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Review
. 2023 Jan 31;29(1):40-45.
doi: 10.4274/dir.2022.211260. Epub 2023 Jan 2.

Artificial intelligence in diagnostic ultrasonography

Oğuz Dicle  1
Affiliations
Review

Artificial intelligence in diagnostic ultrasonography

Oğuz Dicle. Diagn Interv Radiol. .

Abstract

Artificial intelligence (AI) continues to change paradigms in the field of medicine with new applications that are applicable to daily life. The field of ultrasonography, which has been developing since the 1950s and continues to be one of the most powerful tools in the field of diagnosis, is also the subject of AI studies, despite its unique problems. It is predicted that many operations, such as appropriate diagnostic tool selection, use of the most relevant parameters, improvement of low-quality images, automatic lesion detection and diagnosis from the image, and classification of pathologies, will be performed using AI tools in the near future. Especially with the use of convolutional neural networks, successful results can be obtained for lesion detection, segmentation, and classification from images. In this review, relevant developments are summarized based on the literature, and examples of the tools used in the field are presented.

Keywords: Artificial intelligence; deep learning; machine learning; radiology; ultrasonography.

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Figures

Figure 1
Figure 1
Basic data processing in convolutional networks
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