Current Issue : October - December Volume : 2013 Issue Number : 4 Articles : 5 Articles
Undersampling ??-space data is an efficient way to speed up the magnetic resonance imaging (MRI) process. As a newly developed\r\nmathematical framework of signal sampling and recovery, compressed sensing (CS) allows signal acquisition using fewer samples\r\nthan what is specified by Nyquist-Shannon sampling theorem whenever the signal is sparse. As a result, CS has great potential in\r\nreducing data acquisition time in MRI. In traditional compressed sensing MRI methods, an image is reconstructed by enforcing\r\nits sparse representation with respect to a basis, usually wavelet transform or total variation. In this paper, we propose an improved\r\ncompressed sensing-based reconstruction method using the complex double-density dual-tree discrete wavelet transform. Our\r\nexperiments demonstrate that this method can reduce aliasing artifacts and achieve higher peak signal-to-noise ratio (PSNR) and\r\nstructural similarity (SSIM) index....
This paper presents a novel processing technique which can be applied to corneal in vivo images obtained with optical coherence\r\ntomograms across the central meridian of the cornea. The method allows to estimate the thickness of the corneal sublayers\r\n(Epithelium, Bowman�s layer, Stroma, Endothelium, and whole corneal thickness) at any location, including the center and the\r\nmidperiphery, on both nasal and temporal sides. The analysis is carried out on both the pixel and subpixel scales to reduce\r\nthe uncertainty in thickness estimations. This technique allows quick and noninvasive assessment of patients. As an example of\r\napplication and validation, we present the results obtained from the analysis of 52 healthy subjects, each with 3 scans per eye, for\r\na total of more than 300 images. Particular attention has been paid to the statistical interpretation of the obtained results to find a\r\nrepresentative assessment of each sublayer�s thickness....
Tetrahedron beamcomputed tomography (TBCT) performs volumetric imaging using a stack of fan beams generated by amultiple\r\npixel X-ray source.While the TBCT system was designed to overcome the scatter and detector issues faced by cone beamcomputed\r\ntomography (CBCT), it still suffers the same large cone angle artifacts as CBCT due to the use of approximate reconstruction\r\nalgorithms. It has been shown that iterative reconstruction algorithms are better able to model irregular system geometries and\r\nthat algebraic iterative algorithms in particular have been able to reduce cone artifacts appearing at large cone angles. In this paper,\r\nthe SART algorithm is modified for the use with the different TBCT geometries and is tested using both simulated projection data\r\nand data acquired using the TBCT benchtop system.Themodified SART reconstruction algorithms were able tomitigate the effects\r\nof using data generated at large cone angles and were also able to reconstruct CT images without the introduction of artifacts due\r\nto either the longitudinal or transverse truncation in the data sets. Algebraic iterative reconstruction can be especially useful for\r\ndual-source dual-detector TBCT, wherein the cone angle is the largest in the center of the field of view....
TheFinite ElementMethod is a well-known technique, being extensively applied in different areas. Studies using the Finite Element\r\nMethod (FEM) are targeted to improve cardiac ablation procedures. For such simulations, the finite elementmeshes should consider\r\nthe size and histological features of the target structures.However, it is possible to verify that some methods or tools used to generate\r\nmeshes of human body structures are still limited, due to nondetailed models, nontrivial preprocessing, or mainly limitation in the\r\nuse condition. In this paper, alternatives are demonstrated to solid modeling and automatic generation of highly refined tetrahedral\r\nmeshes, with quality compatible with other studies focused on mesh generation.The innovations presented here are strategies to\r\nintegrate Open Source Software (OSS). The chosen techniques and strategies are presented and discussed, considering cardiac\r\nstructures as a first application context....
Long acquisition times lead to image artifacts in thoracic C-arm CT. Motion blur caused by respiratory motion leads to decreased\r\nimage quality in many clinical applications.We introduce an image-based method to estimate and compensate respiratory motion\r\nin C-arm CT based on diaphragm motion. In order to estimate respiratory motion, we track the contour of the diaphragm in the\r\nprojection image sequence. Using a motion corrected triangulation approach on the diaphragm vertex, we are able to estimate a\r\nmotion signal.The estimated motion signal is used to compensate for respiratory motion in the target region, for example, heart\r\nor lungs. First, we evaluated our approach in a simulation study using XCAT. As ground truth data was available, a quantitative\r\nevaluation was performed.We observed an improvement of about 14%using the structural similarity index. In a real phantomstudy,\r\nusing the artiCHEST phantom, we investigated the visibility of bronchial tubes in a porcine lung. Compared to an uncompensated\r\nscan, the visibility of bronchial structures is improved drastically. Preliminary results indicate that this kind ofmotion compensation\r\ncan deliver a first step in reconstruction image quality improvement. Compared to ground truth data, image quality is still\r\nconsiderably reduced....
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