A Unified Approach Addressing Class Imbalance in Magnetic Resonance Image for Deep Learning Models-Reference-Cited by-同舟云学术

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A Unified Approach Addressing Class Imbalance in Magnetic Resonance Image for Deep Learning Models

Published:2024 Issue: Volume:12 Page:27368-27384
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Cui Lijuan¹^ORCID,Li Dengao¹^ORCID,Yang Xiaofeng²,Liu Chao³,Yan Xiaoting²

Affiliation:

1. College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan, China

2. Department of Urology, First Hospital of Shanxi Medical University, Taiyuan, Shanxi, China

3. Department of Bioengeering Research Center, First Hospital of Shanxi Medical University, Shanxi Medical University, Taiyuan, Shanxi, China

Funder

Central Government Guided Local Science and Technology Development Fund Project

National Natural Science Foundation of China

National Major Scientific Research Instrument Development Project of China

Key Research and Development Projects of Shanxi Province

Central Guidance on Local Science and Technology Development Fund of Shanxi Province

Patents Transformation Project of Shanxi Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10433506.pdf?arnumber=10433506

Reference70 articles.

1. Addressing class imbalance in deep learning for small lesion detection on medical images

2. A Foreground Prototype-Based One-Shot Segmentation of Brain Tumors

3. Enhanced Performance of Brain Tumor Classification via Tumor Region Augmentation and Partition

4. Classification of Brain MRI Tumor Images Based on Deep Learning PGGAN Augmentation

5. Brain tumor segmentation with deep convolutional symmetric neural network

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