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008			170707s2017 si a ob 001 0 eng d
020			_a9789811046360 _q(electronic bk.)
020			_a9811046360 _q(electronic bk.)
020			_z9789811046353
020			_z9811046352
040			_aN$T _cN$T _dN$T _dEBLCP _dGW5XE _dYDX _dOCLCF _dNJR _dUAB _dESU _dAZU _dUPM _dCOO _dOCLCQ _dMERER _dVT2 _dOCLCQ _dIOG _dES-MaUEC _bspa
050		4	_aRC78.7.D53 _b2017 EB
100	1		_aGunjan, Vinit Kumar, _eautor
245	1	0	_aComputational methods in molecular imaging technologies _cVinit Kumar Gunjan, Fahimuddin Shaik, C. Venkatesh, M. Amarnath.
264		1	_aSingapore _bSpringer _c[2017]
300			_a1 recurso en línea
336			_aTexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_atext file _bPDF
490	0		_aSpringerBriefs in applied sciences and technology. Forensic and medical bioinformatics
500			_aSpringerLink _bSpringer Engineering eBooks 2017 English+International
504			_aIncluye referencias bibliográficas
505	0		_aPreface; Acknowledgements; Contents; About the Authors; Abstract; 1 Introduction; 1.1 Introduction to Medical Imaging; 1.2 Medical Imaging Overview; 1.3 Molecular Imaging and Its Modalities; 1.4 Medical Image Reconstruction; 1.5 Types of Image Reconstruction; 2 Artifacts Correction in MRI Images; 2.1 Existing Methods; 2.1.1 Disadvantages of Ultra-echo Time Imaging (UTE); 2.1.2 Disadvantages of Sweep Imaging with Fourier Transform; 2.1.3 Disadvantages of Water- and Fat-suppressed Proton Projection MRI; 2.1.4 Disadvantages of ZTE Imaging Without Excitation Profile; 2.2 Implemented Method.
505	8		_a2.3 Process Diagram2.4 Model as an Inverse Problem; 2.5 NUFFT Operator; 2.5.1 Features of NUFFT; 2.5.2 Non-uniform FFT Algorithm; 2.6 Quadratic Phase-Modulated RF Pulse Excitation; 2.6.1 Hard RF Phase Modulation; 2.7 Excitation Profile Measurement; 2.8 Pointwise Encoding Time Reduction with Radial Acquisition (PETRA); 2.9 Iterative Partial K-Space Reconstruction; 2.10 Processing of Project; 2.11 Flow Diagram; 3 Spiral Cone-Beam CT Reconstruction; 3.1 CT Reconstruction Using the Medical Phantom Image; 3.1.1 Assessment of Image Quality of the CT Medical Phantom Image Before Reconstruction.
505	8		_a3.1.2 Assesment of the Image Quality of Cone-Beam Phantom After Image Reconstruction3.2 CT Reconstruction of the Hand Section of the Human Body; 3.2.1 Assesment of the Image Quality of CT Hand Section Before Reconstruction; 3.2.2 Assesment of the Image Quality of Cone-Beam CT Hand Section After Reconstruction; 3.3 CT Reconstruction of the Head Section of the Human Body; 3.3.1 Assesment of the Image Quality of the CT Head Section Before Reconstruction; 3.3.2 Assesment of the Image Quality of the Cone-Beam CT Head Section After Reconstruction; 3.4 Quantization of the Artifacts.
505	8		_a3.4.1 Assessment of Image Resolution and Noise Quantization of the Artifacts3.4.1.1 Factors Affecting the Assessment of Image Resolution and Noise Quantization of the Artifacts; 3.4.1.2 Image Quality Metrics; 3.4.1.3 Computational Efficiency Measurement; 4 Visual Quality Improvement of CT Image Reconstruction with Quantitative Measures; 4.1 Existing System; 4.1.1 Background; 4.1.2 Criterion for Filtering Edge Information; 4.2 Proposed Algorithms; 4.2.1 Model Specification; 4.2.2 Boundary-Edge Correspondence; 4.2.3 Local Intensity Clustering Property; 4.2.4 Energy Formulation.
505	8		_a4.2.5 Multiphase Level Set Formulation4.3 Block Diagram; 4.4 Back Projection; 4.5 Filtered Back Projection (FBP) Reconstruction; 4.6 Discrete Direct Back Projection; 4.7 Data Acquisition; 4.8 Iterative Reconstruction Algorithm; 4.9 Histogram Processing; 4.10 Bias Field; 4.11 Experimental Findings; 4.11.1 Assesment of the Image Statistics of Before Image Reconstruction of CT Knee Bone; 4.11.2 Assesment of the Image Statistics of After Image Reconstruction of CT Knee Bone; 4.12 Computational Efficiency Comparison; Bibliography.
520	3		_aThis book highlights the experimental investigations that have been carried out on magnetic resonance imaging and computed tomography (MRI & CT) images using state-of-the-art Computational Image processing techniques, and tabulates the statistical values wherever necessary. In a very simple and straightforward way, it explains how image processing methods are used to improve the quality of medical images and facilitate analysis. It offers a valuable resource for researchers, engineers, medical doctors and bioinformatics experts alike.
650		7	_aBioinformática _2embne _0(OCoLC)fst00871990 _0 _9160489
700	1		_aAmarnath, M., _eautor
700	1		_aShaik, Fahimuddin, _eautor _9100846
700	1		_aVenkatesh, Chethan, _eautor
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=http://link.springer.com/10.1007/978-981-10-4636-0 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
988			_aEBOOK, asignarmaterias, EBSPRINGER_2017D
998			_b02/2018 _dz _e- _zSI
999			_c96305 _d96305 _x1