Polyp-Mixer: An Efficient Context-Aware MLP-Based Paradigm for Polyp Segmentation-Reference-Cited by-同舟云学术

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Polyp-Mixer: An Efficient Context-Aware MLP-Based Paradigm for Polyp Segmentation

Published:2023-01 Issue:1 Volume:33 Page:30-42
ISSN:1051-8215
Container-title:IEEE Transactions on Circuits and Systems for Video Technology
language:
Short-container-title:IEEE Trans. Circuits Syst. Video Technol.

Author:

Shi Jing-Hui¹,Zhang Qing¹^ORCID,Tang Yu-Hao²,Zhang Zhong-Qun³

Affiliation:

1. School of Computer Science and Information Engineering, Shanghai Institute of Technology, Shanghai, China

2. Department of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China

3. Department of Computer Science, University of Birmingham, Birmingham, U.K.

Funder

Municipal Natural Science Foundation of Shanghai

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Media Technology

Link

http://xplorestaging.ieee.org/ielx7/76/10007626/09852486.pdf?arnumber=9852486

Reference60 articles.

1. Automated Diagnosis of Various Gastrointestinal Lesions Using a Deep Learning–Based Classification and Retrieval Framework With a Large Endoscopic Database: Model Development and Validation

2. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification

3. Artificial Intelligence-Based Classification of Multiple Gastrointestinal Diseases Using Endoscopy Videos for Clinical Diagnosis

4. Enhanced-alignment Measure for Binary Foreground Map Evaluation

5. Psi-Net: Shape and boundary aware joint multi-task deep network for medical image segmentation

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