04181nam 22006375 450 99641827330331620200702071103.03-642-27795-010.1007/978-3-642-27795-5(CKB)3710000000306363(DE-He213)978-3-642-27795-5(PPN)242974546(EXLCZ)99371000000030636320190617d2020 u| 0engurnn|008mamaatxtrdacontentcrdamediacrrdacarrierHandbook of Mathematical Methods in Imaging[electronic resource] /edited by Otmar ScherzerBerlin, Heidelberg :Springer Berlin Heidelberg :Imprint: Springer,2020.1 online resource (XVIII, 455 p. 150 illus.) Introduction -- Part 1: Inverse Problems -- Tomography -- MR DTI -- Hybrid Methods -- Nonlinear Inverse Problems -- EIT -- Scattering -- Sampling Methods -- Expansion Methods -- Regularization Methods for Ill-Posed Problems -- Iterative Solution Methods -- Wave Phenomena -- Seismic -- Radar -- Ultrasound -- Part 2: Signal and Image Processing -- Morphological Image Processing -- Learning, Classification, Data Mining -- Partial Differential Equations -- Variational Methods for Image Analysis -- Level Set Methods Including Fast Marching Methods -- Segmentation -- Registration, Optical Flow -- Duality and Convex Minimization -- Spline, Statistics -- Wavelets -- Fourier Analysis -- Compressed Sensing -- Geometry Processing -- Compression -- Computational Geometry -- Shape Spaces -- PDEs and Variational Methods on Manifold -- References -- Subject Index.The Handbook of Mathematical Methods in Imaging provides a comprehensive treatment of the mathematical techniques used in imaging science. The material is grouped into two central themes, namely, Inverse Problems (Algorithmic Reconstruction) and Signal and Image Processing. Each section within the themes covers applications (modeling), mathematics, numerical methods (using a case example) and open questions. Written by experts in the area, the presentation is mathematically rigorous. The entries are cross-referenced for easy navigation through connected topics. Available in both print and electronic forms, the handbook is enhanced by more than 150 illustrations and an extended bibliography. It will benefit students, scientists and researchers in applied mathematics. Engineers and computer scientists working in imaging will also find this handbook useful.Applied mathematicsEngineering mathematicsOptical data processingSignal processingImage processingSpeech processing systemsNumerical analysisRadiologyApplications of Mathematicshttps://scigraph.springernature.com/ontologies/product-market-codes/M13003Image Processing and Computer Visionhttps://scigraph.springernature.com/ontologies/product-market-codes/I22021Signal, Image and Speech Processinghttps://scigraph.springernature.com/ontologies/product-market-codes/T24051Numerical Analysishttps://scigraph.springernature.com/ontologies/product-market-codes/M14050Imaging / Radiologyhttps://scigraph.springernature.com/ontologies/product-market-codes/H29005Applied mathematics.Engineering mathematics.Optical data processing.Signal processing.Image processing.Speech processing systems.Numerical analysis.Radiology.Applications of Mathematics.Image Processing and Computer Vision.Signal, Image and Speech Processing.Numerical Analysis.Imaging / Radiology.519Scherzer Otmaredthttp://id.loc.gov/vocabulary/relators/edtBOOK996418273303316Handbook of mathematical methods in imaging1520292UNISA