Detection of white matter lesion regions in MRI using SLIC0 and convolutional neural network.
Journal:
Computer methods and programs in biomedicine
Published Date:
Apr 19, 2018
Abstract
BACKGROUND AND OBJECTIVE: White matter lesions are non-static brain lesions that have a prevalence rate up to 98% in the elderly population. Because they may be associated with several brain diseases, it is important that they are detected as soon as possible. Magnetic Resonance Imaging (MRI) provides three-dimensional data with the possibility to detect and emphasize contrast differences in soft tissues, providing rich information about the human soft tissue anatomy. However, the amount of data provided for these images is far too much for manual analysis/interpretation, representing a difficult and time-consuming task for specialists. This work presents a computational methodology capable of detecting regions of white matter lesions of the brain in MRI of FLAIR modality. The techniques highlighted in this methodology are SLIC0 clustering for candidate segmentation and convolutional neural networks for candidate classification.
Authors
Keywords
Algorithms
Brain
Databases, Factual
Deep Learning
Diagnosis, Computer-Assisted
False Positive Reactions
Humans
Image Processing, Computer-Assisted
Magnetic Resonance Imaging
Neural Networks, Computer
Pattern Recognition, Automated
Prevalence
Reproducibility of Results
Sensitivity and Specificity
White Matter