Search Results - "Gianoli, C."

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    Ballast water compliance monitoring: A new application for ATP by Lo Curto, A., Stehouwer, P., Gianoli, C., Schneider, G., Raymond, M., Bonamin, V.

    Published in Journal of sea research (01-03-2018)
    “…The coming into force of the USCG ballast water regulations and the IMO ballast water management convention resulted in the development of several technologies…”
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    Journal Article
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    An overview of recent developments in FLUKA PET tools by Augusto, R.S., Bauer, J., Bouhali, O., Cuccagna, C., Gianoli, C., Kozłowska, W.S., Ortega, P.G., Tessonnier, T., Toufique, Y., Vlachoudis, V., Parodi, K., Ferrari, A.

    Published in Physica medica (01-10-2018)
    “…•FLUKA PET tools: a dedicated FLUKA package for PET simulations.•Simulation of hadrontherapy irradiation scenarios, with in-beam PET, is now possible.•The…”
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    Journal Article
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    Upgrading an Integrating Carbon-Ion Transmission Imaging System With Active Scanning Beam Delivery Toward Low Dose Ion Imaging by Magallanes, L., Meyer, S., Gianoli, C., Kopp, B., Voss, B., Jakel, O., Brons, S., Gordon, J., Parodi, K.

    “…The dosimetric advantages of ion therapy come at the cost of an increased sensitivity to range inaccuracies in the treatment planning and delivery stages. This…”
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    Journal Article
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    4D ML reconstruction as a tool for volumetric PET‐based treatment verification in ion beam radiotherapy by De Bernardi, E., Ricotti, R., Riboldi, M., Baroni, G., Parodi, K., Gianoli, C.

    Published in Medical physics (Lancaster) (01-02-2016)
    “…Purpose: An innovative strategy to improve the sensitivity of positron emission tomography (PET)‐based treatment verification in ion beam radiotherapy is…”
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    Journal Article
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    ML segmentation strategies for object interference compensation in FDG-PET lesion quantification by De Bernardi, E, Fiorani Gallotta, F, Gianoli, C, Zito, F, Gerundini, P, Baselli, G

    “…Quantification of lesion activity by FDG uptake in oncological PET is severely limited by partial volume effects. A maximum likelihood (ML) expectation…”
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    Journal Article
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