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3D Medical Imaging

Project researchers

3D medical imaging is a growing sector thanks to the lates developments in automated image processing and 3D modeling. The activity deals with th euse of medical data, in terms of CT or visible imagery, for various applications and needs, such as realization of artificial hearths or brain anatomy. 

Total Artificial Hearts (TAH) are becoming more and more important devices to overcome heart diseases at any age. A TAH replaces natural heart functionally and anatomically. A TAH is an invasive devices therefore a correct design, realization and implantation, based on virtual techniques, is mandatory. The aim of the project is to realize a virtual fitting process to better design and implant artificial hearts. CT-based generated 3D geometries of cardiopulmonary and skeletal structures (atrium, ventricle, arteries, bones, etc.) are used for the virtual fitting of a TAH.

  

In the neuroscientific community there is an open debate how to collect quantitative information of the main neuroanatomical tracts. We have develop a method to support the process of acquiring metric information of the main pathways of the white matter of brain by means of photogrammetric acquisition and dense point cloud generation.

Representative Publications:

- Nocerino, E., Menna, F., Remondino, F., Sarubbo, S., De Benedictis, A., Olivetti, E., Avesani, P., 2017: Application of photogrammetry to brain anatomy. ISPRS Workshop on "Photogrammetric and computer vision techniques for video surveillance, biometrics and biomedicine". In press

 Gallo, M., D'Onofrio, A., Tarantini, G., Nocerino, E., Remondino, F., Gerosa, G., 2016: 3D-printing model for complex aortic transcatheter valve treatmentInternational Journal of Cardiology, Vol. 210, pp. 139–140

- Nocerino, E., Remondino, F., Uccheddu, F., Gallo, M. and Gerosa, G., 2016: 3D Modelling and Rapid Prototyping for Cardiovascular Surgical Planning - Two Case Studies. ISPRS Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XLI-B5, pp. 887-893 (poster presentation)

Partners: 
  • University of Padua (Italy)
  • Division of Neurosurgery, Department of Neurosciences, S. Chiara Hospital, Trento, Italy
  • Department of Neuroscience and Neurorehabilitation, Bambino Gesù Children's Hospital, Roma, Italy
  • Neuroinformatics Laboratory (NILab), Fondazione Bruno Kessler, Trento, Italy
Funding: 
Autonomous Province of Trento (PAT)