Davide Boschetto

Davide Boschetto photo

Davide Boschetto, born in Padova in 1987, obtained his PhD in Image Analysis at IMT School for Advanced Studies on December 2, 2016, defeding his PhD thesis titled "Quantitative methods for computer aided decision support systems in confocal laser endomicroscopy imaging of the gastrointestinal tract".

He previously received a B.Sc. degree in Biomedical Engineering in 2009 and a M.Sc. degree in Bioengineering in 2012, both from the University of Padova. For his MSc thesis, the use of Compressed Sensing in DSC-MRI was analyzed, with Prof. Enrico Grisan as Supervisor.

At the beginning of his PhD (starting Feb. 2013) he worked on problems regarding Myocardial Image Registration in Cardiac BOLD MRI stacks, performing time-series analysis to identify local differences in oxygenation among different myocardial territories, under the supervision of Prof. Sotirios Tsaftaris, with Dr. Cristian Rusu and Dr. Rita Morisi.

He then focused on developing a pipeline for a novel Computer-Aided Decision Support System (CADSS) for Endoscopy, particularly regarding the gastrointestinal (GI) tract, with high resolution datasets obtained from colonoscopies and gastroscopies, both with confocal endomicroscopy and white light / NBI endoscopies, working as an external member in the FAIR group at the University of Padova. His advisors were Prof. Enrico Grisan and Prof. Guido Caldarelli, and his thesis was reviewed by Dr. Stefano Realdon (Veneto Institute of Oncology) and Prof. Miguel Coimbra (University of Porto).

He won the AIDA-E (Analysis of Images to detect abnormalities in Endoscopy) challenge ("Gastric chromoendoscopy images in cancer surveillance") at IEEE International Symposium on Biomedical Imaging 2016, held in Prague, Czech Republic.

He worked for one year as Data Scientist at Previnet S.p.A. in Preganziol, Treviso, dealing with Natural Language Processing, general data analysis, predictive modeling and data mining.

From August 2017, he holds the position of Deep Learning Specialist at Microtec GmbH, in Mestre (Venice), studying the latest trends in the field for solving his firm's and its clients' problems (hard to solve with traditional methods), using Keras/Tensorflow, Pytorch and/or internally developed frameworks.



  1. D. Boschetto, E. Grisan, Superpixel-based classification of gastric chromoendoscopy images, SPIE Medical Imaging 2017, Orlando, Florida, USA, February 11th - 16th, 2017.
  2. D. Boschetto, H. Mirzaei, R. Leong, E. Grisan, Superpixel-based automatic segmentation of villi in confocal endomicroscopy, IEEE International Conference on Biomedical and Health Informatics (BHI) 2016, February 24-27, Las Vegas, Nevada, USA.
  3. D. Boschetto, G. Gambaretto, E. Grisan, Automatic Classification of Endoscopic Images for Premalignant Conditions of the Esophagus, SPIE Medical Imaging 2016, San Diego, California, USA, February 27th - March 3rd, 2016.
  4. D. Boschetto, G. Di Claudio, H. Mirzaei, R. Leong, E. Grisan, Automatic Classification of Small Bowel Mucosa Alterations in Celiac Disease for Confocal Laser Endomicroscopy, SPIE Medical Imaging 2016, San Diego, California, USA, February 27th - March 3rd, 2016.
  5. D. Boschetto, H. Mirzaei, R. Leong and E. Grisan, Detection and density estimation of goblet cells in confocal endoscopy for the evaluation of celiac disease, 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), August 25-29 2015.
  6. D. Boschetto, H. Mirzaei, R. Leong, G. Tarroni and E. Grisan, Semiautomatic detection of villi in confocal endoscopy for the evaluation of celiac disease, 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), August 25-29 2015.
  7. C. Rusu, R. Morisi, D. Boschetto, R. Dharmakumar and S. A. Tsaftaris, Synthetic Generation of Myocardial Blood-oxygen-level-dependent MRI Time Series via Structural Sparse Decomposition Modeling, IEEE Trans. Med. Imaging, 33 (7), pp. 1422-1433, 2014.
  8. D. Boschetto, C. Rusu, R. Dharmakumar, S. A. Tsaftaris, Temporal and Spatial Variation of Baseline Myocardial BOLD Signal Intensity in Cardiac Phase-Resolved BOLD MRI: A Potentially Revealing Insight into Dynamic Changes in Myocardial Oxygenation, Joint Annual Meeting ISMRM-ESMRMB 2014, SMRT 23rd Annual Meeting, Milan, Italy, p. 2383, 2014.
  9. D. Boschetto, P. Di Prima, M. Castellaro, A. Bertoldo, E. Grisan, Baseline constrained reconstruction of DSC-MRI data tracer kinetics from sparse Fourier data, 11th IEEE International Symposium on Biomedical Imaging (ISBI 2014), April 29th - May 2nd, Beijing, China, pp. 321-4, 2014.
  10. D. Boschetto, M. Castellaro, P. Di Prima, A. Bertoldo, E. Grisan, Reconstruction of DSC-MRI data from sparse data exploiting temporal redundancy and contrast localization, XIII Mediterranean Conference on Medical and Biological Engineering and Computing 2013, IFMBE Proceedings Volume 41, pp 225-228, 2014.