Literature DB >> 22256319

Image enhancement by spectral-error correction for dual-energy computed tomography.

Kyung-Kook Park1, Chang-Hyun Oh, Metin Akay.   

Abstract

Dual-energy CT (DECT) was reintroduced recently to use 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 low and high energy images or measurements, so that it is difficult to acquire accurate spectral information due to amplification of high pixel noise in the resulting difference image. In this work, an image enhancement technique for DECT is proposed, based on the fact that the attenuation of a higher density material decreases more rapidly as X-ray energy increases. We define as spectral error the case when a pixel pair of low and high energy images deviates far from the expected attenuation trend. After analyzing the spectral-error sources of DECT images, we propose a DECT image enhancement method, which consists of three steps: water-reference offset correction, spectral-error correction, and anti-correlated noise reduction. It is the main idea of this work that makes spectral errors distributed like random noise over the true attenuation and suppressed by the well-known anti-correlated noise reduction. The proposed method suppressed noise of liver lesions and improved contrast between liver lesions and liver parenchyma in DECT contrast-enhanced abdominal images and their two-material decomposition.

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Year:  2011        PMID: 22256319     DOI: 10.1109/IEMBS.2011.6092095

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  3 in total

1.  Adaptive noise correction of dual-energy computed tomography images.

Authors:  Rafael Simon Maia; Christian Jacob; Amy K Hara; Alvin C Silva; William Pavlicek; J Ross Mitchell
Journal:  Int J Comput Assist Radiol Surg       Date:  2015-10-13       Impact factor: 2.924

2.  Virtual versus true non-contrast dual-energy CT imaging for the diagnosis of aortic intramural hematoma.

Authors:  Salim Si-Mohamed; Nicolas Dupuis; Valérie Tatard-Leitman; David Rotzinger; Sara Boccalini; Matthias Dion; Alain Vlassenbroek; Philippe Coulon; Yoad Yagil; Nadav Shapira; Philippe Douek; Loic Boussel
Journal:  Eur Radiol       Date:  2019-07-01       Impact factor: 5.315

3.  An algorithm for noise correction of dual-energy computed tomography material density images.

Authors:  Rafael Simon Maia; Christian Jacob; Amy K Hara; Alvin C Silva; William Pavlicek; Mitchell J Ross
Journal:  Int J Comput Assist Radiol Surg       Date:  2014-05-11       Impact factor: 2.924

  3 in total

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