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008			160712s2016 gw | s |||| 0|eng d
020			_a9783319399348
040			_aES-MaUEC
050		4	_aTK5102.9 _bA334 2016
082	0	4	_a005.55
100	1		_aAja-Fernández, Santiago. _946918
245	1	0	_aStatistical Analysis of Noise in MRI : _bModeling, Filtering and Estimation _cby Santiago Aja-Fernández, Gonzalo Vegas-Sánchez-Ferrero
260			_aCham _bSpringer International Publishing _c2016
300			_a1 recurso en línea (XXI, 327 páginas) _b172 ilustraciones, 99 ilustraciones en color
336			_aTexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
505	0		_aThe Problem of Noise in MRI -- Part I: Noise Models and the Noise Analysis Problem -- Acquisition and Reconstruction of Magnetic Resonance Imaging -- Statistical Noise Models for MRI -- Noise Analysis in MRI: Overview -- Noise Filtering in MRI -- Part II: Noise Analysis in Non-Accelerated Acquisitions -- Noise Estimation in the Complex Domain -- Noise Estimation in Single-Coil MR Data -- Noise Estimation in Multiple-Coil MR Data -- Parametric Noise Analysis from Correlated Multiple-Coil MR Data -- Part III: Noise Estimators in pMRI -- Parametric Noise Analysis in Parallel MRI -- Blind Estimation of Non-Stationary Noise in MRI -- Appendix A: Probability Distributions and Combination of Random Variables -- Appendix B: Variance Stabilizing Transformation -- Appendix C: Data Sets Used in the Experiments.
520	3		_aThis unique text/reference presents a comprehensive review of methods for modeling signal and noise in magnetic resonance imaging (MRI), providing a systematic study, classifying and comparing the numerous and varied estimation and filtering techniques drawn from more than ten years of research in this area. Topics and features: Provides a complete framework for the modeling and analysis of noise in MRI, considering different modalities and acquisition techniques Describes noise and signal estimation for MRI from a statistical signal processing perspective Surveys the different methods to remove noise in MRI acquisitions, under different approaches and from a practical point of view Reviews different techniques for estimating noise from MRI data in single- and multiple-coil systems for fully sampled acquisitions Examines the issue of noise estimation when accelerated acquisitions are considered, and parallel imaging methods are used to reconstruct the signal Includes appendices covering probability density functions, combinations of random variables used to derive estimators, and useful MRI datasets This practically-focused work serves as a reference manual for researchers dealing with signal processing in MRI acquisitions, and is also suitable as a textbook for postgraduate students in engineering with an interest in medical image processing. Dr. Santiago Aja-Fernández is an Associate Professor at the School of Telecommunications of the University of Valladolid, Spain. His other publications include the Springer title Tensors in Image Processing and Computer Vision. Dr. Gonzalo Vegas-Sánchez-Ferrero is a Research Fellow at Brigham and Women�s Hospital, and in the Applied Chest Imaging Laboratory of Harvard Medical School, Boston, MA, USA.
710	2		_aSpringerLink (Online service) _0Local _9106996
942			_2lcc _cLE
988			_aEBOOK, asignarmaterias , EBSPRINGER
650		7	_aEstadística matemática _0comprobar BNE19900966258 _2embne _9138936
650	0	7	_aSimulación por ordenador _0 _2embne _9147541
700	1		_aVegas-Sánchez-Ferrero, Gonzalo. _999662 _0Local
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://link.springer.com/book/10.1007/978-3-319-39934-8 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
901			_ai9783319399348
907			_a.b12954408 _b10-10-17 _c21-11-16
998			_am _a_alco _a_vill _b - - _cm _dz _e- _feng _ggw _h0
945			_aTK5102.9 A334 2016 EB _g1 _ieBOOK _j0 _lmae _o- _pEUR0.00 _q- _r- _sb _t15 _u0 _v0 _w0 _x0 _y.i11596788 _z06-04-17
999			_c86162 _d86162 _x1