Article ; Online: Computer-Aided Diagnosis Methods for High-Frequency Ultrasound Data Analysis: A Review.
2022 Volume 22, Issue 21
Abstract: Over the last few decades, computer-aided diagnosis systems have become a part of clinical practice. They have the potential to assist clinicians in daily diagnostic tasks. The image processing techniques are fast, repeatable, and robust, which helps ... ...
Abstract | Over the last few decades, computer-aided diagnosis systems have become a part of clinical practice. They have the potential to assist clinicians in daily diagnostic tasks. The image processing techniques are fast, repeatable, and robust, which helps physicians to detect, classify, segment, and measure various structures. The recent rapid development of computer methods for high-frequency ultrasound image analysis opens up new diagnostic paths in dermatology, allergology, cosmetology, and aesthetic medicine. This paper, being the first in this area, presents a research overview of high-frequency ultrasound image processing techniques, which have the potential to be a part of computer-aided diagnosis systems. The reviewed methods are categorized concerning the application, utilized ultrasound device, and image data-processing type. We present the bridge between diagnostic needs and already developed solutions and discuss their limitations and future directions in high-frequency ultrasound image analysis. A search was conducted of the technical literature from 2005 to September 2022, and in total, 31 studies describing image processing methods were reviewed. The quantitative and qualitative analysis included 39 algorithms, which were selected as the most effective in this field. They were completed by 20 medical papers and define the needs and opportunities for high-frequency ultrasound application and CAD development. |
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MeSH term(s) | Diagnosis, Computer-Assisted/methods ; Ultrasonography ; Image Processing, Computer-Assisted/methods ; Algorithms |
Language | English |
Publishing date | 2022-10-30 |
Publishing country | Switzerland |
Document type | Journal Article ; Review |
ZDB-ID | 2052857-7 |
ISSN | 1424-8220 ; 1424-8220 |
ISSN (online) | 1424-8220 |
ISSN | 1424-8220 |
DOI | 10.3390/s22218326 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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