medical imaging

Differentiable Boundary Point Extraction for Weakly Supervised Star-shaped Object Segmentation

Robin Camarasa, Hoel Kervadec, Daniel Bos, Marleen de Bruijne (Talk)

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

Robin Camarasa, Daniel Bos, Jeroen Hendrikse, Paul Nederkoorn, Eline Kooi, Aad van der Lugt, Marleen de Bruijne

Quantitative Comparison of Monte-Carlo Dropout Uncertainty Measures for Multi-class Segmentation

Robin Camarasa, Daniel Bos, Jeroen Hendrikse, Paul Nederkoorn, Eline Kooi, Aad van der Lugt, Marleen de Bruijne (Talk)

Erasmus MC - Ph.D. student

Ph.D. project focused on uncertainty and interpretability of Convolutional Neural Networks, applied to cardiovascular diseases.

DataGenius - Internship

6-month data sciences internship covering various type of projects from Business Intelligence to theoretical Machine Learning (Spiking Neural Networks) for customers

Erasmus MC - Internship

3-month internship. Participation to two international medical imaging challenges.