Machine Learning in Ultrasound Computer-Aided Diagnostic Systems: A Survey
Joint Authors
Huang, Qinghua
Zhang, Fan
Li, Xuelong
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-03-04
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
The ultrasound imaging is one of the most common schemes to detect diseases in the clinical practice.
There are many advantages of ultrasound imaging such as safety, convenience, and low cost.
However, reading ultrasound imaging is not easy.
To support the diagnosis of clinicians and reduce the load of doctors, many ultrasound computer-aided diagnosis (CAD) systems are proposed.
In recent years, the success of deep learning in the image classification and segmentation led to more and more scholars realizing the potential of performance improvement brought by utilizing the deep learning in the ultrasound CAD system.
This paper summarized the research which focuses on the ultrasound CAD system utilizing machine learning technology in recent years.
This study divided the ultrasound CAD system into two categories.
One is the traditional ultrasound CAD system which employed the manmade feature and the other is the deep learning ultrasound CAD system.
The major feature and the classifier employed by the traditional ultrasound CAD system are introduced.
As for the deep learning ultrasound CAD, newest applications are summarized.
This paper will be useful for researchers who focus on the ultrasound CAD system.
American Psychological Association (APA)
Huang, Qinghua& Zhang, Fan& Li, Xuelong. 2018. Machine Learning in Ultrasound Computer-Aided Diagnostic Systems: A Survey. BioMed Research International،Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1127101
Modern Language Association (MLA)
Huang, Qinghua…[et al.]. Machine Learning in Ultrasound Computer-Aided Diagnostic Systems: A Survey. BioMed Research International No. 2018 (2018), pp.1-10.
https://search.emarefa.net/detail/BIM-1127101
American Medical Association (AMA)
Huang, Qinghua& Zhang, Fan& Li, Xuelong. Machine Learning in Ultrasound Computer-Aided Diagnostic Systems: A Survey. BioMed Research International. 2018. Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1127101
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1127101