TY  - BOOK
AU  - Ting,Michael
TI  - Molecular Imaging in Nano MRI
T2  - Focus series
SN  - 9781118760932
AV  - T174.7 
U1  - 620.5 22
PY  - 2014///
CY  - London, U.K., Hoboken, N.J.
PB  - ISTE, Wiley
KW  - Magnetic resonance imaging
KW  - Computer programs
KW  - Nanoscience
KW  - Nuclear magnetic resonance
KW  - TECHNOLOGY & ENGINEERING
KW  - Engineering (General)
KW  - bisacsh
KW  - Reference
KW  - Electronic books
N1  - Includes bibliographical references and index; Cover; Title page; Contents; Introduction; Chapter 1. Nano MRI; Chapter 2. Sparse Image Reconstruction; 2.1. Introduction; 2.2. Problem formulation; 2.3. Validity of the observation model in MRFM; 2.4. Literature review; 2.4.1. Sparse denoising; 2.4.2. Variable selection; 2.4.3. Compressed sensing; 2.5. Reconstruction performance criteria; Chapter 3. Iterative Thresholding Methods; 3.1. Introduction; 3.2. Separation of deconvolution and denoising; 3.2.1. Gaussian noise statistics; 3.2.2. Poisson noise statistics; 3.3. Choice of sparse denoising operator in the case of Gaussian noise statistics3.3.1. Comparison to the projected gradient method; 3.4. Hyperparameter selection; 3.5. MAP estimators using the LAZE image prior; 3.5.1. MAP1; 3.5.2. MAP2; 3.5.3. Comparison of MAP1 versus MAP2; 3.6. Simulation example; 3.7. Future directions; Chapter 4. Hyperparameter Selection Using the SURE Criterion; 4.1. Introduction; 4.2. SURE for the lasso estimator; 4.3. SURE for the hybrid estimator; 4.4. Computational considerations; 4.5. Comparison with other criteria; 4.6. Simulation example
N2  - The authors describe a technique that can visualize the atomic structure of molecules, it is necessary, in terms of the image processing, to consider the reconstruction of sparse images. Many works have leveraged the assumption of sparsity in order to achieve an improved performance that would not otherwise be possible. For nano MRI, the assumption of sparsity is given by default since, at the atomic scale, molecules aresparse structures. This work reviews the latest results on molecular imaging for nano MRI. Sparse image reconstruction methods can be categorized as either non-B
UR  - http://dx.doi.org/10.1002/9781118760949
ER  -