image masking, tissue changes and trabecular features

Published:2015 Issue:1 Volume:6 Page:26
ISSN:2153-3539
Container-title:Journal of Pathology Informatics
language:en
Short-container-title:J Pathol Inform

Author:

Aziz MaulanaAbdul,Abe Tokiya,Kanazawa Hiroshi,Murakami Yuri,Kimura Fumikazu,Kiyuna Tomoharu,Saito Akira,Ishikawa Masahiro,Kobayashi Naoki,Hashiguchi Akinori,Yamaguchi Masahiro,Yamashita Yoshiko,Sakamoto Michiie

Publisher

Medknow

Subject

Computer Science Applications,Health Informatics,Pathology and Forensic Medicine

Cited by 8 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Self-supervised multi-magnification feature enhancement for segmentation of hepatocellular carcinoma region in pathological images;Engineering Applications of Artificial Intelligence;2024-07

2. Weakly Supervised Framework for Cancer Regions Detection of Hepatocellular Carcinoma in Whole-Slide Pathologic Images Based on Multiscale Attention Convolutional Neural Network;The American Journal of Pathology;2021-12

3. A hybrid network for automatic hepatocellular carcinoma segmentation in H&E-stained whole slide images;Medical Image Analysis;2021-02

4. Convolutional autoencoder based model HistoCAE for segmentation of viable tumor regions in liver whole-slide images;Scientific Reports;2021-01-08

5. Whole Slide Imaging and Its Applications to Histopathological Studies of Liver Disorders;Frontiers in Medicine;2020-01-08

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