|
|
|
|
LEADER |
03994nam a22005055i 4500 |
001 |
978-3-540-34767-5 |
003 |
DE-He213 |
005 |
20151029231353.0 |
007 |
cr nn 008mamaa |
008 |
100301s2006 gw | s |||| 0|eng d |
020 |
|
|
|a 9783540347675
|9 978-3-540-34767-5
|
024 |
7 |
|
|a 10.1007/978-3-540-34767-5
|2 doi
|
040 |
|
|
|d GrThAP
|
050 |
|
4 |
|a TA342-343
|
072 |
|
7 |
|a PBWH
|2 bicssc
|
072 |
|
7 |
|a TBJ
|2 bicssc
|
072 |
|
7 |
|a MAT003000
|2 bisacsh
|
072 |
|
7 |
|a TEC009060
|2 bisacsh
|
082 |
0 |
4 |
|a 003.3
|2 23
|
245 |
1 |
0 |
|a Mathematical Models for Registration and Applications to Medical Imaging
|h [electronic resource] /
|c edited by Otmar Scherzer.
|
264 |
|
1 |
|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg,
|c 2006.
|
300 |
|
|
|a X, 191 p. 54 illus., 12 illus. in color.
|b online resource.
|
336 |
|
|
|a text
|b txt
|2 rdacontent
|
337 |
|
|
|a computer
|b c
|2 rdamedia
|
338 |
|
|
|a online resource
|b cr
|2 rdacarrier
|
347 |
|
|
|a text file
|b PDF
|2 rda
|
490 |
1 |
|
|a Mathematics in industry,
|x 1612-3956 ;
|v 10
|
505 |
0 |
|
|a Numerical 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 |
|
|
|a Image 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 |
|a Mathematics.
|
650 |
|
0 |
|a Radiology.
|
650 |
|
0 |
|a Computer graphics.
|
650 |
|
0 |
|a Mathematical models.
|
650 |
1 |
4 |
|a Mathematics.
|
650 |
2 |
4 |
|a Mathematical Modeling and Industrial Mathematics.
|
650 |
2 |
4 |
|a Computer Imaging, Vision, Pattern Recognition and Graphics.
|
650 |
2 |
4 |
|a Imaging / Radiology.
|
700 |
1 |
|
|a Scherzer, Otmar.
|e editor.
|
710 |
2 |
|
|a SpringerLink (Online service)
|
773 |
0 |
|
|t Springer eBooks
|
776 |
0 |
8 |
|i Printed edition:
|z 9783540250296
|
830 |
|
0 |
|a Mathematics in industry,
|x 1612-3956 ;
|v 10
|
856 |
4 |
0 |
|u http://dx.doi.org/10.1007/978-3-540-34767-5
|z Full Text via HEAL-Link
|
912 |
|
|
|a ZDB-2-SMA
|
950 |
|
|
|a Mathematics and Statistics (Springer-11649)
|