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Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/106082

Improved image quality in pinhole SPECT by accurate modeling of the point spread function in low magnification systems

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It is well-known that in pinhole SPECT (single-photon-emission computed tomography), iterative reconstruction methods including accurate estimations of the system response matrix can lead to submillimeter spatial resolution. There are two different methods for obtaining the system response matrix: those that model the system analytically using an approach including an experimental characterization of the detector response, and those that make use of Monte Carlo simulations. Methods based on analytical approaches are faster and handle the statistical noise better than those based on Monte Carlo simulations, but they require tedious experimental measurements of the detector response. One suggested approach for avoiding an experimental characterization, circumventing the problem of statistical noise introduced by Monte Carlo simulations, is to perform an analytical computation of the system response matrix combined with a Monte Carlo characterization of the detector response. Our findings showed that this approach can achieve high spatial resolution similar to that obtained when the system response matrix computation includes an experimental characterization. Furthermore, we have shown that using simulated detector responses has the advantage of yielding a precise estimate of the shift between the point of entry of the photon beam into the detector and the point of interaction inside the detector. Considering this, it was possible to slightly improve the spatial resolution in the edge of the field of view.

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PINO SORROCHE, Francisco, et al. Improved image quality in pinhole SPECT by accurate modeling of the point spread function in low magnification systems. Medical Physics. 2015. Vol. 42, num. 2, pags. 703-714. ISSN 0094-2405. [consulted: 20 of August of 2026]. Available at: https://hdl.handle.net/2445/106082

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