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Histogram equalization-based techniques for contrast enhancement of MRI brain Glioma tumor images: Comparative study., , , and . ATSIP, page 1-6. IEEE, (2018)A computer aided diagnosis 'CAD' for brain glioma exploration., , , , , and . ATSIP, page 243-248. IEEE, (2014)Deep Convolutional Encoder-Decoder algorithm for MRI brain reconstruction., , , , , and . Medical Biol. Eng. Comput., 59 (7-8): 85-106 (2021)Review of Computer Aided-Diagnosis (CAD) Systems for MRI Gliomas brain tumors explorations based on Machine Learning and Deep learning., , , and . ATSIP, page 1-6. IEEE, (2022)A distribution-matching approach to MRI brain tumor segmentation., , and . ISBI, page 1707-1710. IEEE, (2012)Computer Aided Diagnosis (CAD) tool for MS lesions exploration In multimodal brain MRI., , , , and . ATSIP, page 1-6. IEEE, (2022)Deep Transfer Learning (DTL) Based-Framework for an Accurate Multi-classification of MRI Brain Tumors., , , , and . CW, page 86-93. IEEE, (2023)Glioblastomas brain Tumor Segmentation using Optimized U-Net based on Deep Fully Convolutional Networks (D-FCNs)., , , and . ATSIP, page 1-6. IEEE, (2020)Towards a computer aided diagnosis (CAD) for brain MRI glioblastomas tumor exploration based on a deep convolutional neuronal networks (D-CNN) architectures., , , , , and . Multim. Tools Appl., 80 (1): 899-919 (2021)Brief review of multiple sclerosis lesions segmentation methods on conventional magnetic resonance imaging., , , , and . ATSIP, page 249-253. IEEE, (2014)