Daniel Bos

Orcid: 0000-0001-8979-2603

According to our database1, Daniel Bos authored at least 12 papers between 2017 and 2023.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2023
Nested star-shaped objects segmentation using diameter annotations.
Medical Image Anal., December, 2023

UR-CarA-Net: A Cascaded Framework With Uncertainty Regularization for Automated Segmentation of Carotid Arteries on Black Blood MR Images.
IEEE Access, 2023

2022
Computer-aided diagnosis and prediction in brain disorders.
CoRR, 2022

Differentiable Boundary Point Extraction for Weakly Supervised Star-shaped Object Segmentation.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2022

2021
Morphometric and Mechanical Analyses of Calcifications and Fibrous Plaque Tissue in Carotid Arteries for Plaque Rupture Risk Assessment.
IEEE Trans. Biomed. Eng., 2021

A Quantitative Comparison of Epistemic Uncertainty Maps Applied to Multi-Class Segmentation.
CoRR, 2021

Automated Segmentation and Volume Measurement of Intracranial Carotid Artery Calcification on Non-Contrast CT.
CoRR, 2021

2020
Uncertainty-Based Segmentation of Myocardial Infarction Areas on Cardiac MR Images.
Proceedings of the Statistical Atlases and Computational Models of the Heart. M&Ms and EMIDEC Challenges, 2020

Quantitative Comparison of Monte-Carlo Dropout Uncertainty Measures for Multi-class Segmentation.
Proceedings of the Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical Image Analysis, 2020

2019
Increasing Accuracy of Optimal Surfaces Using Min-Marginal Energies.
IEEE Trans. Medical Imaging, 2019

Patterns of functional connectivity in an aging population: The Rotterdam Study.
NeuroImage, 2019

2017
Segmentation of Intracranial Arterial Calcification with Deeply Supervised Residual Dropout Networks.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017


  Loading...