Literature DB >> 24149861

Iterative image reconstruction and its role in cardiothoracic computed tomography.

Sarabjeet Singh1, Ranish Deedar Ali Khawaja, Sarvenaz Pourjabbar, Atul Padole, Diego Lira, Mannudeep K Kalra.   

Abstract

Revolutionary developments in multidetector-row computed tomography (CT) scanner technology offer several advantages for imaging of cardiothoracic disorders. As a result, expanding applications of CT now account for >85 million CT examinations annually in the United States alone. Given the large number of CT examinations performed, concerns over increase in population-based risk for radiation-induced carcinogenesis have made CT radiation dose a top safety concern in health care. In response to this concern, several technologies have been developed to reduce the dose with more efficient use of scan parameters and the use of "newer" image reconstruction techniques. Although iterative image reconstruction algorithms were first introduced in the 1970s, filtered back projection was chosen as the conventional image reconstruction technique because of its simplicity and faster reconstruction times. With subsequent advances in computational speed and power, iterative reconstruction techniques have reemerged and have shown the potential of radiation dose optimization without adversely influencing diagnostic image quality. In this article, we review the basic principles of different iterative reconstruction algorithms and their implementation for various clinical applications in cardiothoracic CT examinations for reducing radiation dose.

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Year:  2013        PMID: 24149861     DOI: 10.1097/RTI.0000000000000054

Source DB:  PubMed          Journal:  J Thorac Imaging        ISSN: 0883-5993            Impact factor:   3.000


  6 in total

1.  Optimizing radiation dose by using advanced modelled iterative reconstruction in high-pitch coronary CT angiography.

Authors:  Sonja Gordic; Lotus Desbiolles; Martin Sedlmair; Robert Manka; André Plass; Bernhard Schmidt; Daniela B Husarik; Francesco Maisano; Simon Wildermuth; Hatem Alkadhi; Sebastian Leschka
Journal:  Eur Radiol       Date:  2015-06-03       Impact factor: 5.315

2.  Low kilovoltage peak (kVp) with an adaptive statistical iterative reconstruction algorithm in computed tomography urography: evaluation of image quality and radiation dose.

Authors:  Zhiguo Zhou; Haixi Chen; Wei Wei; Shanghui Zhou; Jingbo Xu; Xifu Wang; Qingguo Wang; Guixiang Zhang; Zhuoli Zhang; Linfeng Zheng
Journal:  Am J Transl Res       Date:  2016-09-15       Impact factor: 4.060

3.  Influence of model based iterative reconstruction algorithm on image quality of multiplanar reformations in reduced dose chest CT.

Authors:  Heloise Barras; Vincent Dunet; Anne-Lise Hachulla; Jochen Grimm; Catherine Beigelman-Aubry
Journal:  Acta Radiol Open       Date:  2016-08-24

Review 4.  Clinical Implementation of Deep Learning in Thoracic Radiology: Potential Applications and Challenges.

Authors:  Eui Jin Hwang; Chang Min Park
Journal:  Korean J Radiol       Date:  2020-05       Impact factor: 3.500

5.  Improved sensitivity of computed tomography towards iodine and gold nanoparticle contrast agents via iterative reconstruction methods.

Authors:  Ally Leigh Bernstein; Amar Dhanantwari; Martina Jurcova; Rabee Cheheltani; Pratap Chandra Naha; Thomas Ivanc; Efrat Shefer; David Peter Cormode
Journal:  Sci Rep       Date:  2016-05-17       Impact factor: 4.379

6.  The effect of iterative reconstruction on image quality in evaluating patients with coronary calcifications or stents at coronary computed tomography angiography.

Authors:  Sherif Moustafa; Karuna M Das; Khalid Al Dossari
Journal:  Anatol J Cardiol       Date:  2015-05-05       Impact factor: 1.596

  6 in total

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