publications

 

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2024

  • Svanera, M., Savardi, M., Signoroni, A., Benini*, S., & Muckli*, L. (2023). Fighting the scanner effect in brain segmentation with a progressive level-of-detail network trained on multi-site data. Medical Image Analysis (link).
  • Moia, S., H.T. Wang, A. Heinsfeld, D., Jarecka, Y., Yang, S., Heunis, M., Svanera, et al. and The Physiopy Community. “Proceedings of the OHBM Brainhack 2022”. In: Aperture Neuro 4. URL: link.

2023

  • Muckli*, L., Petro*, L. S., Abbatecola, C., Adeel, A., Bergmann, J., Deperrois, N., Destexhe, A., Kriegeskorte, N., Levelt, C. N., Maass, W., Morgan, A. T., Papale, P., Pennartz. Cyriel M. A., Peters, B., Petrovici, M. A., Phillips, W. A., Roelfsema, P. R., Sachdev, R. N. S., Seignette, K., Self, M., Smith, F., Storm, J., Svanera, M., Vanduffel, W., Senn, W. & Larkum, M., (2023). The cortical microcircuitry of predictions and context – A multi-scale perspective. Zenodo (link).
  • Ferrari, D., Savardi, M., Fracasso, A., Muckli, L., Benini, S., Signoroni, A., & Svanera, M., (2023). DeepThickness: A Deep Learning Method for Brain MRI Cortical Thickness Estimation. Annual Meeting of the Organization for Human Brain Mapping (OHBM23). Montreal, Canada, 22-26 July 2023 (poster presentation).
  • Ferrari, D., Savardi, M., Fracasso, A., Muckli, L., Benini, S., Signoroni, A., & Svanera, M., (2023). DeepThickness: A Deep Learning Method for Brain MRI Cortical Thickness Estimation. 2023 SINAPSE Annual Scientific Meeting. Glasgow, UK, 14 June 2023 (oral presentation).
  • Signoroni, A., Savardi, M., Farina, D., Benini, S., Coppola, E., Ferrari, D., Massussi, M., Curello, S., Svanera, M., & D’Ancona, G., Medical image interpretation challenges and research activities of the tAImedIA group at UniBS. Proceedings of the Italia Intelligenza Artificiale, pp. 118-123 – Thematic Workshops co-located with the 3rd CINI National Lab AIIS Conference on Artificial Intelligence (Ital IA 2023), Pisa, Italy, May 29-30, 2023.
  • Ferrari, D., Savardi, M., Fracasso, A., Muckli, L., Benini, S., Signoroni, A., & Svanera, M., (2023). DeepThickness: A Deep Learning Method for Brain MRI Cortical Thickness Estimation. Human Brain Project Summit 2023. Marseille, France, 28-31 March 2023 (poster presentation).

2022

  • Svanera, M., Savardi, M., Signoroni, A., Benini*, S., & Muckli*, L. (2022). Fighting the scanner effect in brain MRI segmentation with a progressive level-of-detail network trained on multi-site data. arXiv preprint arXiv:2211.02400 (link).
  • Svanera, M., Savardi, M., Signoroni, A., Benini*, S., & Muckli*, L. (2023). Fighting the Scanner Effect: a Coarse-to-Fine 3D Network for Multi-Site Brain MRI Segmentation. Annual Meeting of the Organization for Human Brain Mapping (OHBM22), Glasgow, UK, 19-23 June.

2021

  • Svanera, M., Benini, S., Bontempi, D., & Muckli, L. (2021). CEREBRUM-7T: Fast and Fully-volumetric Brain Segmentation of 7 Tesla MR Volumes. Human Brain Mapping (link).
  • Svanera, M., Morgan, A., Petro, L., Muckli, L. (2021). A Self-Supervised Deep Neural Network for Image Completion Resembles Early Visual Cortex fMRI Activity Patterns for Occluded Scenes. Journal of Vision (link).

2020

  • Svanera, M., Benini, S., Bontempi, D., & Muckli, L. (2020). CEREBRUM 7T: Fast and Fully-volumetric Brain Segmentation of 7 Tesla MR Volumes. bioRxiv (link).
  • Svanera, M., Morgan, A., Petro, L., Muckli, L. (2020). A Self-Supervised Deep Neural Network for Image Completion Resembles Early Visual Cortex fMRI Activity Patterns for Occluded Scenes. (link).
  • Bontempi, D., Benini, S., Signoroni, A., Svanera*, M., & Muckli*, L. (2020). CEREBRuM: a Convolutional Encoder-decodeR for Fully Volumetric Fast sEgmentation of BRain MRI. Medical Imaging Analysis (link).
  • Svanera, M., S. Benini, D. Bontempi, A. Fracasso, L. Muckli, “Fast brain segmentation of out-of-the-scanner MR 7T volumes using deep learning”, in Annual Meeting of the Organization for Human Brain Mapping (OHBM 2020), Montreal, Canada, June 26-30, 2020. (poster)

2019

  • Kovács, A. B., Raz, G., Valente, G., Svanera, M., & Benini, S. (2019). A Robust Neural Fingerprint of Cinematic Shot-Scale. Projections13(3), 23-52 (link).
  • Bontempi, D., Benini, S., Signoroni, A., Svanera*, M., & Muckli*, L. (2019). CEREBRuM: a Convolutional Encoder-decodeR for Fully Volumetric Fast sEgmentation of BRain MRI. arXiv preprint arXiv:1909.05085 (link).
  • Svanera, M., Savardi, M., Signoroni, A., Kovács, A. B., & Benini, S. (2019). Who is the film’s director? Authorship recognition based on shot features. IEEE MultiMedia (link).
  • Svanera, M., Savardi, M., Benini, S., Signoroni, A., Raz, G., Hendler, T., R. Goebel, & Valente, G. (2019). Transfer learning of deep neural network representations for fMRI decoding. Journal of Neuroscience Methods (link).
  • Bontempi, D., S. Benini, A. Signoroni, L. Muckli*, and Svanera M.*. “Fast Brain MRI Segmentation Using a Volumetric Deep Learning Approach”. In: 2019 Conference on Cognitive Computational Neuroscience (CCN) (link).

2018

  • Svanera, M., Savardi, M., Signoroni, A., Kovács, A. B., & Benini, S. (2018). Who is the director of this movie? Automatic style recognition based on shot features. arXiv preprint arXiv:1807.09560 (link).
  • Muhammad, U. R., Svanera, M., Leonardi, R., & Benini, S. (2018). Hair detection, segmentation, and hairstyle classification in the wild. Image and Vision Computing71, 25-37 (link).
  • Svanera M., A. T. Morgan, L. S. Petro, and L. Muckli. “Unsupervised deep neural network for fMRI feedback modelling”. In: 2018 Conference on Cognitive Computational Neuroscience (CCN). (link).

2017

  • Raz, G., Svanera, M., Singer, N., Gilam, G., Cohen, M. B., Lin, T., … & Goebel, R. (2017). Robust inter-subject audiovisual decoding in functional magnetic resonance imaging using high-dimensional regression. Neuroimage163, 244-263 (link).
  • Svanera, M., Benini, S., Raz, G., Hendler, T., Goebel, R., & Valente, G. (2017). Deep driven fMRI decoding of visual categories. arXiv preprint arXiv:1701.02133 (link).

2016

  • Benini, S., Svanera, M., Adami, N., Leonardi, R., & Kovács, A. B. (2016). Shot scale distribution in art films. Multimedia Tools and Applications75(23), 16499-16527 (link).
  • Svanera, M., Muhammad, U. R., Leonardi, R., & Benini, S. (2016, September). Figaro, hair detection and segmentation in the wild. In 2016 IEEE International Conference on Image Processing (ICIP) (pp. 933-937). IEEE (link).
  • Gordiychuk, A., Svanera, M., Benini, S., & Poesio, P. (2016). Size distribution and Sauter mean diameter of micro bubbles for a Venturi type bubble generator. Experimental Thermal and Fluid Science70, 51-60 (link).

2015

  • Svanera, M., Benini, S., Adami, N., Leonardi, R., & Kovács, A. B. (2015, June). Over-the-shoulder shot detection in art films. In 2015 13th International Workshop on Content-Based Multimedia Indexing (CBMI) (pp. 1-6). IEEE (link).