Literature DB >> 28010920

Computer aided diagnosis of Coronary Artery Disease, Myocardial Infarction and carotid atherosclerosis using ultrasound images: A review.

Oliver Faust1, U Rajendra Acharya2, Vidya K Sudarshan3, Ru San Tan3, Chai Hong Yeong4, Filippo Molinari5, Kwan Hoong Ng6.   

Abstract

The diagnosis of Coronary Artery Disease (CAD), Myocardial Infarction (MI) and carotid atherosclerosis is of paramount importance, as these cardiovascular diseases may cause medical complications and large number of death. Ultrasound (US) is a widely used imaging modality, as it captures moving images and image features correlate well with results obtained from other imaging methods. Furthermore, US does not use ionizing radiation and it is economical when compared to other imaging modalities. However, reading US images takes time and the relationship between image and tissue composition is complex. Therefore, the diagnostic accuracy depends on both time taken to read the images and experience of the screening practitioner. Computer support tools can reduce the inter-operator variability with lower subject specific expertise, when appropriate processing methods are used. In the current review, we analysed automatic detection methods for the diagnosis of CAD, MI and carotid atherosclerosis based on thoracic and Intravascular Ultrasound (IVUS). We found that IVUS is more often used than thoracic US for CAD. But for MI and carotid atherosclerosis IVUS is still in the experimental stage. Furthermore, thoracic US is more often used than IVUS for computer aided diagnosis systems.
Copyright © 2016 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Carotid atherosclerosis; Computer aided diagnosis; Coronary Artery Disease; Intravascular Ultrasound; Myocardial Infarction; Thoracic Ultrasound

Mesh:

Year:  2016        PMID: 28010920     DOI: 10.1016/j.ejmp.2016.12.005

Source DB:  PubMed          Journal:  Phys Med        ISSN: 1120-1797            Impact factor:   2.685


  9 in total

1.  Accuracy of diffusion-weighted imaging-magnetic resonance in differentiating functional from non-functional pituitary macro-adenoma and classification of tumor consistency.

Authors:  Morteza Sanei Taheri; Farnaz Kimia; Mersad Mehrnahad; Hamidreza Saligheh Rad; Hamidreza Haghighatkhah; Afshin Moradi; Anahita Fathi Kazerooni; Mohammadreza Alviri; Abdorrahim Absalan
Journal:  Neuroradiol J       Date:  2018-12-03

Review 2.  Deep learning for cardiac computer-aided diagnosis: benefits, issues & solutions.

Authors:  Brian C S Loh; Patrick H H Then
Journal:  Mhealth       Date:  2017-10-19

Review 3.  Harnessing Machine Intelligence in Automatic Echocardiogram Analysis: Current Status, Limitations, and Future Directions.

Authors:  Ghada Zamzmi; Li-Yueh Hsu; Wen Li; Vandana Sachdev; Sameer Antani
Journal:  IEEE Rev Biomed Eng       Date:  2021-01-22

4.  An efficient data mining framework for the characterization of symptomatic and asymptomatic carotid plaque using bidimensional empirical mode decomposition technique.

Authors:  Filippo Molinari; U Raghavendra; Anjan Gudigar; Kristen M Meiburger; U Rajendra Acharya
Journal:  Med Biol Eng Comput       Date:  2018-02-23       Impact factor: 2.602

5.  A computer-aided diagnosing system in the evaluation of thyroid nodules-experience in a specialized thyroid center.

Authors:  Shujun Xia; Jiejie Yao; Wei Zhou; Yijie Dong; Shangyan Xu; Jianqiao Zhou; Weiwei Zhan
Journal:  World J Surg Oncol       Date:  2019-12-06       Impact factor: 2.754

6.  Deep Neural Network-Aided Histopathological Analysis of Myocardial Injury.

Authors:  Yiping Jiao; Jie Yuan; Oluwatofunmi Modupeoluwa Sodimu; Yong Qiang; Yichen Ding
Journal:  Front Cardiovasc Med       Date:  2022-01-10

7.  Bi-stream CNN Down Syndrome screening model based on genotyping array.

Authors:  Bing Feng; William Hoskins; Yan Zhang; Zibo Meng; David C Samuels; Jiandong Wang; Ruofan Xia; Chao Liu; Jijun Tang; Yan Guo
Journal:  BMC Med Genomics       Date:  2018-11-20       Impact factor: 3.063

Review 8.  A Novel Promising Frontier for Human Health: The Beneficial Effects of Nutraceuticals in Cardiovascular Diseases.

Authors:  Albino Carrizzo; Carmine Izzo; Maurizio Forte; Eduardo Sommella; Paola Di Pietro; Eleonora Venturini; Michele Ciccarelli; Gennaro Galasso; Speranza Rubattu; Petro Campiglia; Sebastiano Sciarretta; Giacomo Frati; Carmine Vecchione
Journal:  Int J Mol Sci       Date:  2020-11-18       Impact factor: 5.923

Review 9.  Machine Learning Quantitation of Cardiovascular and Cerebrovascular Disease: A Systematic Review of Clinical Applications.

Authors:  Chris Boyd; Greg Brown; Timothy Kleinig; Joseph Dawson; Mark D McDonnell; Mark Jenkinson; Eva Bezak
Journal:  Diagnostics (Basel)       Date:  2021-03-19
  9 in total

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