Design a novel hybrid optimization with tuned deep convolutional neural network classifier for brain tumor segmentation and classification-Reference-Cited by-同舟云学术

Design a novel hybrid optimization with tuned deep convolutional neural network classifier for brain tumor segmentation and classification

Published:2024-01-30 Issue:27 Volume:83 Page:69169-69196
ISSN:1573-7721
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

Viswanathan A.,Umamaheswari M.,M Sathya,Yadav S. J. Karthik Deep

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s11042-024-18315-8.pdf

Reference24 articles.

1. George EB, Rosline GJ, Rajesh DG (2015) Brain tumor segmentation using Cuckoo search optimization for magnetic resonance images. In 2015 IEEE 8th GCC Conference & Exhibition (pp 1–6). IEEE

2. Singh A, Sharma DK (2020) Image collection summarization: Past, present and future. Spotting Data Points with Artificial Intelligence, Data Visualization and Knowledge Engineering, pp 49–78

3. Soleimani V, Vincheh FH (2013) Improving ant colony optimization for brain MRI image segmentation and brain tumor diagnosis. In 2013 first Iranian conference on pattern recognition and image analysis (PRIA) (pp 1–6). IEEE

4. Nema S, Dudhane A, Murala S, Naidu S (2020) RescueNet: An unpaired GAN for brain tumor segmentation. Biomed Signal Process Control 55:101641

5. Natarajan A, Kumarasamy S (2019) Efficient segmentation of brain tumor using FL-SNM with a metaheuristic approach to optimization. J Med Syst 43(2):25

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