Comparative study of deep learning methods for the automatic segmentation of lung, lesion and lesion type in CT scans of COVID-19 patients. - Sofie Tilborghs; Ine Dirks; Lucas Fidon; Siri Willems; Tom Eelbode; Jeroen Bertels; Bart Ilsen; Arne Brys; Adriana Dubbeldam; Nico Buls; Panagiotis Gonidakis; Sebastián Amador Sánchez; et al. (CoRR, 2020)

Explainable-by-design Semi-Supervised Representation Learning for COVID-19 Diagnosis from CT Imaging. - Abel Díaz Berenguer; Hichem Sahli; Boris Joukovsky; Maryna Kvasnytsia; Ine Dirks; Mitchel Alioscha-Pérez; Nikos Deligiannis; Panagiotis Gonidakis; Sebastián Amador Sánchez; Redona Brahimetaj; Evgenia Papavasileiou; Jonathan Cheung-Wai Chan; et al. (CoRR, 2020)

Segmentation-Guided Coordinate Regression for Robust Landmark Detection on X-Rays: Application to Automated Assessment of Lower Limb Alignment. - Sebastián Amador Sánchez; Philippe van Overschelde; Jef Vandemeulebroucke (IEEE Access, 2024)

Optimization and Benchmarking of Image Segmentation for Improved Landmark Detection in Lower Limb X-Rays and Accurate Coronal Plane Alignment of the Knee Classification. - Sebastián Amador Sánchez; Ashkan Zarghami; Philippe van Overschelde; Jef Vandemeulebroucke (IEEE Access, 2025)