Coronary artery stents: influence of adaptive statistical iterative reconstruction on image quality using 64-HDCT | Zendy

Cathérine Gebhard | Zendy; Michael Fiechter | Zendy; Tobias A. Fuchs | Zendy; Julia Stehli | Zendy; E. Müller | Zendy; Barbara E. Stähli | Zendy; C. E. Gebhard | Zendy; Jelena-R. Ghadri | Zendy; Bernd Klaeser | Zendy; Oliver Gaemperli | Zendy; Philipp A. Kaufmann | Zendy

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Coronary artery stents: influence of adaptive statistical iterative reconstruction on image quality using 64-HDCT

Author(s) -

Cathérine Gebhard,

Michael Fiechter,

Tobias A. Fuchs,

Julia Stehli,

E. Müller,

Barbara E. Stähli,

C. E. Gebhard,

Jelena-R. Ghadri,

Bernd Klaeser,

Oliver Gaemperli,

Philipp A. Kaufmann

Publication year - 2013

Publication title -

european heart journal - cardiovascular imaging

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 2.576

H-Index - 92

eISSN - 2047-2412

pISSN - 2047-2404

DOI - 10.1093/ehjci/jet013

Subject(s) - image quality , iterative reconstruction , stent , medicine , image noise , radiology , nuclear medicine , artificial intelligence , image (mathematics) , computer science

The assessment of coronary stents with present-generation 64-detector row computed tomography (HDCT) scanners is limited by image noise and blooming artefacts. We evaluated the performance of adaptive statistical iterative reconstruction (ASIR) for noise reduction in coronary stent imaging with HDCT.

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