LA-ViT: A Network With Transformers Constrained by Learned-Parameter-Free Attention for Interpretable Grading in a New Laryngeal Histopathology Image Dataset-Reference-Cited by-同舟云学术

LA-ViT: A Network With Transformers Constrained by Learned-Parameter-Free Attention for Interpretable Grading in a New Laryngeal Histopathology Image Dataset

Published:2024-06 Issue:6 Volume:28 Page:3557-3570
ISSN:2168-2194
Container-title:IEEE Journal of Biomedical and Health Informatics
language:
Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Huang Pan¹^ORCID,Xiao Hualiang²^ORCID,He Peng¹^ORCID,Li Chentao³^ORCID,Guo Xiaodong¹^ORCID,Tian Sukun⁴^ORCID,Feng Peng¹^ORCID,Chen Hu⁴^ORCID,Sun Yuchun⁴^ORCID,Mercaldo Francesco⁵^ORCID,Santone Antonella⁵^ORCID,Qin Jing⁶^ORCID

Affiliation:

1. College of Optoelectronic Engineering, Chongqing University, Chongqing, China

2. Department of Pathology, Daping Hospital, Army Medical University, Chongqing, China

3. College of Mathematics and Statistics, Chongqing University, Chongqing, China

4. Center of Digital Dentistry, Faculty of Prosthodontics, Peking University School and Hospital of Stomatology, Beijing, China

5. Department of Medicine and Health Sciences “Vincenzo Tiberio”, University of Molise, Campobasso, Italy

6. School of Nursing, The Hong Kong Polytechnic University, Hong Kong, SAR China

Funder

Graduate Scientific Research and Innovation Foundation of Chongqing

National Key R&D Program of China

Beijing Natural Science Foundation

National Natural Science Foundation of China

Innovation and Technology Fund

Midstream Research Programme for Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6221020/10550931/10460116.pdf?arnumber=10460116

Reference38 articles.

1. Expression Profile of p63 in 127 Patients with Laryngeal Squamous Cell Carcinoma

2. Head and Neck Squamous Cell Carcinoma: Update on Epidemiology, Diagnosis, and Treatment

3. Diagnostic Histopathology of Tumors

4. Identify Representative Samples by Conditional Random Field of Cancer Histology Images

5. Explanation and Use of Uncertainty Obtained by Bayesian Neural Network Classifiers for Breast Histopathology Images

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