A Hybrid Approach Based on Deep CNN and Machine Learning Classifiers for the Tumor Segmentation and Classification in Brain MRI.

ABSTRACT: Conventional medical imaging and machine learning techniques are not perfect enough to correctly segment the brain tumor in MRI as the proper identification and segmentation of tumor borders are one of the most important criteria of tumor extraction. The existing approaches are time-consuming, incursive, and susceptible to human mistake. These drawbacks highlight the importance of developing a completely automated deep learning-based approach for segmentation and classification of brain tumors. The expedient and prompt segmentation and classification of a brain tumor are critical for accurate clinical diagnosis and adequately treatment. As a result, deep learning-based brain tumor segmentation and classification algorithms are extensively employed. In the deep learning-based brain tumor se

SUBMITTER: Haq EU 

PROVIDER: S-EPMC9400402 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature