CalciVision, a web platform for annotation and detection of aortic valve calcification
Year: 2025
Type: conference-paper
Abstract: We present CalciVision, an innovative web platform that leverages artificial intelligence (AI) to automate the analysis and classification of calcifications in the aortic valve, a condition that can progress to aortic stenosis and significantly impact patient health outcomes. Currently, diagnosis relies on manual analysis of echocardiography images, a time-consuming process prone to human error. CalciVision addresses these challenges by providing a simple and efficient graphical interface that enables cardiologists to utilize AI algorithms and their functionalities in their diagnostic workflows, enhancing accuracy and reducing workload. The web platform integrates features such as AI-driven automatic classification of calcifications, manual image annotation, calculation of calcium quantification metrics, and automated generation of clinical reports. The evaluation conducted with healthcare professionals confirmed the platform’s high usability and effectiveness, underscoring its potential to enhance diagnostic workflows and support clinical decision-making.
Authors: Taveira Janeiro, Rodrigo, Delgado, David
Institution: Iscte – Instituto Universitário de Lisboa
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W7090688607
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