Adaptive Angular Sampling for SPECT Imaging

This paper presents an analytical approach for performing adaptive angular sampling in single photon emission computed tomography (SPECT) imaging. It allows for a rapid determination of the optimum sampling strategy that minimizes image variance in regions-of-interest (ROIs). The proposed method con...

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Publié dans:IEEE transactions on nuclear science. - 1988. - 58(2011), 5 vom: 01. Okt., Seite 2205-2218
Auteur principal: Li, Nan (Auteur)
Autres auteurs: Meng, Ling-Jian
Format: Article
Langue:English
Publié: 2011
Accès à la collection:IEEE transactions on nuclear science
Sujets:Journal Article Adaptive angular sampling non-uniform object-space pixelation (NUOP) approach single photon emission computed tomography (SPECT)
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Résumé:This paper presents an analytical approach for performing adaptive angular sampling in single photon emission computed tomography (SPECT) imaging. It allows for a rapid determination of the optimum sampling strategy that minimizes image variance in regions-of-interest (ROIs). The proposed method consists of three key components: (a) a set of close-form equations for evaluating image variance and resolution attainable with a given sampling strategy, (b) a gradient-based algorithm for searching through the parameter space to find the optimum sampling strategy and (c) an efficient computation approach for speeding up the search process. In this paper, we have demonstrated the use of the proposed analytical approach with a single-head SPECT system for finding the optimum distribution of imaging time across all possible sampling angles. Compared to the conventional uniform angular sampling approach, adaptive angular sampling allows the camera to spend larger fractions of imaging time at angles that are more efficient in acquiring useful imaging information. This leads to a significantly lowered image variance. In general, the analytical approach developed in this study could be used with many nuclear imaging systems (such as SPECT, PET and X-ray CT) equipped with adaptive hardware. This strategy could provide an optimized sampling efficiency and therefore an improved image quality
Description:Date Revised 20.11.2019
published: Print-Electronic
Citation Status PubMed-not-MEDLINE
ISSN:0018-9499