Print Email Facebook Twitter Early Detection of Rheumatoid Arthritis using extremity MRI: Quantification of Bone Marrow Edema in the Carpal bones Title Early Detection of Rheumatoid Arthritis using extremity MRI: Quantification of Bone Marrow Edema in the Carpal bones Author Roex, E.A.H. Contributor Lelieveldt, B.P.F. (mentor) Stoel, B.C. (mentor) Faculty Mechanical, Maritime and Materials Engineering Department BioMechanical Engineering Programme BioMedical Engineering Date 2015-03-20 Abstract Visual scoring of magnetic resonance images for the early detection of rheumatoid arthritis is prone to human subjectivity and lacks sensitivity. In a bid to develop an objective and quantitative alternative using digital image processing, this thesis proposes automatic segmentation of the carpal bones, followed by the quantification of bone marrow edema, which is an important inflammatory imaging biomarker. Segmentation of the carpal bones is achieved using multi atlas-based segmentation. Compared to manual segmentations of the training data, an average Dice overlap of 0.85 was achieved. By examining contrast-enhanced MR images of the wrist, edematous bone is classified from normal bone marrow using knowledge based fuzzy clustering. Validation of the quantitative score against the existing RA MRI Scoring (RAMRIS) system showed a significant positive correlation. Segmentation error was seen to be a confounding factor, limiting the specificity of the BME measure. To increase agreement and maximise the available information, it is recommended that data from a complementary imaging plane is included. Subject MRIReumatoid ArthritisImage processingBiomedicalSegmentation To reference this document use: http://resolver.tudelft.nl/uuid:7145d7a6-25bb-42a4-ba48-240d70a68792 Coordinates 51.999734, 4.375790 Part of collection Student theses Document type master thesis Rights (c) 2015 Roex, E.A.H. Files PDF EAH_Roex_4253450_MScThesi ... 0Mar15.pdf 9.12 MB Close viewer /islandora/object/uuid:7145d7a6-25bb-42a4-ba48-240d70a68792/datastream/OBJ/view