A survey of deep learning for MRI brain tumor segmentation methods: Trends, challenges, and future directions

ConclusionThis review's objective is to increase scholars' interest in this difficult field and familiarize them with current advancements in it. To create CAD systems aimed at brain tumor identification using MR images, digital image processing approaches, such as preprocessing, segmentation, and classification, are applied. The classic machine learning and deep learning approaches for brain tumor identification are deliberated in this work. This paper provides a summary of commonly used MR image datasets. For classification, various machine learning and deep learning algorithms have been used. This survey examines current methodologies and can be used in the future to develop effective diagnostic plans for other brain disorders such as dementia, Alzheimer's disease, stroke, and Parkinson's disease using various Magnetic Resonance imaging modalities.
Source: Health and Technology - Category: Information Technology Source Type: research