The hidden-Markov brain: comparison and inference of white matter hyperintensities on magnetic resonance imaging (MRI).
Rating and quantification of cerebral white matter hyperintensities on magnetic resonance imaging (MRI) are important tasks in various clinical and scientific settings. As manual evaluation is time consuming and imprecise, much effort has been made to automate the quantification of white matter hyperintensities. There is rarely any report that attempts to study the similarity/dissimilarity of white matter hyperintensity patterns that have different sizes, shapes and spatial localizations on the MRI. This paper proposes an original computational neuroscience framework for such a conceptual study with a standpoint that the prior knowledge about white matter hyperintensities can be accumulated and utilized to enable a reliable inference of the rating of a new white matter hyperintensity observation. This computational approach for rating inference of white matter hyperintensities, which appears to be the first study, can be utilized as a computerized rating-assisting tool and can be very economical for diagnostic evaluation of brain tissue lesions.
Bioinformatics Research Group, School of Engineering and Information Technology, University of New South Wales, Canberra, ACT 2600, Australia. t.pham@adfa.edu.au
Tuan D
TD
Pham
Federica
F
Salvetti
Bing
B
Wang
Marco
M
Diani
Walter
W
Heindel
Stefan
S
Knecht
Heike
H
Wersching
Bernhard T
BT
Baune
Klaus
K
Berger
D001921:Brain / Q000473:pathology*; D015331:Cohort Studies; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods; D008390:Markov Chains; D008959:Models, Neurological; D009413:Nerve Fibers, Myelinated / Q000473:pathology*; D010802:Phylogeny