An automated metaheuristic-optimized approach for diagnosing and classifying brain tumors based on a convolutional neural network-Reference-Cited by-同舟云学术

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An automated metaheuristic-optimized approach for diagnosing and classifying brain tumors based on a convolutional neural network

Published:2024-09 Issue: Volume:23 Page:102459
ISSN:2590-1230
Container-title:Results in Engineering
language:en
Short-container-title:Results in Engineering

Author:

Aljohani Mansourah,Bahgat Waleed M.,Balaha Hossam Magdy,AbdulAzeem Yousry,El-Abd Mohammed,Badawy Mahmoud^ORCID,Elhosseini Mostafa A.

Publisher

Elsevier BV

Reference87 articles.

1. An ensemble of optimal deep learning features for brain tumor classification;Aziz;Comput. Mater. Continua,2021

2. A survey of methods for brain tumor segmentation-based MRI images;Mohammed;J. Comput. Des. Eng.,2023

3. Salp swarm algorithm with iterative mapping and local escaping for multi-level threshold image segmentation: a skin cancer dermoscopic case study;Hao;J. Comput. Des. Eng.,2023

4. Optimization driven deep convolution neural network for brain tumor classification;Kumar;Biocybern. Biomed. Eng.,2020

5. An ensemble model for the diagnosis of brain tumors through MRIs;Ghafourian;Diagnostics,2023

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Towards ovarian cancer diagnostics: A vision transformer-based computer-aided diagnosis framework with enhanced interpretability;Results in Engineering;2024-09

2. A Comprehensive Review of AI Diagnosis Strategies for Age-Related Macular Degeneration (AMD);Bioengineering;2024-07-13

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