Image Segmentation for MR Brain Tumor Detection Using Machine Learning: A Review-Reference-Cited by-同舟云学术

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Image Segmentation for MR Brain Tumor Detection Using Machine Learning: A Review

Published:2023 Issue: Volume:16 Page:70-90
ISSN:1937-3333
Container-title:IEEE Reviews in Biomedical Engineering
language:
Short-container-title:IEEE Rev. Biomed. Eng.

Author:

Soomro Toufique A.¹^ORCID,Zheng Lihong¹^ORCID,Afifi Ahmed J.²^ORCID,Ali Ahmed³^ORCID,Soomro Shafiullah⁴^ORCID,Yin Ming⁵^ORCID,Gao Junbin⁶^ORCID

Affiliation:

1. Charles Sturt University, Bathurst, NSW, Australia

2. Technische Universität Berlin, Berlin, Germany

3. Sukkur IBA University, Sukkur, Pakistan

4. Chung-Ang University, Seoul, South Korea

5. Institute of Semiconductors, South China Normal University, Guangzhou, China

6. University of Sydney, Camperdown, NSW, Australia

Funder

Guangdong Provincial Pearl River Talents Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Biomedical Engineering

Link

http://xplorestaging.ieee.org/ielx7/4664312/10007429/09804867.pdf?arnumber=9804867

Reference143 articles.

1. Automatic Segmentation of Brain Tumor Using 3D SE-Inception Networks with Residual Connections

2. Deep Convolutional Neural Networks Using U-Net for Automatic Brain Tumor Segmentation in Multimodal MRI Volumes

3. Brain Tumor Segmentation in MRI Scans Using Deeply-Supervised Neural Networks

4. Automatic Brain Tumor Segmentation with Domain Adaptation

5. Supervised learning based multimodal MRI brain tumour segmentation using texture features from supervoxels

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