2 citations · 4 across the 4 of their papers we have counts for
4 papers
Improving Uncertainty-Error Correspondence in Deep Bayesian Medical Image Segmentation
Prerak Mody, Nicolas F. Chaves-de-Plaza, Chinmay Rao +5
Increased usage of automated tools like deep learning in medical image segmentation has alleviated the bottleneck of manual contouring. This has shifted manual labour to quality as…
Deep learning for size-agnostic inverse design of random-network 3D printed mechanical metamaterials
Helda Pahlavani, Kostas Tsifoutis-Kazolis, Prerak Mody +3
Practical applications of mechanical metamaterials often involve solving inverse problems where the objective is to find the (multiple) microarchitectures that give rise to a given…
Report on AI-Infused Contouring Workflows for Adaptive Proton Therapy in the Head and Neck
Nicolas F. Chaves-de-Plaza, Prerak Mody, Klaus Hildebrandt +5
Delineation of tumors and organs-at-risk permits detecting and correcting changes in the patients' anatomy throughout the treatment, making it a core step of adaptive proton therap…
Comparing Bayesian Models for Organ Contouring in Head and Neck Radiotherapy
Prerak Mody, Nicolas Chaves-de-Plaza, Klaus Hildebrandt +3
Deep learning models for organ contouring in radiotherapy are poised for clinical usage, but currently, there exist few tools for automated quality assessment (QA) of the predicted…