title: LoAd: a locally adaptive cortical segmentation algorithm.
abstract: Thickness measurements of the cerebral cortex can aid diagnosis and provide valuable information about the temporal evolution of diseases such as Alzheimer's, Huntington's, and schizophrenia. Methods that measure the thickness of the cerebral cortex from in-vivo magnetic resonance (MR) images rely on an accurate segmentation of the MR data. However, segmenting the cortex in a robust and accurate way still poses a challenge due to the presence of noise, intensity non-uniformity, partial volume effects, the limited resolution of MRI and the highly convoluted shape of the cortical folds. Beginning with a well-established probabilistic segmentation model with anatomical tissue priors, we propose three post-processing refinements: a novel modification of the prior information to reduce segmentation bias; introduction of explicit partial volume classes; and a locally varying MRF-based model for enhancement of sulci and gyri. Experiments performed on a new digital phantom, on BrainWeb data and on data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) show statistically significant improvements in Dice scores and PV estimation (p<10(-3)) and also increased thickness estimation accuracy when compared to three well established techniques.
authors.affiliation: Centre for Medical Image Computing (CMIC), University College London, London, UK. manuel.cardoso@ucl.ac.uk
authors.forename: M Jorge
authors.initials: MJ
authors.lastname: Cardoso
authors.forename: Matthew J
authors.initials: MJ
authors.lastname: Clarkson
authors.forename: Gerard R
authors.initials: GR
authors.lastname: Ridgway
authors.forename: Marc
authors.initials: M
authors.lastname: Modat
authors.forename: Nick C
authors.initials: NC
authors.lastname: Fox
authors.forename: Sebastien
authors.initials: S
authors.lastname: Ourselin
mesh_terms: D000465:Algorithms; D000544:Alzheimer Disease / Q000473:pathology; D001271:Atlases as Topic; D001921:Brain / Q000033:anatomy & histology; D002540:Cerebral Cortex / Q000033:anatomy & histology* / Q000473:pathology; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007091:Image Processing, Computer-Assisted / Q000379:methods; D016013:Likelihood Functions; D008390:Markov Chains; D008959:Models, Neurological; D015233:Models, Statistical; D009434:Neural Pathways / Q000033:anatomy & histology; D016011:Normal Distribution