Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Elena Morotti"'
Autor:
Fabio Merizzi, Perrine Saillard, Oceane Acquier, Elena Morotti, Elena Loli Piccolomini, Luca Calatroni, Rosa Maria Dessì
Publikováno v:
Heritage Science, Vol 12, Iss 1, Pp 1-22 (2024)
Abstract 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 digi
Externí odkaz:
https://doaj.org/article/8922a12fe008422ab46931bd69b416e9
Publikováno v:
Journal of Imaging, Vol 9, Iss 7, p 133 (2023)
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:
https://doaj.org/article/5a47591ae8a0467c8e29d3f4291e7b77
Publikováno v:
Journal of Imaging, Vol 7, Iss 8, p 139 (2021)
Deep Learning is developing interesting tools that are of great interest for inverse imaging applications. In this work, we consider a medical imaging reconstruction task from subsampled measurements, which is an active research field where Convoluti
Externí odkaz:
https://doaj.org/article/22d4837d517b40909c08147bbe0a6e62
A Model-Based Optimization Framework for Iterative Digital Breast Tomosynthesis Image Reconstruction
Autor:
Elena Loli Piccolomini, Elena Morotti
Publikováno v:
Journal of Imaging, Vol 7, Iss 2, p 36 (2021)
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 the clinical setting, enhancing the quality
Externí odkaz:
https://doaj.org/article/a57267b03273458a95255adf0fb86dcc
Autor:
Elena Morotti, Bruno Battaglia, Raffaella Fabbri, Roberto Paradisi, Stefano Venturoli, Cesare Battaglia
Publikováno v:
International Journal of Fertility and Sterility, Vol 7, Iss 4, Pp 301-312 (2014)
Background: To verify if in lean polycystic ovary syndrome (PCOS) patients, the smok- ing habitude might increase the risk of cardiovascular (CV) disease. Materials and Methods: In this prospective observational study, eighty-one women were divided i
Externí odkaz:
https://doaj.org/article/efc20a2d7c38437e93148d3736122da3
Publikováno v:
Journal of Imaging; Volume 9; Issue 7; Pages: 133
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
Autor:
Cesare Battaglia, Elena Morotti, Elisa Montaguti, Giacomo Mariacci, Fabio Facchinetti, Gianluigi Pilu
Publikováno v:
European Journal of Obstetrics & Gynecology and Reproductive Biology. 270:105-110
First trimester miscarriage is a multifactorial event. Various angiogenic factors have been proposed as possible early markers of non-viable pregnancies. The aim of the present study was to evaluate the systemic nitric oxide (NO) production in health
Autor:
Elena Morotti, Elena Loli Piccolomini
Publikováno v:
Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging ISBN: 9783030030094
Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging ISBN: 9783030986605
Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging ISBN: 9783030986605
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::379684e941a90d7d5e77005b79b7c95e
https://doi.org/10.1007/978-3-030-03009-4_123-1
https://doi.org/10.1007/978-3-030-03009-4_123-1
Autor:
Lorenzo Donatiello, Gustavo Marfia, Elena Morotti, Jari Tarabelli, Lorenzo Stacchio, Marco Roccetti
The ongoing development of eXtended Reality (XR) technologies is supporting a rapid increase of their performances along with a progressive decrease of their costs, making them more and more attractive for a large class of consumers. As a result, the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a0364af1c903078de7801148b06c7b85
https://hdl.handle.net/11585/838028
https://hdl.handle.net/11585/838028
Publikováno v:
Computerized Medical Imaging and Graphics. 103:102156
Medical image reconstruction from low-dose tomographic data is an active research field, recently revolutionized by the advent of deep learning. In fact, deep learning typically yields superior results than classical optimization approaches, but unst