Zobrazeno 1 - 10
of 98
pro vyhledávání: '"Morotti Elena"'
Sparse-view Computed Tomography (CT) is an emerging protocol designed to reduce X-ray dose radiation in medical imaging. Traditional Filtered Back Projection algorithm reconstructions suffer from severe artifacts due to sparse data. In contrast, Mode
Externí odkaz:
http://arxiv.org/abs/2412.01703
Autor:
Bianchi, Davide, Serra, Sonia Colombo, Evangelista, Davide, Luo, Pengpeng, Morotti, Elena, Valbusa, Giovanni
The adoption of contrast agents in medical imaging protocols is crucial for accurate and timely diagnosis. While highly effective and characterized by an excellent safety profile, the use of contrast agents has its limitation, including rare risk of
Externí odkaz:
http://arxiv.org/abs/2407.10559
This paper focuses on the development of a space-variant regularization model for solving an under-determined linear inverse problem. The case study is a medical image reconstruction from few-view tomographic noisy data. The primary objective of the
Externí odkaz:
http://arxiv.org/abs/2404.16900
Autor:
Cevolini, Alberto, Morotti, Elena, Esposito, Elena, Romanelli, Lorenzo, Tisseur, Riccardo, Misani, Cristiano
The use of behavioural data in insurance is loaded with promises and unresolved issues. This paper explores the related opportunities and challenges analysing the use of telematics data in third-party liability motor insurance. Behavioural data are u
Externí odkaz:
http://arxiv.org/abs/2309.02814
Autor:
Merizzi, Fabio, Saillard, Perrine, Acquier, Oceane, Morotti, Elena, Piccolomini, Elena Loli, Calatroni, Luca, Dessì, Rosa Maria
The unprecedented success of image reconstruction approaches based on deep neural networks has revolutionised both the processing and the analysis paradigms in several applied disciplines. In the field of digital humanities, the task of digital recon
Externí odkaz:
http://arxiv.org/abs/2306.14209
In recent years, large convolutional neural networks have been widely used as tools for image deblurring, because of their ability in restoring images very precisely. It is well known that image deblurring is mathematically modeled as an ill-posed in
Externí odkaz:
http://arxiv.org/abs/2305.19774
The solution of linear inverse problems arising, for example, in signal and image processing is a challenging problem since the ill-conditioning amplifies, in the solution, the noise present in the data. Recently introduced algorithms based on deep l
Externí odkaz:
http://arxiv.org/abs/2211.13692
This paper proposes a new two-step procedure for sparse-view tomographic image reconstruction. It is called RISING, since it combines an early-stopped Rapid Iterative Solver with a subsequent Iteration Network-based Gaining step. So far, regularized
Externí odkaz:
http://arxiv.org/abs/2201.09777
Blur and noise corrupting Computed Tomography (CT) images can hide or distort small but important details, negatively affecting the diagnosis. In this paper, we present a novel gradient-based Plug-and-Play algorithm, constructed on the Half-Quadratic
Externí odkaz:
http://arxiv.org/abs/2102.07510
Digital Breast Tomosynthesis is an X-ray imaging technique that allows a volumetric reconstruction of the breast, from a small number of low-dose two-dimensional projections. Although it is already used in clinical setting, enhancing the quality of t
Externí odkaz:
http://arxiv.org/abs/2007.10039