Open AccessBig Data Brain Image Data Repair and Diagnosis Technology Based on Deep Learning
Author(s) -
Yunlong Wang,
Luxu Liang,
Zhijie Qu
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/769/4/042075
Subject(s) - artificial intelligence , computer science , computer vision , feature extraction , brain tumor , pattern recognition (psychology) , deep learning , image (mathematics) , feature (linguistics) , medicine , linguistics , philosophy , pathology
In this paper, we propose an automatic tumor detection algorithm in MRI brain images based on significance modeling based on directional features.Firstly, the MRI brain image is preprocessed to remove the interference of the skull region in the image.Then, directional-feature-based saliency detection is used to increase the contrast of the lesion area to achieve more accurate extraction of the tumor image area.A large number of experiments have been carried out on the brain image data sets, and compared with the mainstream automatic tumor detection methods, the effectiveness of the proposed algorithm has been proved.