abstract: Computed tomography (CT) is one of the essential imaging modalities for medical diagnosis. Since its introduction in 1972, CT technology has been improved dramatically, especially in terms of its acquisition speed. However, the main principle of CT which consists in acquiring only density information has not changed at all until recently. Different materials may have the same CT number, which may lead to uncertainty or misdiagnosis. Dual-energy CT (DECT) was reintroduced recently to solve this problem by using the additional spectral information of X-ray attenuation and aims for accurate density measurement and material differentiation. However, the spectral information lies in the difference between two low and high energy images or measurements, so that it is difficult to acquire the accurate spectral information due to amplification of high pixel noise in the resulting difference image. In this work, a new model and an image enhancement technique for DECT are proposed, based on the fact that the attenuation of a high density material decreases more rapidly as X-ray energy increases. This fact has been previously ignored in most of DECT image enhancement techniques. The proposed technique consists of offset correction, spectral error correction, and adaptive noise suppression. It reduced noise, improved contrast effectively and showed better material differentiation in real patient images as well as phantom studies. / Dissertation/Thesis / Ph.D. Bioengineering 2011
Identifer | oai:union.ndltd.org:asu.edu/item:9200 |
Date | January 2011 |
Contributors | Park, Kyung K. (Author), Metin, Akay (Advisor), Pavlicek, William (Committee member), Akay, Yasemin (Committee member), Towe, Bruce (Committee member), Muthuswamy, Jitendran (Committee member), Arizona State University (Publisher) |
Source Sets | Arizona State University |
Language | English |
Detected Language | English |
Type | Doctoral Dissertation |
Format | 82 pages |
Rights | http://rightsstatements.org/vocab/InC/1.0/, All Rights Reserved |
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