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• W2555254865 abstract "Quantitative analysis of signal abnormalities in MR imaging for multiple sclerosis and Creutzfeldt-Jakob disease In multiple sclerosis and Creutzfeldt-Jakob disease, pathological changes in the brain result in deviations in signal intensity on MR images. Quantitative analysis of these changes and their correlation with clinical findings provides important information for in vivo diagnosis, therapy planning and follow-up as well as for biomedical research. This thesis presents a framework for fully automated, objective and reproducible quantification of pathology-related signal abnormalities in large amounts of multi-spectral MR data. The overall strategy adopted was to build statistical models for normal brain MR images, including explicit models for MR field inhomogeneities, tissue-specific intensity distributions, spatial clustering of tissue types, and the partial volume effect. Signal abnormalities were detected as model outliers, i.e. voxels that could not be well explained by the model. Throughout this thesis, special attention was paid to automatically estimate all model parameters from the data itself, to eliminate subjective manual tuning and training. Kwantitatieve analyse van signaalabnormaliteiten in MR-beeldvorming voor multiple sclerose en Creutzfeldt-Jakob Bij multiple sclerose en de ziekte van Creutzfeldt-Jakob resulteren pathologische veranderingen in de hersenen in afwijkingen in de signaalintensiteit op MR-beelden. Kwantitatieve analyse van deze veranderingen en hun correlatie met klinische bevindingen levert belangrijke informatie op voor zowel in vivo diagnose, therapieplanning en opvolging als voor biomedisch onderzoek. Deze thesis stelt een raamwerk voor voor volledig automatische, objectieve en reproduceerbare kwantificatie van pathologische signaalafwijkingen in grote hoeveelheden multi-spectrale MR-data. De algemene strategie die werd gevolgd, bestond uit het construeren van statistische modellen voor MR-beelden van normale hersenen, met inbegrip van expliciete modellen voor MR-veldinhomogeniteiten, weefselspecifieke intensiteitsverdelingen, spatiale clustering van weefseltypes, en het partieel-volume-effect. Signaalabnormaliteiten werden gedetecteerd als voxels die niet goed door het model konden worden verklaard. Doorheen deze thesis werd er bijzondere aandacht geschonken aan het automatisch schatten van alle modelparameters uit de data zelf, om subjectieve manuele interventie uit te sluiten." @default.
• W2555254865 created "2016-11-30" @default.
• W2555254865 creator A5058982702 @default.
• W2555254865 date "2001-05-18" @default.
• W2555254865 modified "2023-09-27" @default.
• W2555254865 title "Quantitative analysis of signal abnormalities in MR imaging for multiple sclerosis and creutzfeldt-jakob disease" @default.
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