Hooman Vaseli

Orcid: 0000-0002-8259-9488

According to our database1, Hooman Vaseli authored at least 10 papers between 2018 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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PhD thesis 
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Bibliography

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
Designing lightweight deep learning models for echocardiography view classification.
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


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