Literature DB >> 32017605

Development and application of artificial intelligence in cardiac imaging.

Beibei Jiang1, Ning Guo2, Yinghui Ge3, Lu Zhang1, Matthijs Oudkerk4,5, Xueqian Xie1.   

Abstract

In this review, we describe the technical aspects of artificial intelligence (AI) in cardiac imaging, starting with radiomics, basic algorithms of deep learning and application tasks of algorithms, until recently the availability of the public database. Subsequently, we conducted a systematic literature search for recently published clinically relevant studies on AI in cardiac imaging. As a result, 24 and 14 studies using CT and MRI, respectively, were included and summarized. From these studies, it can be concluded that AI is widely applied in cardiac applications in the clinic, including coronary calcium scoring, coronary CT angiography, fractional flow reserve CT, plaque analysis, left ventricular myocardium analysis, diagnosis of myocardial infarction, prognosis of coronary artery disease, assessment of cardiac function, and diagnosis and prognosis of cardiomyopathy. These advancements show that AI has a promising prospect in cardiac imaging.

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Year:  2020        PMID: 32017605      PMCID: PMC7465846          DOI: 10.1259/bjr.20190812

Source DB:  PubMed          Journal:  Br J Radiol        ISSN: 0007-1285            Impact factor:   3.039


  67 in total

Review 1.  Cardiac MRI: A General Overview with Emphasis on Current Use and Indications.

Authors:  Michael P Pfeiffer; Robert W W Biederman
Journal:  Med Clin North Am       Date:  2015-07       Impact factor: 5.456

2.  Automatic segmentation of the right ventricle from cardiac MRI using a learning-based approach.

Authors:  Michael R Avendi; Arash Kheradvar; Hamid Jafarkhani
Journal:  Magn Reson Med       Date:  2017-02-16       Impact factor: 4.668

3.  A combined deep-learning and deformable-model approach to fully automatic segmentation of the left ventricle in cardiac MRI.

Authors:  M R Avendi; Arash Kheradvar; Hamid Jafarkhani
Journal:  Med Image Anal       Date:  2016-02-06       Impact factor: 8.545

4.  Challenges Related to Artificial Intelligence Research in Medical Imaging and the Importance of Image Analysis Competitions.

Authors:  Luciano M Prevedello; Safwan S Halabi; George Shih; Carol C Wu; Marc D Kohli; Falgun H Chokshi; Bradley J Erickson; Jayashree Kalpathy-Cramer; Katherine P Andriole; Adam E Flanders
Journal:  Radiol Artif Intell       Date:  2019-01-30

5.  Generative Adversarial Networks for Noise Reduction in Low-Dose CT.

Authors:  Jelmer M Wolterink; Tim Leiner; Max A Viergever; Ivana Isgum
Journal:  IEEE Trans Med Imaging       Date:  2017-05-26       Impact factor: 10.048

6.  Incremental role of resting myocardial computed tomography perfusion for predicting physiologically significant coronary artery disease: A machine learning approach.

Authors:  Donghee Han; Ji Hyun Lee; Asim Rizvi; Heidi Gransar; Lohendran Baskaran; Joshua Schulman-Marcus; Bríain Ó Hartaigh; Fay Y Lin; James K Min
Journal:  J Nucl Cardiol       Date:  2017-03-16       Impact factor: 5.952

7.  Texture analysis of cardiac cine magnetic resonance imaging to detect nonviable segments in patients with chronic myocardial infarction.

Authors:  Andrés Larroza; María P López-Lereu; José V Monmeneu; Jose Gavara; Francisco J Chorro; Vicente Bodí; David Moratal
Journal:  Med Phys       Date:  2018-02-22       Impact factor: 4.071

8.  Deep learning analysis of the myocardium in coronary CT angiography for identification of patients with functionally significant coronary artery stenosis.

Authors:  Majd Zreik; Nikolas Lessmann; Robbert W van Hamersvelt; Jelmer M Wolterink; Michiel Voskuil; Max A Viergever; Tim Leiner; Ivana Išgum
Journal:  Med Image Anal       Date:  2017-11-26       Impact factor: 8.545

9.  Coronary plaque quantification and fractional flow reserve by coronary computed tomography angiography identify ischaemia-causing lesions.

Authors:  Sara Gaur; Kristian Altern Øvrehus; Damini Dey; Jonathon Leipsic; Hans Erik Bøtker; Jesper Møller Jensen; Jagat Narula; Amir Ahmadi; Stephan Achenbach; Brian S Ko; Evald Høj Christiansen; Anne Kjer Kaltoft; Daniel S Berman; Hiram Bezerra; Jens Flensted Lassen; Bjarne Linde Nørgaard
Journal:  Eur Heart J       Date:  2016-01-12       Impact factor: 29.983

10.  Radiomics versus Visual and Histogram-based Assessment to Identify Atheromatous Lesions at Coronary CT Angiography: An ex Vivo Study.

Authors:  Márton Kolossváry; Júlia Karády; Yasuka Kikuchi; Alexander Ivanov; Christopher L Schlett; Michael T Lu; Borek Foldyna; Béla Merkely; Hugo J Aerts; Udo Hoffmann; Pál Maurovich-Horvat
Journal:  Radiology       Date:  2019-08-06       Impact factor: 11.105

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  5 in total

Review 1.  Recent Advances in Coronary Computed Tomography Angiogram: The Ultimate Tool for Coronary Artery Disease.

Authors:  Luay Alalawi; Matthew J Budoff
Journal:  Curr Atheroscler Rep       Date:  2022-05-04       Impact factor: 5.967

Review 2.  Artificial Intelligence in Coronary CT Angiography: Current Status and Future Prospects.

Authors:  Jiahui Liao; Lanfang Huang; Meizi Qu; Binghui Chen; Guojie Wang
Journal:  Front Cardiovasc Med       Date:  2022-06-17

3.  Development and multicenter validation of chest X-ray radiography interpretations based on natural language processing.

Authors:  Yaping Zhang; Mingqian Liu; Shundong Hu; Yao Shen; Jun Lan; Beibei Jiang; Geertruida H de Bock; Rozemarijn Vliegenthart; Xu Chen; Xueqian Xie
Journal:  Commun Med (Lond)       Date:  2021-10-28

4.  Artificial Intelligence Algorithm-Based Computerized Tomography Image Features Combined with Serum Tumor Markers for Diagnosis of Pancreatic Cancer.

Authors:  Zhengmei Qiao; Junli Ge; Wenping He; Xinye Xu; Jianxin He
Journal:  Comput Math Methods Med       Date:  2022-03-02       Impact factor: 2.238

5.  Imaging patients with stable chest pain special feature: introductory editorial.

Authors:  Matthijs Oudkerk; Edwin Jr van Beek
Journal:  Br J Radiol       Date:  2020-09-01       Impact factor: 3.039

  5 in total

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