Get our free extension to see links to code for papers anywhere online!

Chrome logo  Add to Chrome

Firefox logo Add to Firefox
Picture for Daniel Bos

Daniel Bos
Alert button

Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands, Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands

Computer-aided diagnosis and prediction in brain disorders


Jun 29, 2022
Vikram Venkatraghavan, Sebastian R. van der Voort, Daniel Bos, Marion Smits, Frederik Barkhof, Wiro J. Niessen, Stefan Klein, Esther E. Bron

Add code
Alert button

Figure 1 for Computer-aided diagnosis and prediction in brain disorders
Figure 2 for Computer-aided diagnosis and prediction in brain disorders
Figure 3 for Computer-aided diagnosis and prediction in brain disorders

   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

A Quantitative Comparison of Epistemic Uncertainty Maps Applied to Multi-Class Segmentation


Sep 22, 2021
Robin Camarasa, Daniel Bos, Jeroen Hendrikse, Paul Nederkoorn, M. Eline Kooi, Aad van der Lugt, Marleen de Bruijne

Add code
Alert button

Figure 1 for A Quantitative Comparison of Epistemic Uncertainty Maps Applied to Multi-Class Segmentation
Figure 2 for A Quantitative Comparison of Epistemic Uncertainty Maps Applied to Multi-Class Segmentation
Figure 3 for A Quantitative Comparison of Epistemic Uncertainty Maps Applied to Multi-Class Segmentation
Figure 4 for A Quantitative Comparison of Epistemic Uncertainty Maps Applied to Multi-Class Segmentation
* 39 pages, 22 figures, to be published in Journal of Machine Learning for Biomedical Imaging for the Special Issue: Uncertainty for Safe Utilization of Machine Learning in Medical Imaging (UNSURE) 2020 
   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Automated Segmentation and Volume Measurement of Intracranial Carotid Artery Calcification on Non-Contrast CT


Jul 20, 2021
Gerda Bortsova, Daniel Bos, Florian Dubost, Meike W. Vernooij, M. Kamran Ikram, Gijs van Tulder, Marleen de Bruijne

Add code
Alert button

Figure 1 for Automated Segmentation and Volume Measurement of Intracranial Carotid Artery Calcification on Non-Contrast CT
Figure 2 for Automated Segmentation and Volume Measurement of Intracranial Carotid Artery Calcification on Non-Contrast CT
Figure 3 for Automated Segmentation and Volume Measurement of Intracranial Carotid Artery Calcification on Non-Contrast CT
Figure 4 for Automated Segmentation and Volume Measurement of Intracranial Carotid Artery Calcification on Non-Contrast CT
* Accepted for publication in Radiology: Artificial Intelligence (https://pubs.rsna.org/journal/ai), which is published by the Radiological Society of North America (RSNA) 
   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Segmentation of Intracranial Arterial Calcification with Deeply Supervised Residual Dropout Networks


Jun 04, 2017
Gerda Bortsova, Gijs van Tulder, Florian Dubost, Tingying Peng, Nassir Navab, Aad van der Lugt, Daniel Bos, Marleen de Bruijne

Add code
Alert button

Figure 1 for Segmentation of Intracranial Arterial Calcification with Deeply Supervised Residual Dropout Networks
Figure 2 for Segmentation of Intracranial Arterial Calcification with Deeply Supervised Residual Dropout Networks
Figure 3 for Segmentation of Intracranial Arterial Calcification with Deeply Supervised Residual Dropout Networks
Figure 4 for Segmentation of Intracranial Arterial Calcification with Deeply Supervised Residual Dropout Networks
* Accepted for MICCAI 2017 
   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email