2 citations · 3 across the 4 of their papers we have counts for
4 papers
Deep learning automates bidimensional and volumetric tumor burden measurement from MRI in pre- and post-operative glioblastoma patients
Jakub Nalepa, Krzysztof Kotowski, Bartosz Machura +11
Tumor burden assessment by magnetic resonance imaging (MRI) is central to the evaluation of treatment response for glioblastoma. This assessment is complex to perform and associate…
Introducing the "opacity" for IMPT planning: can it improve robustness and quality of plans?
F. Arcadu
Intensity modulated proton therapy (IMPT) provides highly conformal dose distributions through the application of multiple, angularly spaced fields, each applying an ad-hoc pattern…
On the crucial impact of the coupling projector-backprojector in iterative tomographic reconstruction
Filippo Arcadu, Marco Stampanoni, Federica Marone
The performance of an iterative reconstruction algorithm for X-ray tomography is strongly determined by the features of the used forward and backprojector. For this reason, a large…
Improving analytical tomographic reconstructions through consistency conditions
Filippo Arcadu, Jakob Vogel, Marco Stampanoni +1
This work introduces and characterizes a fast parameterless filter based on the Helgason-Ludwig consistency conditions, used to improve the accuracy of analytical reconstructions o…