{"62123":{"#nid":"62123","#data":{"type":"event","title":"Statistical Methods for Analysis of Diffusion Weighted Magnetic Resonance Imaging","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETITLE: \u003C\/strong\u003EStatistical Methods for Analysis of Diffusion Weighted Magnetic \nResonance Imaging\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ESPEAKER: \u003C\/strong\u003ESofia Olhede\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EABSTRACT:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EHigh angular resolution diffusion imaging data is the observed\ncharacteristic function for the local diffusion of water molecules in\ntissue. This data is used to infer structural information in brain\nimaging.\u0026nbsp; Non-parametric scalar measures are proposed to summarize\nsuch data, and to locally characterize spatial features of the\ndiffusion probability density function (PDF), relying on the geometry\nof the characteristic function.\u0026nbsp; Summary statistics are defined so\nthat their distributions are, to first order, both independent of\nnuisance parameters and analytically tractable.\u0026nbsp; The dominant\ndirection of the diffusion at a spatial location (voxel) is\ndetermined, and a new set of axes are introduced in Fourier space.\nVariation quantified in these axes determines the local spatial\nproperties of the diffusion density.\u0026nbsp; Non-parametric hypothesis tests\nfor determining whether the diffusion is unimodal, isotropic or\nmulti-modal are proposed.\u0026nbsp; More subtle characteristics of white-matter\nmicrostructure, such as the degree of anisotropy of the PDF and\nsymmetry compared with a variety of asymmetric PDF alternatives, may\n\u003Cbr \/\u003Ebe ascertained directly in the Fourier domain without parametric\nassumptions on the form of the diffusion~PDF.\u0026nbsp; We simulate a set of\ndiffusion processes and characterize their local properties using the\nnewly introduced summaries.\u0026nbsp; We show how complex white-matter\n\u003Cbr \/\u003Estructures across multiple voxels exhibit clear ellipsoidal and\nasymmetric structure in simulation, and assess the performance of the\nstatistics in clinically-acquired magnetic resonance imaging data.\u0026nbsp;\nJoint work with Brandon Whitcher, GSK.\n\u003Cbr \/\u003E\n\u003Cbr \/\u003EBIO: Sofia C. Olhede was awarded the M.Sci. and Ph.D. degrees in\nmathematics from Imperial College London, London, U.K., in 2000 and 2003,\nrespectively. She was a Lecturer (2002\ufffd2006) and Senior Lecturer\n(2006\ufffd2007) with the Mathematics Department, Imperial College London. In\n2007, she joined the Department of Statistical Science, University College\n\u003Cbr \/\u003ELondon, where she is Pearson Professor of Statistics and Honorary\nProfessor of Computer Science. Her research interests include the analysis\nof nonstationary time series, inhomogeneous random fields and applications\nin geoscience, medical imaging and oceanography. Prof. Olhede is an\nAssociate Editor of the Journal of the Royal Statistical Society, Series B\n(Statistical Methodology) and of the IEEE Transactions on Signal\n\u003Cbr \/\u003EProcessing. She is a member of the Programme Committee of the\nInternational\nCentre for Mathematical Sciences, and is an Isaac Newton Institute\nCorrespondent.\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Statistical Methods for Analysis of Diffusion Weighted Magnetic Resonance Imaging"}],"uid":"27187","created_gmt":"2010-10-13 10:30:56","changed_gmt":"2016-10-08 01:53:12","author":"Anita Race","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2010-10-14T12:00:00-04:00","event_time_end":"2010-10-14T13:00:00-04:00","event_time_end_last":"2010-10-14T13:00:00-04:00","gmt_time_start":"2010-10-14 16:00:00","gmt_time_end":"2010-10-14 17:00:00","gmt_time_end_last":"2010-10-14 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}