Diffusion-based deep-learning framework (ETH Zürich BMDS Lab) for automated multiclass segmentation of lumbar spine MRI in low-back-pain patients. Segments vertebral bodies, discs …
Granted U.S. patent (12,239,477 B2) for automatic determination of a cardiac motion parameter — deep-learning mitral/tricuspid valve tracking on long-axis CINE MRI. Assigned to …
Poster on diffusion-based semantic segmentation of lumbar spine MRI in low-back-pain patients. ML4H Symposium, 2024.
Automated pipeline to extract vertebral compression parameters from clinical lumbar-spine MRI. Poster, IEEE ISBI 2024.
Automated AI-based extraction of mitral and tricuspid valve motion parameters from long-axis cine cardiac MRI. European Journal of Radiology, 2023.
Deep-learning extraction of mitral-valve annulus motion parameters from long-axis cine cardiac MRI. ISMRM 29th Annual Meeting, 2021.
Two chained CNNs for automatic mitral valve-annulus landmark tracking on 2- and 4-chamber CINE CMR, with an interactive dashboard for cluster analysis and anomaly detection. …
Deep-learning segmentation combining bSSFP, T2 and LGE cardiac MRI to delineate infarcted and edema myocardial regions for myocardial-infarction diagnosis.
M.Sc. Thesis carried out in collaboration with Siemens Healthineers. Research state-of-the-art literature on cardiac MRI slice tracking and medical landmark detection. Develop a …
MATLAB GUI for ECG annotation plus an SVM classifier that retrospectively detects arrhythmia during resuscitation episodes from five discriminative ECG features. BSc thesis.