A Survey on Brain Tumor Segmentation Using MRI Data

International Journal of Research in Engineering, Science and Management

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Field Value
Title A Survey on Brain Tumor Segmentation Using MRI Data
Creator Sushanth, J. A.
Rudresh, G. S.
Prabhu, K. Anuj
Ali, Arif
Subject Artificial Intelligence
Brain tumor segmentation
Deep Learning
Image segmentation
MRI scan
Neural Networks
Description Gliomas are the most frequent primary brain tumors, with varying degrees of aggressiveness, prognosis, and histological sub-regions, such as peritumoral edematous, necrotic core, active, and non-enhancing core. Variable intensity profiles spread throughout multi-parametric magnetic resonance imaging (mpMRI) images illustrate these sub-regions, representing diverse biological features. In longitudinal scans, the amount of resected tumor is also taken into account while evaluating the apparent tumor for possible progression diagnosis. Furthermore, there is growing evidence that accurate segmentation of multiple tumor sub-regions can provide a foundation for quantitative image analysis to predict patient overall survival. Manual segmentation of brain tumor regions is time-consuming and prone to human error, and its accuracy is determined by pathologists' experience. This study includes about 10 scientific papers that address a wide range of technical topics, including network architecture design, segmentation under imbalanced situations, and multi-modality processes. We use this survey to present a complete assessment of newly established deep learning-based brain tumor segmentation algorithms, taking into account the astonishing breakthroughs produced by state-of-the-art technology.
Publisher RESAIM
Date 2022-05-01
Type info:eu-repo/semantics/article
Peer-reviewed Article
Format application/pdf
Identifier https://www.journals.resaim.com/ijresm/article/view/1982
Source International Journal of Research in Engineering, Science and Management; Vol. 5 No. 4 (2022); 169-171
Language eng
Relation https://www.journals.resaim.com/ijresm/article/view/1982/1922
Rights Copyright (c) 2022 J. A. Sushanth, G. S. Rudresh, K. Anuj Prabhu, Arif Ali

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