Künstliche Intelligenz in der kardialen Bildgebung

Zusammenfassung

Verfahren der künstlichen Intelligenz (KI) haben in der kardialen Bildgebung große Relevanz erlangt. In dieser Kurzübersicht werden die Anwendungsbereiche von KI in der Echokardiografie, Magnetresonanztomografie (MRT) und Computertomografie (CT) beleuchtet. Die Analyse des ventrikulären Volumens und dessen Funktion werden durch KI in der Echokardiografie und in der MRT erweitert und verbessert. In der CT ermöglicht die KI die automatische Quantifizierung der koronaren Kalklast, Risikoklassifizierung und Prognose des Behandlungserfolgs. KI verringert die Kluft zwischen Experten und Anfängern, da sie zuverlässige und reproduzierbare Analysen durchführt bei gesteigerter Effizienz. Neue Konzepte wie das föderierte Lernen, das multizentrisches verteiltes Trainieren ermöglicht, sowie die multimodale KI, die automatisiert Text- und Bildeingaben miteinander verknüpft, werden voraussichtlich die nächsten größeren Meilensteine darstellen.

Abstract

Artificial intelligence (AI) methods have gained great relevance in cardiac imaging. This brief overview highlights the application areas of AI in echocardiography, cardiac magnetic resonance imaging (MRI) and cardiac computed tomography (CT). The analysis of the ventricular volume and its function will be expanded and improved by AI in echocardiography and MRI. In the CT, the AI enables the automatic quantification of the coronary calcification, risk classification and prognosis of the treatment success. AI narrows the gap between experts and novices by performing reliable and reproducible analysis with increased efficiency. New concepts such as federated learning, which enables multi-centric distributed training, and multi-modal AI, which automatically links text and image inputs, will probably represent the next major milestones in the field.

Schlüsselwörter

künstliche Intelligenz - kardiologische Bildgebung - föderiertes Lernen

Keywords

artificial intelligence - cardiac imaging - federated learning

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