database of image Archives — MATLAB Number ONE https://matlab1.com/category/database-of-image/ MATLAB Simulink | Tutorial | Code | Project Tue, 14 Aug 2018 12:47:48 +0000 en-GB hourly 1 https://matlab1.com/wp-content/uploads/2018/08/icon1-100x100.png database of image Archives — MATLAB Number ONE https://matlab1.com/category/database-of-image/ 32 32 Accelerating Parallel Image Reconstruction Using Random Projection https://matlab1.com/accelerating-parallel-image-reconstruction-using-random-projection/ https://matlab1.com/accelerating-parallel-image-reconstruction-using-random-projection/#respond Sun, 26 Nov 2017 19:14:05 +0000 https://matlab1.com/?p=3652 Accelerating Parallel Image Reconstruction Using Random Projection Prologue Random projection has been used for data dimension reduction . The concept of random projection is related to compressed sensing , a topic that has attracted many attentions recently. By projecting the data to lower dimensions using some random matrices with certain properties (e.g., the restricted isometry […]

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]]> https://matlab1.com/accelerating-parallel-image-reconstruction-using-random-projection/feed/ 0 Compressed Sensing MRI https://matlab1.com/compressed-sensing-mri/ https://matlab1.com/compressed-sensing-mri/#respond Sun, 26 Nov 2017 18:40:51 +0000 https://matlab1.com/?p=3644 Compressed Sensing MRI Parallel imaging has led to revolutionary progress in the field of rapid MRI in the past two decades. However, as discussed in the previous section, the maximum acceleration that can be achieved in parallel imaging is limited by the number and the design of coils, and ultimately by fundamental electrodynamic principles. Compressed […]

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]]> https://matlab1.com/compressed-sensing-mri/feed/ 0 Parallel MRI https://matlab1.com/parallel-mri/ https://matlab1.com/parallel-mri/#respond Sun, 26 Nov 2017 18:18:53 +0000 https://matlab1.com/?p=3633 The Need for Speed in MRI MR imaging speed is of critical importance in many clinical applications. However, the imaging speed with which gradient-encoded MR images can be acquired is fundamentally limited by the sequential nature of gradient-based MR acquisitions, in which only one k-space line can be acquired per unit time. In order to […]

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]]> https://matlab1.com/parallel-mri/feed/ 0 MR Image Reconstruction https://matlab1.com/mr-image-reconstruction/ https://matlab1.com/mr-image-reconstruction/#respond Sun, 26 Nov 2017 17:58:03 +0000 https://matlab1.com/?p=3621 MR Image Reconstruction As shown in Eq. (2.11), MR signal from a two-dimensional plane is a spatial integration of the spin density against the sinusoidal spatial modulation generated by encoding gradients. In other words, the MR signal comprises projections of the spin density against Nx×Ny distinct functions, in which a total number of Nx×Ny measurements […]

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]]> https://matlab1.com/mr-image-reconstruction/feed/ 0 Spatial Encoding and k-Space Formalism https://matlab1.com/spatial-encoding-k-space-formalism/ https://matlab1.com/spatial-encoding-k-space-formalism/#respond Sun, 26 Nov 2017 17:25:37 +0000 https://matlab1.com/?p=3613 Spatial Encoding and k-Space Formalism Following slice selection, the in-plane spatial information now can be further encoded with two additional gradients, known as frequency-encoding and phase-encoding gradients. In 2D imaging, the received MRI signal can be described as Here m(x, y) represents the spin density in the 2D object to be imaged. Considering only the […]

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]]> https://matlab1.com/spatial-encoding-k-space-formalism/feed/ 0 MRI Signal https://matlab1.com/mri-signal/ https://matlab1.com/mri-signal/#respond Sun, 26 Nov 2017 17:15:24 +0000 https://matlab1.com/?p=3601 MRI Signal NMR Phenomenon The physical phenomenon behind MRI is nuclear magnetic resonance (NMR), which was first discovered in the 1940s. An atomic nucleus with an odd number of protons possesses an angular momentum J called spin, which generates a tiny magnetic moment μ. The magnetic moment is directly proportional to the angular moment as […]

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]]> https://matlab1.com/mri-signal/feed/ 0 Magnetic Resonance Imaging https://matlab1.com/magnetic-resonance-imaging/ https://matlab1.com/magnetic-resonance-imaging/#respond Sun, 26 Nov 2017 16:48:01 +0000 https://matlab1.com/?p=3598 Magnetic Resonance Imaging Magnetic Resonance Imaging (MRI) is a non-invasive and powerful imaging modality, with a broad range of applications in both clinical diagnosis and basic scientific research. Comparing to other medical imaging modalities, MRI does not use ionizing radiation and provides superior soft-tissue characterization with high resolution and flexible image contrast parameters. Moreover, MRI […]

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]]> https://matlab1.com/magnetic-resonance-imaging/feed/ 0 Bayesian Statistics https://matlab1.com/bayesian-statistics/ https://matlab1.com/bayesian-statistics/#respond Sat, 25 Nov 2017 17:43:34 +0000 https://matlab1.com/?p=3479 Bayesian Statistics A hypothesis is nothing more than a claim or premise that one is interested in verifying. In imaging and spectroscopy, one example is that at a certain location in the eld of view, the hypothesis is that a spectrum is present. Another hypothesis is that the mean value of the signal is some […]

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]]> https://matlab1.com/bayesian-statistics/feed/ 0 Principal Component Analysis https://matlab1.com/principal-component-analysis/ https://matlab1.com/principal-component-analysis/#respond Sat, 25 Nov 2017 17:21:58 +0000 https://matlab1.com/?p=3471 Principal Component Analysis Principal component analysis (PCA) is a dimensionality reduction technique that attempts to recast a dataset in a manner that nds correlations in data that may not be evident in their native basis and creates a set of basis vectors in which the data has a low dimensional representation. PCA works by producing […]

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]]> https://matlab1.com/principal-component-analysis/feed/ 0 Practical Considerations in Computational Sensing https://matlab1.com/practical-considerations-computational-sensing/ https://matlab1.com/practical-considerations-computational-sensing/#respond Sat, 25 Nov 2017 17:01:49 +0000 https://matlab1.com/?p=3460 Practical Considerations in Computational Sensing Computational sensing as a eld is continuing to grow at a rapid pace. The number of journal publications related to computational sensing has steadily increased every year since 2008 . There is now a major Optical Society of America (OSA) meeting dedicated to computational sensing  and textbooks dedicated to its study […]

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