Browsing by Author "Ye, Yangbo"
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- Development and Applications of Interior Tomography - Multi-source Interior Tomography for Ultrafast PerformanceWang, Ge; Ritman, Erik; Ye, Yangbo; Katsevich, Alexander; Yu, Hengyong; Cao, Guohua; Zhou, Otto (2010-04-05)Conventional tomography allows excellent reconstruction of an object from non-truncated projections. The long-standing interior problem is to reconstruct an interior ROI accurately only from local projection segments. Interior tomography solves the interior problem with practical knowledge such as a known sub-region or a sparsity model using compressive sensing. Advantages of interior tomography include radiation dose reduction (no x-rays go outside an ROI), scattering artifact suppression (no cross-talk from radiation outside the ROI), image quality improvement (with the novel reconstruction approach), large object handling (measurement can be truncated in any direction), and ultrafast imaging performance (with multiple source detector chains tightly integrated targeting the ROI).
- Exact Interior Reconstruction from Truncated Limited-Angle Projection DataYe, Yangbo; Yu, Hengyong; Wang, Ge (Hindawi, 2008-05-06)Using filtered backprojection (FBP) and an analytic continuation approach, we prove that exact interior reconstruction is possible and unique from truncated limited-angle projection data, if we assume a prior knowledge on a subregion or subvolume within an object to be reconstructed. Our results show that (i) the interior region-of-interest (ROI) problem and interior volume-of-interest (VOI) problem can be exactly reconstructed from a limited-angle scan of the ROI/VOI and a 180 degree PI-scan of the subregion or subvolume and (ii) the whole object function can be exactly reconstructed from nontruncated projections from a limited-angle scan. These results improve the classical theory of Hamaker et al. (1980).
- Exact Interior Reconstruction with Cone-Beam CTYe, Yangbo; Yu, Hengyong; Wang, Ge (Hindawi, 2008-01-23)Using the backprojection filtration (BPF) and filtered backprojection (FBP) approaches, respectively, we prove that with cone-beam CT the interior problem can be exactly solved by analytic continuation. The prior knowledge we assume is that a volume of interest (VOI) in an object to be reconstructed is known in a subregion of the VOI. Our derivations are based on the so-called generalized PI-segment (chord). The available projection onto convex set (POCS) algorithm and singular value decomposition (SVD) method can be applied to perform the exact interior reconstruction. These results have many implications in the CT field and can be extended to other tomographic modalities, such as SPECT/PET, MRI.
- Gel'fand-Graev's Reconstruction Formula in the 3D Real Space - a Framework towards a General Interior Tomography TheoryYe, Yangbo; Yu, Hengyong; Wang, Ge (2010-05-31)In [1-4], I. M. Gel'fand and M. I. Graev proposed inversion formulas for x-ray transforms in different spaces. In particular, Gel’fand-Graev’s inversion formula [1] is a fundamental relationship linking projection data to the Hilbert transform of an image to be reconstructed. This finding was re-discovered in the CT field; see [5-9]. It has wide applications, including local reconstruction [10-11], backprojection filtration (BPF) [12], interior tomography [13-17], and limited-angle tomography [18]. For a survey, see [19, 20]. Despite its high information density, Gel’fand-Graev’s inversion formula [1] was cast in high dimensions and specialized terms, and difficult to follow for a well-trained engineer. In this poster, we represent this formula and its proof for the 1D x-ray transform in a 3D real space for easy access and further extension.
- A General Local Reconstruction Approach Based on a Truncated Hilbert TransformYe, Yangbo; Yu, Hengyong; Wei, Yuchuan; Wang, Ge (Hindawi, 2007-06-17)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.
- Interior tomography and instant tomography by reconstruction from truncated limited-angle projection data(United States Patent and Trademark Office, 2010-04-13)A system and method for tomographic image reconstruction using truncated limited-angle projection data that allows exact interior reconstruction (interior tomography) of a region of interest (ROI) based on the linear attenuation coefficient distribution of a subregion within the ROI, thereby improving image quality while reducing radiation dosage. In addition, the method includes parallel interior tomography using multiple sources beamed at multiple angles through an ROI and that enables higher temporal resolution.