Tewodros Weldebirhan Arega

Orcid: 0000-0002-2319-9038

According to our database1, Tewodros Weldebirhan Arega authored at least 11 papers between 2020 and 2023.

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

Timeline

Legend:

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Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2023
Deep Learning Segmentation of the Right Ventricle in Cardiac MRI: The M&Ms Challenge.
IEEE J. Biomed. Health Informatics, July, 2023

Automatic uncertainty-based quality controlled T1 mapping and ECV analysis from native and post-contrast cardiac T1 mapping images using Bayesian vision transformer.
Medical Image Anal., May, 2023

Uncertainty-based Deep Learning Methods for Robust and Reliable Cardiac MRI Segmentation and Analysis. (Méthodes d'apprentissage profond basées sur l'incertitude pour une segmentation et une analyse robustes et fiables de l'IRM cardiaque).
PhD thesis, 2023

MyoPS: A benchmark of myocardial pathology segmentation combining three-sequence cardiac magnetic resonance images.
Medical Image Anal., 2023

Using Uncertainty Information for Kidney Tumor Segmentation.
Proceedings of the Kidney and Kidney Tumor Segmentation - MICCAI 2023 Challenge, 2023

2022
An Improved 3D Deep Learning-Based Segmentation of Left Ventricular Myocardial Diseases from Delayed-Enhancement MRI with Inclusion and Classification Prior Information U-Net (ICPIU-Net).
Sensors, 2022

Automatic Quality Assessment of Cardiac MR Images with Motion Artefacts Using Multi-task Learning and K-Space Motion Artefact Augmentation.
Proceedings of the Statistical Atlases and Computational Models of the Heart. Regular and CMRxMotion Challenge Papers, 2022

Using Polynomial Loss and Uncertainty Information for Robust Left Atrial and Scar Quantification and Segmentation.
Proceedings of the Left Atrial and Scar Quantification and Segmentation - First Challenge, 2022

2021
Using MRI-specific Data Augmentation to Enhance the Segmentation of Right Ventricle in Multi-disease, Multi-center and Multi-view Cardiac MRI.
Proceedings of the Statistical Atlases and Computational Models of the Heart. Multi-Disease, Multi-View, and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge, 2021

Leveraging Uncertainty Estimates to Improve Segmentation Performance in Cardiac MR.
Proceedings of the Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Perinatal Imaging, Placental and Preterm Image Analysis, 2021

2020
Automatic Myocardial Scar Segmentation from Multi-sequence Cardiac MRI Using Fully Convolutional Densenet with Inception and Squeeze-Excitation Module.
Proceedings of the Myocardial Pathology Segmentation Combining Multi-Sequence Cardiac Magnetic Resonance Images, 2020


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