Posts tagged Local Reconstruction
Bharkhada D, Yu H, Shuping G, Carr J, Wang G: Cardiac CT dose reduction using interior reconstruction algorithm with the aorta and vertebra as known information. Journal of Computer Assisted Tomography, 33(3), 338-347, 20090
High x-ray radiation dose is a major public concern with the increasing use of multidetector computed tomography (CT) for diagnosis of cardiovascular diseases. This issue must be effectively addressed by dose-reduction techniques. Recently, our group proved that an internal region of interest (ROI) can be exactly reconstructed solely from localized projections if a small subregion within the ROI is known. In this article, we propose to use attenuation values of the blood in aorta and vertebral bone to serve as the known information for localized cardiac CT. First, we describe a novel interior tomography approach that backprojects differential fan-beam or parallel-beam projections to obtain the Hilbert transform and then reconstructs the original image in an ROI using the iterative projection onto convex sets algorithm. Then, we develop a numerical phantom based on clinical cardiac CT images for simulations. Our results demonstrate that it is feasible to use practical prior information and exactly reconstruct cardiovascular structures only from projection data along x-ray paths through the ROI. Click here for full article….
Wang G, Yu HY, DeMan B: An outlook on x-ray CT research and development. Medical Physics, 35:1051-1064, 20070
Over the past decade, computed tomography (CT) theory, techniques and applications have undergone a rapid development. Since CT is so practical and useful, undoubtedly CT technology will continue advancing biomedical and non-biomedical applications. In this outlook article, we share our opinions on the research and development in this field, emphasizing 12 topics we expect to be critical in the next decade: analytic reconstruction, iterative reconstruction, local/interior reconstruction, flat-panel based CT, dual-source CT, multi-source CT, novel scanning modes, energy-sensitive CT, nano-CT, artifact reduction, modality fusion, and phase-contrast CT. We also sketch several representative biomedical applications. Click here for full article….
Ye Y, Yu H, Wei Y, Wang G: A general local reconstruction approach on a truncated hilbert transfrom. International Journal of Biomedical Imaging 2007:Article ID 63634, 8 pages, 20070
Exact image reconstruction from limited projection data has been a central topic in the computed tomography (CT) field. In this paper, we present a general region-of-interest/volume-of-interest (ROI/VOI) reconstruction approach using a truly truncated Hilbert transform on a line-segment inside a compactly supported object aided by partial knowledge on one or both neighboring intervals of that segment. Our approach and associated new data sufficient condition allows the most flexible ROI/VOI image reconstruction from the minimum account of data in both the fan-beam and cone-beam geometry. We also report primary numerical simulation results to demonstrate the correctness and merits of our finding. Our work has major theoretical potentials and innovative practical applications. Click here for full article….
Zeng K, Zhao S, Farjado L, Wang G: Global low-resolution CT scan regulated tomosynthesis. Journal of CT Theory and Applications 14:63-69, 20050
Tomosynthesis reconstructs a 3D object from a scan consisting of a limited number of projections. Hence, tomosynthesis requires much less radiation dosage as compared to computed tomography (CT). A major problem with tomosynthesis is image artifacts associated with incompleteness of data. In this paper we propose a tomosynthesis approach to achieve higher image quality in a region of interest (ROI) than competing techniques. First, a low-resolution global CT scan is acquired. Then, a high-resolution local scan is performed with respect to the ROI. finally, images, of the ROI are reconstructed from these two datasets. Our numerical simulation results show that images of the ROI obtained by our approach are significantly better than the counterparts without using the global scan information. Click here for full article….
Wang G, Vannier MW, Cheng PC: Iterative X-ray cone-beam tomography for metal artifact reduction and local region reconstruction. Microscopy and Microanalysis 5:58-65, 19990
X-ray cone-beam reconstruction from incomplete projection data has important practical applications, especially in microtomography. We developed expectation maximization (EM)-type and algebraic reconstruction technique (ART)-type iterative cone-beam reconstruction algorithms for metal artifact reduction and local reconstruction from truncated data. These iterative algorithms are adapted from the emission computerized tomography (CT) EM formula and the ART. A key step in our iterative algorithms is introduction of a projection mask and computation of a 3-D spatially varying relaxation factor that allows compensation for beam divergence and data incompleteness. The algorithms are simulated with projection data synthesized from mathematical phantoms. In simulation, the EM-type and ART-type iterative algorithms are demonstrated to be effective for metal artifact reduction and local region reconstruction. They perform similarly in terms of visual quality, image noise, and discrepancy between measured and reprojected data. The EM-type and ART-type iterative cone-beam reconstruction algorithms have potential for metal artifact reduction and local region reconstruction in X-ray CT. Click here for full article….