Hooman Vaseli
Orcid: 0000-0002-8259-9488
According to our database1,
Hooman Vaseli authored at least 19 papers
between 2018 and 2026.
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Bibliography
2026
MultiASNet: Multimodal Label Noise Robust Framework for the Classification of Aortic Stenosis in Echocardiography.
IEEE Trans. Medical Imaging, February, 2026
2025
ControlEchoSynth: Boosting Ejection Fraction Estimation Models via Controlled Video Diffusion.
CoRR, August, 2025
ProtoASNet: Comprehensive evaluation and enhanced performance with uncertainty estimation for aortic stenosis classification in echocardiography.
Medical Image Anal., 2025
HiProtoNet: Hyperbolic Hierarchy-Aware Part Prototypes for Aortic Stenosis Severity Classification.
Proceedings of the Simplifying Medical Ultrasound - 6th International Workshop, 2025
PRECISE-AS: Personalized Reinforcement Learning for Efficient Point-of-Care Echocardiography in Aortic Stenosis Diagnosis.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2025, 2025
Pseudo-D: Informing Multi-view Uncertainty Estimation with Calibrated Neural Training Dynamics.
Proceedings of the Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, 2025
ProtoEFNet: Dynamic Prototype Learning for Inherently Interpretable Ejection Fraction Estimation in Echocardiography.
Proceedings of the Interpretability of Machine Intelligence in Medical Image Computing, 2025
Proceedings of the IEEE/CVF International Conference on Computer Vision, ICCV 2025, 2025
2024
Reliable Multi-view Learning with Conformal Prediction for Aortic Stenosis Classification in Echocardiography.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024
2023
ProtoASNet: Dynamic Prototypes for Inherently Interpretable and Uncertainty-Aware Aortic Stenosis Classification in Echocardiography.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023
EchoGLAD: Hierarchical Graph Neural Networks for Left Ventricle Landmark Detection on Echocardiograms.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023
2022
Differential Learning from Sparse and Noisy Labels for Robust Detection of Clinical Landmarks in Echo Cine Series.
Proceedings of the Simplifying Medical Ultrasound - Third International Workshop, 2022
2021
Echo-Rhythm Net: Semi-Supervised Learning For Automatic Detection of Atrial Fibrillation in Echocardiography.
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021
2020
On Modelling Label Uncertainty in Deep Neural Networks: Automatic Estimation of Intra- Observer Variability in 2D Echocardiography Quality Assessment.
IEEE Trans. Medical Imaging, 2020
Automatic cine-based detection of patients at high risk of heart failure with reduced ejection fraction in echocardiograms.
Comput. methods Biomech. Biomed. Eng. Imaging Vis., 2020
2019
Proceedings of the Medical Imaging 2019: Image-Guided Procedures, 2019
2018
Quantitative Echocardiography: Real-Time Quality Estimation and View Classification Implemented on a Mobile Android Device.
Proceedings of the Simulation, Image Processing, and Ultrasound Systems for Assisted Diagnosis and Navigation, 2018
A Unified Framework Integrating Recurrent Fully-Convolutional Networks and Optical Flow for Segmentation of the Left Ventricle in Echocardiography Data.
Proceedings of the Deep Learning in Medical Image Analysis - and - Multimodal Learning for Clinical Decision Support, 2018
Automatic Detection of Patients with a High Risk of Systolic Cardiac Failure in Echocardiography.
Proceedings of the Deep Learning in Medical Image Analysis - and - Multimodal Learning for Clinical Decision Support, 2018