Spinal cord grey matter segmentation challenge

Spinal cord grey matter segmentation challenge

An important image processing step in spinal cord magnetic resonance imaging is the ability to reliably and accurately segment grey and white matter for tissue specific analysis. There are several semi- or fully-automated segmentation methods for cervical cord cross-sectional area measurement with an excellent performance close or equal to the manual segmentation. However, grey matter segmentat...

Fully automated grey and white matter spinal cord segmentation

Axonal loss in the spinal cord is one of the main contributing factors to irreversible clinical disability in multiple sclerosis (MS). In vivo axonal loss can be assessed indirectly by estimating a reduction in the cervical cross-sectional area (CSA) of the spinal cord over time, which is indicative of spinal cord atrophy, and such a measure may be obtained by means of image segmentation using ...

Spinal Cord Grey Matter Pathology in Multiple Sclerosis

Spinal cord gray matter segmentation using deep dilated convolutions

Gray matter (GM) tissue changes have been associated with a wide range of neurological disorders and was also recently found relevant as a biomarker for disability in amyotrophic lateral sclerosis. The ability to automatically segment the GM is, therefore, an important task for modern studies of the spinal cord. In this work, we devise a modern, simple and end-to-end fully automated human spina...

Mathematical segmentation of grey matter, white matter and cerebral spinal fluid from MR image pairs.

The aims of this study were (1) to design a mathematical segmentation technique to allow extraction of grey matter, white matter and cerebral spinal fluid volumes from paired high resolution MR images and (2) to document the statistical accuracy of the method with different image combinations. A series of linear equations were derived that describe proportional tissue volumes in individual imag...