activity
20242026
most citedlandmarker: a Toolkit for Anatomical Landmark Localization in 2D/3D Images

6 citations · 6 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2026

Proper Scoring Rules for Right-Censored Survival Data

Jef Jonkers, Glenn Van Wallendael, Luc Duchateau +1

Proper scoring rules provide a rigorous theoretical basis for the training and evaluation of probabilistic forecasts. In survival analysis, such forecasts describe the distribution…

cs.CV2025

Reliable uncertainty quantification for 2D/3D anatomical landmark localization using multi-output conformal prediction

Jef Jonkers, Frank Coopman, Luc Duchateau +2

Automatic anatomical landmark localization in medical imaging requires not just accurate predictions but reliable uncertainty quantification for effective clinical decision support…

cs.CV2025★ 6 cited

landmarker: a Toolkit for Anatomical Landmark Localization in 2D/3D Images

Jef Jonkers, Luc Duchateau, Glenn Van Wallendael +1

Anatomical landmark localization in 2D/3D images is a critical task in medical imaging. Although many general-purpose tools exist for landmark localization in classical computer vi…

cs.LG2024

Conformal Predictive Systems Under Covariate Shift

Jef Jonkers, Glenn Van Wallendael, Luc Duchateau +1

Conformal Predictive Systems (CPS) offer a versatile framework for constructing predictive distributions, allowing for calibrated inference and informative decision-making. However…

cs.LG2024

Conformal Convolution and Monte Carlo Meta-learners for Predictive Inference of Individual Treatment Effects

Jef Jonkers, Jarne Verhaeghe, Glenn Van Wallendael +2

Generating probabilistic forecasts of potential outcomes and individual treatment effects (ITE) is essential for risk-aware decision-making in domains such as healthcare, policy, m…