Structure Embedded Nucleus Classification for Histopathology Images-Reference-Cited by-同舟云学术

Structure Embedded Nucleus Classification for Histopathology Images

Published:2024-09 Issue:9 Volume:43 Page:3149-3160
ISSN:0278-0062
Container-title:IEEE Transactions on Medical Imaging
language:
Short-container-title:IEEE Trans. Med. Imaging

Author:

Lou Wei¹^ORCID,Wan Xiang¹^ORCID,Li Guanbin²^ORCID,Lou Xiaoying³^ORCID,Li Chenghang⁴,Gao Feng⁵^ORCID,Li Haofeng¹^ORCID

Affiliation:

1. Shenzhen Research Institute of Big Data, Guangdong Provincial Key Laboratory of Big Data Computing, The Chinese University of Hong Kong at Shenzhen, Shenzhen, China

2. School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China

3. Department of Pathology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China

4. Artificial Intelligence Thrust, The Hong Kong University of Science and Technology at Guangzhou, Guangzhou, China

5. Department of Colorectal Surgery, Department of General Surgery, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China

Funder

Chinese Key-Area Research and Development Program of Guangdong Province

Basic and Applied Basic Research Foundation of Guangdong Province

National Natural Science Foundation of China

Guangdong Provincial Key Laboratory of Big Data Computing, The Chinese University of Hong Kong, Shenzhen

National Key Clinical Discipline

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/42/10663877/10497696.pdf?arnumber=10497696

Reference75 articles.

1. Vision Transformers for Computational Histopathology

2. SwinCup: Cascaded swin transformer for histopathological structures segmentation in colorectal cancer

3. Nuclear shape and orientation features from H&E images predict survival in early-stage estrogen receptor-positive breast cancers

4. Pan-Renal Cell Carcinoma classification and survival prediction from histopathology images using deep learning

5. Automated grading of gliomas using deep learning in digital pathology images: A modular approach with ensemble of convolutional neural networks;Ertosun

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