BTSC-TNAS: A neural architecture search-based transformer for brain tumor segmentation and classification-Reference-Cited by-同舟云学术

BTSC-TNAS: A neural architecture search-based transformer for brain tumor segmentation and classification

Published:2023-12 Issue: Volume:110 Page:102307
ISSN:0895-6111
Container-title:Computerized Medical Imaging and Graphics
language:en
Short-container-title:Computerized Medical Imaging and Graphics

Author:

Liu Xiao,Yao Chong,Chen Hongyi,Xiang Rui,Wu Hao,Du Peng,Yu Zekuan,Liu Weifan^ORCID,Liu Jie,Geng Daoying

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Computer Graphics and Computer-Aided Design,Health Informatics,Computer Vision and Pattern Recognition,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Reference49 articles.

1. Brain tumor segmentation and classification using hybrid deep CNN with LuNetClassifier;Balamurugan;Neural Comput. Appl.,2023

2. Mixed-block neural architecture search for medical image segmentation;Bosma,2022

3. Proxylessnas: Direct neural architecture search on target task and hardware;Cai,2019

4. Swin-unet: Unet-like pure transformer for medical image segmentation;Cao,2023

5. Transunet: Transformers make strong encoders for medical image segmentation;Chen,2021

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1. Research on Brain Tumor MRI Image Segmentation Algorithm based on Lightweight Convolutional Polynomial Neural Network;Proceedings of the 2024 10th International Conference on Computer Technology Applications;2024-05-15

2. Transformer’s Role in Brain MRI: A Scoping Review;IEEE Access;2024

3. Neural architecture search for medicine: A survey;Informatics in Medicine Unlocked;2024

4. A review on brain tumor segmentation based on deep learning methods with federated learning techniques;Computerized Medical Imaging and Graphics;2023-12