Current Issue : January - March Volume : 2013 Issue Number : 1 Articles : 5 Articles
Statistical iterative methods are a widely used method of image reconstruction in emission tomography. Traditionally, the image\r\nspace is modelled as a combination of cubic voxels as a matter of simplicity. After reconstruction, images are routinely filtered to\r\nreduce statistical noise at the cost of spatial resolution degradation. An alternative to produce lower noise during reconstruction\r\nis to model the image space with spherical basis functions. These basis functions overlap in space producing a significantly large\r\nnumber of non-zero elements in the system response matrix (SRM) to store, which additionally leads to long reconstruction times.\r\nThese two problems are partly overcome by exploiting spherical symmetries, although computation time is still slower compared\r\nto non-overlapping basis functions. In this work, we have implemented the reconstruction algorithm using Graphical Processing\r\nUnit (GPU) technology for speed and a precomputedMonte-Carlo-calculated SRM for accuracy. The reconstruction time achieved\r\nusing spherical basis functions on a GPU was 4.3 times faster than the Central Processing Unit (CPU) and 2.5 times faster than\r\na CPU-multi-core parallel implementation using eight cores. Overwriting hazards are minimized by combining a random line of\r\nresponse ordering and constrained atomic writing. Small differences in image quality were observed between implementations....
Microwave approaches to breast imaging include the measurement of signals transmitted through and reflected from the\r\nbreast. Prototype systems typically feature sensors separated from the breast, resulting in measurements that include the effects\r\nof the environment and system. To gain insight into transmission of microwave signals through the breast, a system that\r\nplaces sensors in direct contact with the breast is proposed. The system also includes a lossy immersion medium that enables\r\nmeasurement of the signal passing through the breast while significantly attenuating signals traveling along other paths. Collecting\r\nmeasurements at different separations between sensors also provides the opportunity to estimate the average electrical properties\r\nof the breast tissues. After validation through simulations and measurements, a study of 10 volunteers was performed. Results\r\nindicate symmetry between the right and left breast and demonstrate differences in attenuation, maximum frequency for reliable\r\nmeasurement, and average properties that likely relate to variations in breast composition....
Microwave imaging for breast cancer detection has been of significant interest for the last two decades. Recent studies focus on\r\nsolving the imaging problem using an inverse scattering approach. Efforts have mainly been focused on the development of the\r\ninverse scattering algorithms, experimental setup, antenna design and clinical trials. However, the success of microwave breast\r\nimaging also heavily relies on the quality of the forward data such that the tumor inside the breast volume is well illuminated. In\r\nthis work, a numerical study of the forward scattering data is conducted. The scattering behavior of simple breast models under\r\ndifferent polarization states and aspect angles of illumination are considered. Numerical results have demonstrated that better data\r\ncontrast could be obtained when the breast volume is illuminated using cross-polarized components in linear polarization basis\r\nor the copolarized components in the circular polarization basis....
Intensity standardization in MRI aims at correcting scanner-dependent intensity variations. Existing simple and robust techniques\r\naim at matching the input image histogram onto a standard, while we think that standardization should aim at matching spatially\r\ncorresponding tissue intensities. In this study, we present a novel automatic technique, called STI for STandardization of Intensities,\r\nwhich not only shares the simplicity and robustness of histogram-matching techniques, but also incorporates tissue spatial\r\nintensity information. STI uses joint intensity histograms to determine intensity correspondence in each tissue between the input\r\nand standard images.We compared STI to an existing histogram-matching technique on two multicentric datasets, Pilot E-ADNI\r\nand ADNI, by measuring the intensity error with respect to the standard image after performing nonlinear registration. The Pilot\r\nE-ADNI dataset consisted in 3 subjects each scanned in 7 different sites. The ADNI dataset consisted in 795 subjects scanned in\r\nmore than 50 different sites. STI was superior to the histogram-matching technique, showing significantly better intensity matching\r\nfor the brain white matter with respect to the standard image....
Current clinical breast imaging modalities include ultrasound, magnetic resonance (MR) imaging, and the ubiquitous X-ray\r\nmammography. Microwave imaging, which takes advantage of differing electromagnetic properties to obtain image contrast,\r\nshows potential as a complementary imaging technique. As an emerging modality, interpretation of 3D microwave images poses a\r\nsignificant challenge. MR images are often used to assist in this task, and X-ray mammograms are readily available. However, X-ray\r\nmammograms provide 2D images of a breast under compression, resulting in significant geometric distortion. This paper presents\r\na method to estimate the 3D shape of the breast and locations of regions of interest from standard clinical mammograms. The\r\ntechnique was developed using MR images as the reference 3D shape with the future intention of using microwave images. Twelve\r\nbreast shapes were estimated and compared to ground truth MR images, resulting in a skin surface estimation accurate to within\r\nan average Euclidean distance of 10 mm. The 3D locations of regions of interest were estimated to be within the same clinical area\r\nof the breast as corresponding regions seen on MR imaging. These results encourage investigation into the use of mammography\r\nas a source of information to assist with microwave image interpretation as well as validation of microwave imaging techniques....
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