Unsupervised learning-based clustering approach for smart identification of pathologies and segmentation of tissues in brain magnetic resonance imaging.
Vigneshwaran SenthilvelVishnuvarthanan GovindarajPallikonda Rajasekaran MuruganYudong ZhangThiyagarajan Arun PrasathPublished in: Int. J. Imaging Syst. Technol. (2019)
Keyphrases
- magnetic resonance imaging
- unsupervised learning
- medical images
- magnetic resonance images
- medical imaging
- tissue segmentation
- partial volume effects
- lateral ventricles
- mri data
- gray matter
- mri images
- brain images
- brain mr images
- white matter
- diffusion tensor images
- brain tissue
- brain structures
- brain tumors
- medical image analysis
- single photon emission computed tomography
- partial volume
- magnetic resonance
- mr images
- anatomical structures
- brain segmentation
- breast mri
- positron emission tomography
- supervised learning
- brain mri
- dimensionality reduction
- computer aided diagnosis
- ct images
- image registration
- lesion segmentation
- object recognition
- human brain
- imaging modalities
- computed tomography
- corpus callosum
- semi supervised
- brain imaging
- image analysis
- multiple sclerosis
- image segmentation
- pet images
- computer vision
- x ray
- computer tomography
- k means
- three dimensional
- machine learning
- synthetic data
- high resolution
- remote sensing