Philippe C. Cattin

4D Pencil Beam Treatment Plan with Conditional Weight Predictions

The results suggest that extending this approach to full treatment prediction is feasible but requires further investigation, and the acceleration of 4D treatment generation via pencil beam weight prediction takes us one step closer to the feasibility of treating mobile targets with simplified, gantry-less and magnet-f...

Generalizing Soft Tissue Deformation and Force Prediction Across Material Stiffness and Geometry

Accurate soft tissue simulation is essential for surgical training, pre-operative planning, and haptic feedback systems. While learning-based surrogate models trained on data using the finite element method (FEM) offer a promising path to real-time inference, their reliability depends on well-calibrated constitutive mo...

Age-Residualized Physiological Biomarkers and Gradient-Boosted Trees for Predicting Cognitive Impairment from Polysomnography

Field-of-View Extension in Dental Cone-Beam CT via Implicit Neural Representations and Diffusion Model-Based Refinement

A three-stage framework that consists of an implicit neural representation (INR) for estimating missing parts of the truncated projection data, an iterative reconstruction for generating a secondary volumetric image with improved anatomical consistency and a fast diffusion model for image enhancement is proposed.

SA-Profile: Automated Sulcus Angle Profiling from Super-Resolution MRI

An automatic framework for continuous SA profiling from super-resolved MR volumes is proposed, extending conventional SA assessment to a continuous profile-based description of trochlear morphology without additional imaging, while remaining conceptually linked to current clinical assessment.