Multimodal Brain Tumor Classification and Detection using Deep Learning and Robust Feature Selection: A Comprehensive Survey

Shrisha MR, Gururaj C

Abstract


This research presents a comprehensive literature review of various Deep learning techniques with metaheuristic and hybrid based approaches for segmenting, classifying and detecting brain tumors from MRI images.  It provides an in detail analysis and quantitative evaluation of conventional segmentation and classification methods employed in recent years. By examining the recent techniques the many key insights like performance metrics, datasets, strengths and limitations of different techniques are acquired. The collaborative efforts between researchers, clinicians and industry experts are necessary to translate deep learning advancements into clinical practice. However clinical validation and deployment of deep learning models in real-world settings are crucial for improving patient outcomes.

Keywords


Brain Tumor; MRI image; Radiomics; MCCNN; U-Net; PGAN; AlexNet-gru; Whale Optimization Algorithm

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DOI: http://doi.org/10.11591/ijres.v14.i2.pp%25p

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