Pierre Ambrosini





Deep Learning, Machine Learning, Computer Vision, Image Analysis, Medical Images

Research

Journal Papers

P. Ambrosini, E. Hollemans, C. F. Kweldam, G. J. L. H. van Leenders, S. Stallinga and F. Vos, "Automated Detection of Cribriform Growth Patterns in Prostate Histology Images", Scientific Reports, 10, 14904, 2020.
P. Ambrosini, I. Smal, D. Ruijters, W. J. Niessen, A. Moelker and T. van Walsum, "A Hidden Markov Model for 3D Catheter Tip Tracking With 2D X-ray Catheterization Sequence and 3D Rotational Angiography", IEEE Transactions on Medical Imaging, vol. 36(3), pp. 757-768, 2017.
P. Ambrosini, D. Ruijters, W.J. Niessen, A. Moelker and T. van Walsum, "Continuous Roadmapping in Liver TACE Procedures Using 2D-3D Catheter-based Registration", International Journal of Computer Assisted Radiology and Surgery, vol. 10, pp. 1357-1370, 2015.

Conference Papers

P. Ambrosini, D. Ruijters, W.J. Niessen, A. Moelker and T. van Walsum, "Fully Automatic and Real-Time Catheter Segmentation in X-Ray Fluoroscopy", The 20th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Lecture Notes in Computer Science, vol. 10434, pp. 577-585, 2017.
H. Ma, P. Ambrosini and T. van Walsum, "Fast Prospective Detection of Contrast Inflow in X-ray Angiograms with Convolutional Neural Network and Recurrent Neural Network", The 20th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Lecture Notes in Computer Science, vol. 10434, pp. 453-461, 2017.
P. Ambrosini, I. Smal, D. Ruijters, W.J. Niessen, A. Moelker and T. van Walsum, "3D Catheter Tip Tracking in 2D X-ray Image Sequences Using a Hidden Markov Model and 3D Rotational Angiography", The 10th MICCAI Workshop on Augmented Environments for Computer-Assisted Interventions (AE-CAI), Lecture Notes in Computer Science, vol. 9365, pp. 38-49, 2015.
P. Ambrosini, D. Ruijters, A. Moelker, W.J. Niessen and T. van Walsum, "2D/3D Catheter-based Registration for Improved Image Guidance in TACE of Liver Tumors", The 5th International Conference on Information Processing in Computer-Assisted Interventions (IPCAI), Lecture Notes in Computer Science, vol. 8498, pp. 246-255, 2014.

Conference Abstracts

P. Ambrosini, D. Ruijters, W.J. Niessen, A. Moelker and T. van Walsum, "Catheter Segmentation in X-ray Fluoroscopy using Convolutional Neural Network", The 31th International Congress on Computer Assisted Radiology and Surgery (CARS), 2017.
P. Ambrosini, I. Smal, D. Ruijters, W.J. Niessen, A. Moelker and T. van Walsum, "3D Catheter Tip Tracking in 2D X-ray Image Sequences Using 3D Rotational Angiography", The 28th Conference of the International Society for Medical Innovation and Technology (SMIT), 2016.
E. Vast, P. Ambrosini and T. van Walsum, "Spatial Calibration of 2D/3D Ultrasound with the PLUS Framework and Electro-magnetic Tracking", 5th Dutch Conference on Bio-Medical Engineering, 2015.

Thesis Manuscript

P. Ambrosini, "Improved Image Guidance in TACE Procedures", ISBN 978-94-6323-480-1, 19 February 2019.

Supervision

Bachelor thesis supervision of T. Zonjee: "Developing an automatized tool for E. Coli cell segmentation using deep learning", TU Delft, 2019.
Master thesis supervision of M.A. van der Cammen: "2D Fluoroscopy and 3D Computed Tomography Registration for Minimally Invasive Liver Procedures", TU Delft, 2016-2017.



News

September 10, 2020 Our work on detection of cribriform growth patterns in prostate histology images has been pusblished in Scientific Reports.

June 22, 2017 Interview of Theo van Walsum at the Computer Assisted Radiology and Surgery (CARS) congress about our work on Catheter Segmentation in Fluoroscopy.