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001 978-3-540-34767-5
003 DE-He213
005 20181204131311.0
007 cr nn 008mamaa
008 100301s2006 gw | s |||| 0|eng d
020 _a9783540347675
_9978-3-540-34767-5
024 7 _a10.1007/978-3-540-34767-5
_2doi
040 _aISI Library, Kolkata
050 4 _aTA342-343
072 7 _aPBWH
_2bicssc
072 7 _aMAT003000
_2bisacsh
072 7 _aPBWH
_2thema
072 7 _aTBJ
_2thema
082 0 4 _a003.3
_223
245 1 0 _aMathematical Models for Registration and Applications to Medical Imaging
_h[electronic resource] /
_cedited by Otmar Scherzer.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2006.
300 _aX, 191 p. 54 illus., 12 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aThe European Consortium for Mathematics in Industry ;
_v10
505 0 _aNumerical Methods -- A Generalized Image Registration Framework using Incomplete Image Information – with Applications to Lesion Mapping -- Medical Image Registration and Interpolation by Optical Flow with Maximal Rigidity -- Registration of Histological Serial Sectionings -- Computational Methods for Nonlinear Image Registration -- A Survey on Variational Optic Flow Methods for Small Displacements -- Applications -- Fast Image Matching for Generation of Panorama Ultrasound -- Inpainting of Movies Using Optical Flow -- Medical Applications -- Multimodality Registration in Daily Clinical Practice -- Colour Images.
520 _aImage registration is an emerging topic in image processing with many applications in medical imaging, picture and movie processing. The classical problem of image registration is concerned with ?nding an appropriate transformation between two data sets. This fuzzy de?nition of registration requires a mathematical modeling and in particular a mathematical speci?cation of the terms appropriate transformations and correlation between data sets. Depending on the type of application, typically Euler, rigid, plastic, elastic deformations are considered. The variety of similarity p measures ranges from a simpleL distance between the pixel values of the data to mutual information or entropy distances. This goal of this book is to highlight by some experts in industry and medicine relevant and emerging image registration applications and to show new emerging mathematical technologies in these areas. Currently, many registration application are solved based on variational prin- ple requiring sophisticated analysis, such as calculus of variations and the theory of partial differential equations, to name but a few. Due to the numerical compl- ity of registration problems ef?cient numerical realization are required. Concepts like multi-level solver for partial differential equations, non-convex optimization, and so on play an important role. Mathematical and numerical issues in the area of registration are discussed by some of the experts in this volume. Moreover, the importance of registration for industry and medical imaging is discussed from a medical doctor and from a manufacturer point of view.
650 0 _aComputer vision.
650 0 _aRadiology, Medical.
650 1 4 _aMathematical Modeling and Industrial Mathematics.
_0http://scigraph.springernature.com/things/product-market-codes/M14068
650 2 4 _aComputer Imaging, Vision, Pattern Recognition and Graphics.
_0http://scigraph.springernature.com/things/product-market-codes/I22005
650 2 4 _aImaging / Radiology.
_0http://scigraph.springernature.com/things/product-market-codes/H29005
700 1 _aScherzer, Otmar.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783642064036
776 0 8 _iPrinted edition:
_z9783540808008
776 0 8 _iPrinted edition:
_z9783540250296
830 0 _aThe European Consortium for Mathematics in Industry ;
_v10
856 4 0 _uhttps://doi.org/10.1007/978-3-540-34767-5
912 _aZDB-2-SMA
942 _cEB
950 _aMathematics and Statistics (Springer-11649)
999 _c425221
_d425221