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Segmentation of Multiple Sclerosis Lesions Using Dictionary Learning in Feature Space

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dc.contributor.advisorZhu, Hongmei
dc.creatorKuling, Gregory Christopher
dc.date.accessioned2018-03-01T14:09:14Z
dc.date.available2018-03-01T14:09:14Z
dc.date.copyright2017-08-21
dc.date.issued2018-03-01
dc.date.updated2018-03-01T14:09:14Z
dc.degree.disciplineMathematics & Statistics
dc.degree.levelMaster's
dc.degree.nameMA - Master of Arts
dc.description.abstractManual segmentation is used in the diagnosis, management and evaluation of clinical trials for Multiple Sclerosis (MS), but human error makes manual segmentation variable. Automatic segmentation has been proposed using a Machine Learning algorithm Dictionary Learning (DL). We explored using different feature spaces to automatically segment MS lesions from healthy brain tissue. Methods of image texture analysis quantify the spatial distribution of the voxels in multi-weighted MR scans. We present the results of using a single voxel, single voxel and standard deviation (sigma) of adjacent voxels and a large spatial patch as feature spaces. The single voxel method segments the MS lesions with a Dice Similarity Coefficient (DSC) of 0.985 on simulated Brainweb data, but performed poorly with noise in the image (0.654). The single voxel and sigma performs at a DSC of 0.943 in the presence of 3% noise. The method should be attempted on real patient data.
dc.identifier.urihttp://hdl.handle.net/10315/34387
dc.language.isoen
dc.rightsAuthor owns copyright, except where explicitly noted. Please contact the author directly with licensing requests.
dc.subjectApplied mathematics
dc.subject.keywordsAutomatic segmentation
dc.subject.keywordsMultiple Sclerosis
dc.subject.keywordsMultiple sclerosis lesion
dc.subject.keywordsMachine learning
dc.subject.keywordsDictionary learning
dc.subject.keywordsApplied mathematics
dc.subject.keywordsMedical imaging
dc.subject.keywordsMRI
dc.subject.keywordsMagnetic resonance imaging
dc.subject.keywordsMulti-weighted MRI
dc.subject.keywordsSegmentation
dc.titleSegmentation of Multiple Sclerosis Lesions Using Dictionary Learning in Feature Space
dc.typeElectronic Thesis or Dissertation

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