29 citations · 29 across the 5 of their papers we have counts for
5 papers
Multi-Task Diffusion Approach For Prediction of Glioma Tumor Progression
Aghiles Kebaili, Romain Modzelewski, Jérôme Lapuyade-Lahorgue +3
Glioma, an aggressive brain malignancy characterized by rapid progression and its poor prognosis, poses significant challenges for accurate evolution prediction. These challenges a…
Differential-UMamba: Rethinking Tumor Segmentation Under Limited Data Scenarios
Dhruv Jain, Romain Modzelewski, Romain Herault +3
In data-scarce scenarios, deep learning models often overfit to noise and irrelevant patterns, which limits their ability to generalize to unseen samples. To address these challeng…
Predicting Patient Survival with Airway Biomarkers using nn-Unet/Radiomics
Zacharia Mesbah, Dhruv Jain, Tsiry Mayet +5
The primary objective of the AIIB 2023 competition is to evaluate the predictive significance of airway-related imaging biomarkers in determining the survival outcomes of patients…
AutoPETIII: The Tracer Frontier. What Frontier?
Zacharia Mesbah, Léo Mottay, Romain Modzelewski +4
For the last three years, the AutoPET competition gathered the medical imaging community around a hot topic: lesion segmentation on Positron Emitting Tomography (PET) scans. Each y…
Prediction of brain tumor recurrence location based on multi-modal fusion and nonlinear correlation learning
Tongxue Zhou, Alexandra Noeuveglise, Romain Modzelewski +4
Brain tumor is one of the leading causes of cancer death. The high-grade brain tumors are easier to recurrent even after standard treatment. Therefore, developing a method to predi…