09.00 - 9.15 Welcome

09.15 - 10.00 Keynote: Visual computing and machine learning: a medical perspective (MD M. Aurora Morales)

10.00 - 10.30 Contributed talk: Retinal blood vessels segmentation: improving state-of-the-art deep methods (V. Wargnier-Dauchelle, C. Simon-Chane, A. Histace)

10.30 - 11.00 Contributed talk: A new hybrid method for gland segmentation in histology images (L. Y. Wang, Y. Zhou and B. Matuszewski)

11.00 - 11.30 Coffee break

11.30 - 12.00 Contributed talk: Residual convolutional neural networks to automatically extract significant breast density features (F. Lizzi, F. Laruina, P. Oliva, A. Retico, M. E. Fantacci)

12.00 - 12.30 Contributed talk: Combining convolutional neural networks for multi-context microcalcification detection in mammograms (B. Savelli, C. Marrocco, A. Bria, M. Molinara, F. Tortorella)

12.30 - 13.00 Contributed talk: Classification of autism spectrum disorder through the Graph Fourier Transform of fMRI temporal signals projected on structural connectome (A. Brahim, M. H. El Hassani, N. Farrugia)

13.00 - 14.15 Lunch

14.15 - 15.00 Keynote: Recent developments in graph neural networks (Prof. Pietro LiĆ²)

15.00 - 15.30 Contributed talk: Radiomic and dosiomic profiling of paediatric medulloblastoma tumours treated with Intensity Modulated Radiation Therapy (C. Talamonti, S. Piffer, D. Greto, M. Mangoni, A. Ciccarone, P. Dicarlo, M. E. Fantacci, F. Fusi, P. Oliva, L. Palumbo, C. Frave, L. Livi, S. Pallotta, A. Retico)

15.30 - 16.00 Contributed talk: May radiomic data predict cancer aggressiveness? (D. Germanese, S. Colantonio, C. Caudai, M. A. Pascali, A. Barucci, N. Zoppetti, S. Agostini, E. Bertelli, L. Mercatelli, V. Miele, R. Carpi)

16.00 - 16.30 Closing remarks