180 citations · 199 across the 12 of their papers we have counts for
12 papers
Empirical investigation of 3D CT Foundation Models and Unsupervised Adaptation for Head and Neck Cancer Recurrence Prediction
Bilel Guetarni, Feryal Windal, David Pasquier +1
The rapid emergence of 3D CT foundation models has opened new avenues for predictive modeling from CT imaging, offering a compelling alternative to traditional radiomics which is k…
NoduLoCC2026: Lung Nodule Localization and Classification Contest from Chest X-Ray Images
Adnan Mustafic, Halim Benhabiles, Adnane Cabani +19
We propose NoduLoCC2026, a challenge on lung nodule detection and localization in chest X-ray images. We have provided a dataset for both tasks and received submissions from 5 inte…
SHREC 2025: Protein surface shape retrieval including electrostatic potential
Taher Yacoub, Camille Depenveiller, Atsushi Tatsuma +25
This SHREC 2025 track dedicated to protein surface shape retrieval involved 9 participating teams. We evaluated the performance in retrieval of 15 proposed methods on a large datas…
SHREC'25 Track on Multiple Relief Patterns: Report and Analysis
Gabriele Paolini, Claudio Tortorici, Stefano Berretti +10
This SHREC 2025 track focuses on the recognition and segmentation of relief patterns embedded on the surface of a set of synthetically generated triangle meshes. We report the meth…
Histopathology image embedding based on foundation models features aggregation for patient treatment response prediction
Bilel Guetarni, Feryal Windal, Halim Benhabiles +4
Predicting the response of a patient to a cancer treatment is of high interest. Nonetheless, this task is still challenging from a medical point of view due to the complexity of th…
Ensembling and Test Augmentation for Covid-19 Detection and Covid-19 Domain Adaptation from 3D CT-Scans
Fares Bougourzi, Feryal Windal Moula, Halim Benhabiles +2
Since the emergence of Covid-19 in late 2019, medical image analysis using artificial intelligence (AI) has emerged as a crucial research area, particularly with the utility of CT-…
A vision transformer-based framework for knowledge transfer from multi-modal to mono-modal lymphoma subtyping models
Bilel Guetarni, Feryal Windal, Halim Benhabiles +4
Determining lymphoma subtypes is a crucial step for better patient treatment targeting to potentially increase their survival chances. In this context, the existing gold standard d…
SuperpixelGridCut, SuperpixelGridMean and SuperpixelGridMix Data Augmentation
Karim Hammoudi, Adnane Cabani, Bouthaina Slika +3
A novel approach of data augmentation based on irregular superpixel decomposition is proposed. This approach called SuperpixelGridMasks permits to extend original image datasets th…
MaskedFace-Net -- A Dataset of Correctly/Incorrectly Masked Face Images in the Context of COVID-19
Adnane Cabani, Karim Hammoudi, Halim Benhabiles +1
The wearing of the face masks appears as a solution for limiting the spread of COVID-19. In this context, efficient recognition systems are expected for checking that people faces…
Deep Learning on Chest X-ray Images to Detect and Evaluate Pneumonia Cases at the Era of COVID-19
Karim Hammoudi, Halim Benhabiles, Mahmoud Melkemi +4
Coronavirus disease 2019 (COVID-19) is an infectious disease with first symptoms similar to the flu. COVID-19 appeared first in China and very quickly spreads to the rest of the wo…
Gamma-ray emission in alpha-particle reactions with C, Mg, Si, Fe
J. Kiener, J. Bundesmann, I. Deloncle +10
Cross sections for the strongest gamma-ray emission lines produced in alpha-particle reactions with C, Mg, Si, Fe have been measured in the range E_alpha = 50 - 90 MeV at the cente…
Gamma ray production cross sections in proton induced reactions on natural Mg, Si and Fe targets over the proton energy range 30 up to 66 MeV
W. Yahia-Chérif, S. Ouichaoui, J. Kiener +29
Gamma-ray excitation functions have been measured for 30, 42, 54 and 66 MeV proton beams accelerated onto C + O (Mylar), Mg, Si, and Fe targets of astrophysical interest at the sep…