Quantification of Brain Lesions in Multiple Sclerosis Patients using Segmentation by Convolutional Neural Networks.
Marcela de OliveiraFelipe Balistieri SantinelliMarina Piacenti-SilvaFernando Coronetti Gomes RochaFabio Augusto BarbieriPaulo Noronha Lisboa-FilhoJorge Manuel SantosJaime dos Santos CardosoPublished in: BIBM (2020)
Keyphrases
- multiple sclerosis
- brain mri
- lesion segmentation
- convolutional neural networks
- gad enhancing
- magnetic resonance images
- grey matter
- corpus callosum
- anatomical structures
- medical images
- white matter
- region growing
- clinical trials
- mr images
- brain tissue
- magnetic resonance
- brain tumors
- brain structures
- multiscale
- medical imaging
- level set
- segmentation method
- image segmentation
- image analysis
- edge detection
- cerebrospinal fluid
- segmentation algorithm
- fully automatic
- shape prior
- magnetic resonance imaging
- energy function
- manual segmentation
- mri data
- brain images
- medical image analysis
- caudate nucleus
- quantitative evaluation