DPAFNet: A Residual Dual-Path Attention-Fusion Convolutional Neural Network for Multimodal Brain Tumor Segmentation-Reference-Cited by-同舟云学术

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DPAFNet: A Residual Dual-Path Attention-Fusion Convolutional Neural Network for Multimodal Brain Tumor Segmentation

Published:2023-01 Issue: Volume:79 Page:104037
ISSN:1746-8094
Container-title:Biomedical Signal Processing and Control
language:en
Short-container-title:Biomedical Signal Processing and Control

Author:

Chang Yankang,Zheng Zhouzhou,Sun Yingwei,Zhao Mengmeng,Lu Yao,Zhang Yan

Funder

Natural Science Foundation of Shandong Province

Qingdao University of Science and Technology

Publisher

Elsevier BV

Subject

Health Informatics,Signal Processing,Biomedical Engineering

Reference60 articles.

1. WLFS: Weighted label fusion learning framework for glioma tumor segmentation in brain MRI;Barzegar;Biomed. Signal Process. Control,2021

2. MR brain segmentation based on DE-ResUnet combining texture features and background knowledge;Wu;Biomed. Signal Process. Control,2022

3. Scale-adaptive super-feature based MetricUNet for brain tumor segmentation;Liu;Biomed. Signal Process. Control,2022

4. Relax and focus on brain tumor segmentation;Wang;Med. Image Anal.,2022

5. A deep learning model integrating FCNNs and CRFs for brain tumor segmentation;Zhao;Med. Image Anal.,2018

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