A novel approach to the detection of multiple sclerosis (MS) lesions is presented, which uses an adaptive formulation of the anisotropic diffusion and fuzzy-c-means (FCM) clustering. In opposition to previous works of the same authors, FCM runs only on PD weighted slices that, for each examination, are composed in a unique data set. Images are preprocessed with an an isotropic diffusion filter whose diffusion function has been adaptively optimized to aggregate pixels belonging to lesions and cut off all the others. Adaptivity is used to achieve significant noise reduction. A detailed description of the proposed approach is presented, along with first experimental results.
Automatic segmentation of MR images based on adaptive anisotropic filtering
2003-01-01
405135 byte
Conference paper
Electronic Resource
English
Automatic Segmentation of MR Images Based on Adaptive Anisotropic Filtering
British Library Conference Proceedings | 2003
|Structure adaptive anisotropic image filtering
British Library Online Contents | 1996
|Weighted-Fitting-Based Adaptive Filtering of Images
British Library Conference Proceedings | 1995
|Adaptive segmentation of ultrasound images
British Library Online Contents | 1999
|Automatic nerve segmentation of ultrasound images
IEEE | 2017
|