Segmentation and classification of brain tumour using LRIFCM and LSTM
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11042-024-18478-4.pdf
Reference40 articles.
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2. Masood M, Nazir T, Nawaz M, Mehmood A, Rashid J, Kwon H-Y, Mahmood T, Hussain A (2021) A Novel Deep Learning Method for Recognition and Classification of Brain tumours from MRI Images. Diagnostics 11(5):744. https://doi.org/10.3390/diagnostics11050744
3. Kibriya H, Masood M, Nawaz M, Nazir T (2022) Multiclass classification of brain tumours using a novel CNN architecture. Multimed Tools Appl 81(21):29847–29863. https://doi.org/10.1007/s11042-022-12977-y
4. Atia N, Benzaoui A, Jacques S, Hamiane M, Kourd KE, Bouakaz A, Ouahabi A (2022) Particle swarm optimization and two-way fixed-effects analysis of variance for efficient brain tumour segmentation. Cancers 14(18):4399. https://doi.org/10.3390/cancers14184399
5. Agrawal P, Katal N, Hooda N (2022) Segmentation and classification of brain tumour using 3D-UNet deep neural networks. Int J Cogn Comput Eng 3:199–210. https://doi.org/10.1016/j.ijcce.2022.11.001
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