Sandy Engelhardt, Salman Ul Hussan Dar, Lalith Sharan, Florian André, Eike Nagel, Sarina Thomas
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引用次数: 0
Abstract
Recent progress in artificial intelligence (AI) includes generative models, multimodal foundation models, and federated learning, which enable a wide spectrum of novel exciting applications and scenarios for cardiac image analysis and cardiovascular interventions. The disruptive nature of these novel technologies enables concurrent text and image analysis by so-called vision-language transformer models. They not only allow for automatic derivation of image reports, synthesis of novel images conditioned on certain textual properties, and visual questioning and answering in an oral or written dialogue style, but also for the retrieval of medical images from a large database based on a description of the pathology or specifics of the dataset of interest. Federated learning is an additional ingredient in these novel developments, facilitating multi-centric collaborative training of AI approaches and therefore access to large clinical cohorts. In this review paper, we provide an overview of the recent developments in the field of cardiovascular imaging and intervention and offer a future outlook.
期刊介绍:
Herz is the high-level journal for further education for all physicians interested in cardiology. The individual issues of the journal each deal with specific topics and comprise review articles in English and German written by competent and esteemed authors. They provide up-to-date and comprehensive information concerning the speciality dealt with in the issue. Due to the fact that all relevant aspects of the pertinent topic of an issue are considered, an overview of the current status and progress in cardiology is presented. Reviews and original articles round off the spectrum of information provided.