000			04272cam a2200685Ia 4500
001			ocn871224295
003			OCoLC
005			20171031095653.0
006			m o d
007			cr cnu---unuuu
008			140301s2014 nju ob 001 0 eng d
020			_a9781118760932 _q(electronic bk.)
020			_a111876093X _q(electronic bk.)
020			_a9781118760895 _q(electronic bk.)
020			_a1118760891 _q(electronic bk.)
020			_a9781118760949 _q(electronic bk.)
020			_a1118760948 _q(electronic bk.)
020			_z9781848214743 _q(hbk.)
020			_z184821474X _q(hbk.)
029	1		_aCHBIS _b010442005
029	1		_aCHVBK _b334092795
029	1		_aDEBBG _bBV043396571
029	1		_aDEBBG _bBV043607762
029	1		_aDEBSZ _b405661800
029	1		_aNZ1 _b15497408
029	1		_aNZ1 _b15906667
035			_a(OCoLC)871224295 _z(OCoLC)871318314 _z(OCoLC)876043676
040			_aEBLCP _beng _epn _cEBLCP _dOCLCQ _dIDEBK _dN$T _dDG1 _dCUS _dYDXCP _dDEBSZ _dOCLCA _dOCLCQ _dUA@ _dE7B _dCOO _dDEBBG _dOCLCQ
049			_aMAIN
050		4	_aT174.7
072		7	_aTEC _x009000 _2bisacsh
072		7	_aTEC _x035000 _2bisacsh
082	0	4	_a620.5 _222
100	1		_aTing, Michael _c(Software engineer)
245	1	0	_aMolecular Imaging in Nano MRI / _cMichael Ting. _h[electronic resource]
260			_aLondon, U.K. : _bISTE ; _aHoboken, N.J. : _bWiley, _c2014.
300			_a1 online resource (x, 77 pages).
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
490	1		_aFocus series
504			_aIncludes bibliographical references and index.
505	0		_aCover; 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.
505	8		_a3.3. 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.
520			_aThe 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.
588	0		_aOnline resource; title from PDF title page (Wiley, viewed April 4, 2014).
650		0	_aMagnetic resonance imaging _xComputer programs.
650		0	_aNanoscience.
650		0	_aNuclear magnetic resonance _xComputer programs.
650		4	_aMagnetic resonance imaging _xComputer programs.
650		4	_aNanoscience.
650		4	_aNuclear magnetic resonance _xComputer programs.
650		7	_aTECHNOLOGY & ENGINEERING _xEngineering (General) _2bisacsh
650		7	_aTECHNOLOGY & ENGINEERING _xReference. _2bisacsh
655		4	_aElectronic books.
776	0	8	_iPrint version: _aTing, Michael. _tMolecular imaging in nano MRI. _dLondon, U.K : ISTE ; Hoboken, N.J. : Wiley, 2014 _z9781848214743 _w(OCoLC)859185634
830		0	_aFocus nanoscience and nanotechnology series.
856	4	0	_uhttp://onlinelibrary.wiley.com/book/10.1002/9781118760949 _zWiley Online Library
942			_2ddc _cBK
999			_c207294 _d207294