Computer aided diagnosis of Coronary Artery Disease, Myocardial Infarction and carotid atherosclerosis using ultrasound images: A review. (January 2017)

• Record Type: Journal Article
• Authors: Faust, Oliver; Acharya, U. Rajendra; Sudarshan, Vidya K.; Tan, Ru San; Yeong, Chai Hong; Molinari, Filippo; Ng, Kwan Hoong
• Is Part Of: Physica medica. Volume 33(2017)
• Page Start: 1
• Page End: 15
• Publication Date: 2017-01
• Subjects: Computer aided diagnosis -- Coronary Artery Disease -- Myocardial Infarction -- Carotid atherosclerosis -- Thoracic Ultrasound -- Intravascular Ultrasound; Medical physics -- Periodicals; Biophysics -- Periodicals; Biophysics -- Periodicals; Imagerie médicale -- Périodiques; Radiothérapie -- Périodiques; Rayons X -- Sécurité -- Mesures -- Périodiques; Physique -- Périodiques; Médecine -- Périodiques; 610.153
• DOI: 10.1016/j.ejmp.2016.12.005
• Languages: English
• ISSNs: 1120-1797

Abstract

Highlights: Computer based diagnosis should mimic human decision making. Employ automated decision making to find a diagnosis. More US images will lead to more diagnostically relevant information. Use a design methodology to create diagnosis support systems. Regular hardware and software updates keep the diagnosis support systems relevant. 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.