Ferrante, Enzo

Anatomically constrained neural networks (ACNNS): application to cardiac image enhancement and segmentation

Oktay, O., Ferrante, E., Kamnitsas, K., Heinrich, M., Bai, W., Caballero, J., Cook, S. A., de Marvao, A., Dawes, T., O'Regan, D. P., et al. (2018) · IEEE Transactions on Medical Imaging

Medical Image Segmentation TechniquesAdvanced Neural Network Applications

Cited by 751

Gender imbalance in medical imaging datasets produces biased classifiers for computer-aided diagnosis

Larrazabal, A. J., Nieto, N., Peterson, V., Milone, D. H., & Ferrante, E. (2020) · Proceedings of the National Academy of Sciences

Artificial Intelligence in Healthcare and EducationEthics and Social Impacts of AI

Cited by 685

DeepMedic for Brain Tumor Segmentation

Kamnitsas, K., Ferrante, E., Parisot, S., Ledig, C., Nori, A. V., Criminisi, A., Rueckert, D., & Glocker, B. (2016) · Lecture Notes in Computer Science

Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques

Cited by 346

Multiclass semantic segmentation and quantification of traumatic brain injury lesions on head CT using deep learning: an algorithm development and multicentre validation study

Monteiro, M., Newcombe, V. F. J., Mathieu, F., Adatia, K., Kamnitsas, K., Ferrante, E., Das, T., Whitehouse, D., Rueckert, D., Menon, D. K., et al. (2020) · The Lancet Digital Health

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 162

ConfIC-RCA: Statistically Grounded Efficient Estimation of Segmentation Quality

Cosarinsky, M., Billot, R., Mansilla, L., Jimenez, G., Gaggión, N., Fu, G., Tirer, T., & Ferrante, E. (2025) · arXiv

Medical Image Segmentation TechniquesArtificial Intelligence in Healthcare and Education

Cited by 0