Markov random field-based parcellation of the cerebral cortex: application to histology images
- Resource Type
- Conference
- Authors
- Adamson, C.; Davies, R.; Inder, T.; Rees, S.; Mareels, I.; Egan, G.
- Source
- Proceedings of the 2004 Intelligent Sensors, Sensor Networks and Information Processing Conference, 2004. Intelligent Sensors, Sensor Networks and Information Intelligent Sensors, Sensor Networks and Information Processing Conference, 2004. Proceedings of the 2004. :559-564 2004
- Subject
- Signal Processing and Analysis
Computing and Processing
Components, Circuits, Devices and Systems
Communication, Networking and Broadcast Technologies
Cerebral cortex
Neuroimaging
Digital images
Humans
Neuroscience
Anatomy
Biological cells
Image segmentation
Brain modeling
Magnetic resonance
- Language
The cerebral cortex is composed of regions with a distinct laminar structure. Functional neuroimaging results are often reported with respect to these regions, usually by reference to a standard brain "atlas". Motivated by the need for more precise atlases, we have developed an algorithm that parcellates the cortex into regions of distinct laminar structures. The problem is cast into a segmentation framework and modelled using a Markov random field-based approach. An evaluation of the algorithm on histology images is presented. This technique is presented with a view to producing parcellations on 3D in-vivo magnetic resonance (MR) images of living human subjects.