UJAT-Net: A U-Net Combined Joint-Attention and Transformer for Breast Tubule Segmentation in H&E Stained Images-Reference-Cited by-同舟云学术

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UJAT-Net: A U-Net Combined Joint-Attention and Transformer for Breast Tubule Segmentation in H&E Stained Images

Published:2024 Issue: Volume:12 Page:34582-34591
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Liu Li-Wang¹,Huang Zhao¹^ORCID,Lu Kao-Yan¹,Wang Zu-Xuan¹,Liang Yao-Ming¹,Lin Shi-Yu¹^ORCID,Ji Yan-Hong¹^ORCID

Affiliation:

1. Key Laboratory of Atomic and Subatomic Structure and Quantum Control (Ministry of Education), Guangdong Basic Research Center of Excellence for Structure and Fundamental Interactions of Matter, School of Physics, South China Normal University, Guangzhou, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10445190.pdf?arnumber=10445190

Reference38 articles.

1. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries

2. Tavassoli FA, Devilee P: Pathology and Genetics: Tumours of the Breast and Female Genital Organs. WHO Classification of Tumours series - volume IV. Lyon, France: IARC Press

3. Pathological prognostic factors in breast cancer. I. The value of histological grade in breast cancer: experience from a large study with long-term follow-up. C. W. Elston & I. O. Ellis.Histopathology1991; 19; 403-410

4. ProstAttention-Net: A deep attention model for prostate cancer segmentation by aggressiveness in MRI scans

5. JointRCNN: A Region-Based Convolutional Neural Network for Optic Disc and Cup Segmentation

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