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BibTeX
Introduction to artificial intelligence in ultrasound imaging in obstetrics and gynecology
Ultrasound in obstetrics & gynecology, 2020-10, Vol.56 (4), p.498-505
Drukker, L.
Noble, J. A.
Papageorghiou, A. T.
2020
Volltextzugriff (PDF)
Details
Autor(en) / Beteiligte
Drukker, L.
Noble, J. A.
Papageorghiou, A. T.
Titel
Introduction to artificial intelligence in ultrasound imaging in obstetrics and gynecology
Ist Teil von
Ultrasound in obstetrics & gynecology, 2020-10, Vol.56 (4), p.498-505
Ort / Verlag
Chichester, UK: John Wiley & Sons, Ltd
Erscheinungsjahr
2020
Quelle
MEDLINE
Beschreibungen/Notizen
ABSTRACT Artificial intelligence (AI) uses data and algorithms to aim to draw conclusions that are as good as, or even better than, those drawn by humans. AI is already part of our daily life; it is behind face recognition technology, speech recognition in virtual assistants (such as Amazon Alexa, Apple's Siri, Google Assistant and Microsoft Cortana) and self‐driving cars. AI software has been able to beat world champions in chess, Go and recently even Poker. Relevant to our community, it is a prominent source of innovation in healthcare, already helping to develop new drugs, support clinical decisions and provide quality assurance in radiology. The list of medical image‐analysis AI applications with USA Food and Drug Administration or European Union (soon to fall under European Union Medical Device Regulation) approval is growing rapidly and covers diverse clinical needs, such as detection of arrhythmia using a smartwatch or automatic triage of critical imaging studies to the top of the radiologist's worklist. Deep learning, a leading tool of AI, performs particularly well in image pattern recognition and, therefore, can be of great benefit to doctors who rely heavily on images, such as sonologists, radiographers and pathologists. Although obstetric and gynecological ultrasound are two of the most commonly performed imaging studies, AI has had little impact on this field so far. Nevertheless, there is huge potential for AI to assist in repetitive ultrasound tasks, such as automatically identifying good‐quality acquisitions and providing instant quality assurance. For this potential to thrive, interdisciplinary communication between AI developers and ultrasound professionals is necessary. In this article, we explore the fundamentals of medical imaging AI, from theory to applicability, and introduce some key terms to medical professionals in the field of ultrasound. We believe that wider knowledge of AI will help accelerate its integration into healthcare. © 2020 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of the International Society of Ultrasound in Obstetrics and Gynecology.
Sprache
Englisch
Identifikatoren
ISSN: 0960-7692
eISSN: 1469-0705
DOI: 10.1002/uog.22122
Titel-ID: cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7702141
Format
–
Schlagworte
Algorithms
,
Arrhythmia
,
Artificial intelligence
,
Artificial Intelligence - trends
,
Face recognition
,
Female
,
Gynecology
,
Gynecology - trends
,
Health care
,
Humans
,
Image processing
,
Machine learning
,
Medical electronics
,
Medical equipment
,
Medical imaging
,
Medical personnel
,
Object recognition
,
Obstetrics
,
Obstetrics - trends
,
Pattern recognition
,
Physicians
,
Pregnancy
,
Quality assurance
,
Quality control
,
Radiology
,
Speech recognition
,
State‐of‐the‐Art Review
,
Ultrasonic imaging
,
Ultrasonography - trends
,
Ultrasound
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