A Unified Framework for Comprehensive Cardiac CT Segmentation and Phenotyping
This study introduce a new open-source AI tool that can automatically measure 14 distinct heart structures from CT scans with greater accuracy than existing tools. This development makes it practical to assess heart health on a larger scale using scans that people already receive.
Reconstruction-Informed and Multidomain Deep Learning for Generalizable CT-Free Attenuation Correction in SPECT Myocardial Perfusion Imaging
This study presents a deep learning approach that feeds several differently reconstructed non-corrected SPECT images into a single model and trains it against both the attenuation map and the corrected image at once, producing attenuation-corrected myocardial perfusion scans that hold up on data from an outside centre and that experienced readers could not reliably tell apart from the CT-corrected versions they were meant to replace.
TAVI-ALPURA
An AI-based tool for predicting long-term mortality after transcatheter aortic valve implantation (TAVI).
AiTTRIX
An explainable ML platform for transparent risk stratification in cardiac amyloidosis
Radiuma
A no-code visual workflow builder for reproducible medical image analysis and machine learning.
Grounding Clinical AI Competency in the Architecture of Clinical Care
This work introduces the Clinical World Model and Clinical AI Skill-Mix, a shared framework that organises medical AI competency across billions of clinical contexts and reframes the field’s central question from whether clinical AI works to the coordinates in which it has demonstrated reliability, and for whom.
The 2026 Otto Hess Trainee Award
The Swiss Society of Cardiology honored Dr. Stark’s doctoral thesis on diagnosing hemodynamic relevance in anomalous aortic origin of a coronary artery (AAOCA), a congenital condition that can cause sudden cardiac death. His work pairs a prospective clinical cohort with computational fluid dynamics and two open-source tools, AIVUS-CAA and multimodars, to make accurate AAOCA assessment more accessible beyond specialized centers.
Swiss Heart Foundation Research Prize 2026
Prof. Christoph Gräni was awarded the Cardiology Research Prize 2026 by the Swiss Heart Foundation (Schweizerische Herzstiftung), which was presented on 2 April 2026, in recognition of outstanding contributions to cardiac imaging and prognosis through the integration of artificial intelligence.
CVRC 2026 Best Poster Prize Awarded to Pooya
Pooya received the CVRC 2026 Best Poster Prize (Clinical Category) for his deep learning–based cardiac CT segmentation model.
PySERA
A python-based standardized feature extraction for radiomics analysis.