Y-net: a reducing gaussian noise convolutional neural network for MRI brain tumor classification with NADE concatenation-Reference-Cited by-同舟云学术

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Y-net: a reducing gaussian noise convolutional neural network for MRI brain tumor classification with NADE concatenation

Published:2021-07-13 Issue:5 Volume:7 Page:055006
ISSN:2057-1976
Container-title:Biomedical Physics & Engineering Express
language:
Short-container-title:Biomed. Phys. Eng. Express

Author:

Hashemzehi Raheleh^ORCID,Seyyed Mahdavi Seyyed Javad,Kheirabadi Maryam,Kamel Seyed Reza

Publisher

IOP Publishing

Subject

General Nursing

Link

https://iopscience.iop.org/article/10.1088/2057-1976/ac107b/pdf

Reference38 articles.

1. Deep learning-based brain tumor classification and detection system;Ari;Turkish J. Electr. Eng. Comput. Sci.,2018

2. Development of deep learning algorithm using convolutional neural network for medical imaging;Khadke;Int. J. Eng. Adv. Technol.,2020

3. Brain tumor classification for MR images using transfer learning and fine-tuning;Swati;Comput. Med. Imaging Graph.,2019

4. An integrated design of particle swarm optimization (PSO) with a fusion of features for detection of brain tumor;Sharif;Pattern Recognit. Lett.,2020

5. Magnetic resonance imaging-based brain tumor grades classification and grading via convolutional neural networks and genetic algorithms;Kabir Anaraki;Biocybern. Biomed. Eng.,2019

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2. Tackling the small data problem in medical image classification with artificial intelligence: a systematic review;Progress in Biomedical Engineering;2024-06-17

3. Brain Tumor Recognition Using Artificial Intelligence Neural-Networks (BRAIN): A Cost-Effective Clean-Energy Platform;Neuroglia;2024-04-28

4. Medical image identification methods: A review;Computers in Biology and Medicine;2024-02

5. Thermal Noise Removal of Magnetic Resonance Images: A Deep Learning Approach Based on an Attentive Residue Multi-Dilated Network with Adaptive Filtering and Discrete Cosine Transform;2023 International Joint Conference on Neural Networks (IJCNN);2023-06-18

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