Medical images are often affected by noise or artifacts. A MOX research topic concerns the **reduction of metal artifacts (MAR)** in X-ray computerized tomography (CT), and the development of techniques and procedures for the pre-processing of medical images.

**segmentation**of different vessel district such as the carotid arteries, the aorta artery, the coronary tree and the heart chambers from different image modalities (e.g. CT scans, angio-CT scans, MRI images, etc…). To this aim some general purpose methods have been developed or adapted to ours applications. Moreover, specific methods have been studied and developed such as:

- automatic coronary tree generation from centerlines,
- plaque reconstruction in carotid arteries of patients with atherosclerosis,
- automatic segmentation of the aorta,
- semi-automatic left ventricle segmentation,
- parametric active contour segmentation methods,
- level set image segmentation through adaptive finite element methods,
- aortic valve leaflets reconstruction from CT images.

Another focus of this task is the development of methods for the analysis and the reconstruction of **blood flow information** from both *phase contrast images* (in which the pixel brightness is proportional to the velocity of the material) and from *eco doppler* signals. Velocity field are extremely useful in order to impose patient-specific boundary conditions, to perform validation of numerical simulations and in a data assimilation framework.

In addition to anatomical and velocity informations, also the knowledge of the **three dimensional (3D) motion field** of the arteries such as the carotid bifurcation is important for several applications, such as vessel compliance estimation, data assimilation or fluid-structure interaction validation. A widespread non-invasive method for imaging wall motion in clinical settings is 2D-cine-MRI, whereby a set of individual slices are acquired along the carotid bifurcation in which carotid wall motion is recorded. Within the Image Data Processing task , we proposed a new method to reconstruct the complete 3D carotid motion field starting from the 2D-cine-MRI slices and a static 3D-MRI data.

**Publications: **

- E. Faggiano, T. Lorenzi, A. Quarteroni,
*Metal artefact reduction in computed tomography images by a fourth-order total variation flow*,**Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization**(2014), DOI: 10.1080/21681163.2014.94062 - E. Faggiano, L. Antiga,
*Interpolation-based reconstruction of human carotid dynamics from magnetic resonance images*,**Proceedings of SIMAI 2012 Biannual Congress, MSP – Computational and statistical methods for biomedical applications ,**Torino, 25-28 June 2012 - J. Bonnemain, E. Faggiano, S. Deparis, A. Quarteroni, and L. von Segesser.
*Segmentation and grid generation for numerical simulations of vad connections with patient-specific data*.**INTERNATIONAL JOURNAL OF ARTIFICIAL ORGANS**Volume: 34 Issue: 8 Special Issue: SI Pages: 671-671, 2011. - M. Sangalli, P. Secchi, S. Vantini, A. Veneziani,
*Efficient estimation of 3-dimensional centerlines of inner carotid arteries and their curvature functions by free knot regression splines*,**Journal of the Royal Statistical Society Ser. C, Applied Statistics,**58(3), pp. 285-306 (2009) - R. Ponzini, C. Vergara, A. Redaelli, A. Veneziani,
*Reliable CFD-based estimation of flow rate in haemodynamics measures*,**Ultrasound in Medicine & Biology**, 32(10), pp. 1545-1555 (2006) - G. Abdoulaev, S. Cadeddu, G. Delussu, M. Donizelli, C. Manzi, L. Formaggia, A. Giachetti, E. Gobbetti, A. Leone, P. Pili, A. Schenine, M. Tuveri, A. Varone, A. Veneziani, G. Zanetti, A. Zorcolo,
*ViVA: The Virtual Vascular Project*,**IEEE Transactions on Information Technology in Medicine**, 4(2), pp. 268-274 (1998)

**Thesis:**

- M. Fedele –
*A Patient-Specific Aortic Valve Model based on Moving Resistive Immersed Surfaces*, MSc in Mathematical Engeneering, Politecnico di Milano – Advisors: A. Quarteroni, E. Faggiano A. Laadhari – A.Y. ’12-’13 - R. Ferrero
*–**Numerical study of the fluid-dynamics in patient-specific coronary artery bypass grafts*– MSc in Mathematical Engeneering, Politecnico di Torino – Advisors: L. Preziosi, A. Quarteroni, E. Faggiano – A.Y. ’12-’13 - F. Pizzi
*–**Un approccio probabilistico per la segmentazione di immagini mediche tramite contorni attivi parametrici*– MSc in Mathematical Engeneering, Politecnico di Milano – Advisors: A. Guglielmi, E. Faggiano*– A.Y. ’12-’13* - M. Haile –
*Restauro di immagini tomografiche mediche tramite l’uso di metodi di image inpainting*– MSc in Mathematical Engeneering, Politecnico di Milano*–*Advisors: S. Perotto, E. Faggiano*– A.Y. ’12-’13* - N. Papucci –
*Adattazione anisotropa di griglia applicata alla segmentazione di immagini*, MSc in Mathematical Engeneering, Politecnico di Milano – Advisor: S. Perotto –*A.Y. ’11-’12* - E. Maculan –
*Simulazioni fluidodinamiche in vasi deformabili con moto della parete ricostruito da immagini mediche*, MSc in Mathematical Engeneering, Politecnico di Milano – Advisor: A. Veneziani – A.Y. ’06-’07 - L. Cattaneo and C. Colciago –
*Analisi della diffusività di materiali porosi a partire da immagini – MSc in Mathematical Engeneering, Politecnico di Milano –*Advisor: P. Zunino*– A.Y. ’06-’07*