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Computer-aided evaluation of anatomical accuracy of image fusion between X-ray CT and SPECT

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Title: Computer-aided evaluation of anatomical accuracy of image fusion between X-ray CT and SPECT
Authors: Han, Jingfeng1 jingfeng@informatik.uni-erlangen.de, Köstler, Harald2, Bennewitz, Christian3, Kuwert, Torsten3, Hornegger, Joachim1
Source: Computerized Medical Imaging & Graphics. Jul2008, Vol. 32 Issue 5, p388-395. 8p.
Subjects: Tomography, Scanning systems, Image transmission, Medical imaging systems
Abstract: Abstract: Hybrid scanners, which enable the performance of single photon emission computed tomography (SPECT) and X-ray computed tomography (CT) in one imaging session, have considerable diagnostic potential. However, evaluating the anatomical accuracy of image fusion inherent to these systems remains a challenge. This paper proposes a method for evaluating this variable with minimum user interaction. It focuses on measuring the distance between the centers of gravity of the SPECT hot spot and its counterpart in the CT image. A localized maximally stable extremal regions method is proposed to automatically segment SPECT hot spots, while the corresponding CT structures are segmented by the semi-automatic random walk method, based on a fast multigrid solver. Accuracy and reproducibility of the validation method have been preliminary confirmed by the test with 21 clinical data-sets. [Copyright &y& Elsevier]
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Database: Engineering Source
Description
Abstract:Abstract: Hybrid scanners, which enable the performance of single photon emission computed tomography (SPECT) and X-ray computed tomography (CT) in one imaging session, have considerable diagnostic potential. However, evaluating the anatomical accuracy of image fusion inherent to these systems remains a challenge. This paper proposes a method for evaluating this variable with minimum user interaction. It focuses on measuring the distance between the centers of gravity of the SPECT hot spot and its counterpart in the CT image. A localized maximally stable extremal regions method is proposed to automatically segment SPECT hot spots, while the corresponding CT structures are segmented by the semi-automatic random walk method, based on a fast multigrid solver. Accuracy and reproducibility of the validation method have been preliminary confirmed by the test with 21 clinical data-sets. [Copyright &y& Elsevier]
ISSN:08956111
DOI:10.1016/j.compmedimag.2008.03.002