In space missions, medical control and any therapeutic suggestions are provided by control center on the ground. Indeed, although astronauts are highly trained, they need aid when performing 'complex' medical diagnosis or procedures. In general, medical imaging and plotting vs. time of physiological variables are routine medical procedures. Medical Imaging Techniques (MITs) are standard tools used by clinicians to diagnose, establish appropriate therapies, and/or plan for surgery. MITs consists of image acquisition, image transformation, and image visualization. Uncertainty affects each of these steps. It can degrade information and greatly influence doctors' decision making. In this article, we aim to summarize the current state of the art on the characterization of uncertainty existing in medical imaging. In addition, we briefly illustrate the open problems on the treatment of uncertainty in medical imaging.

Schirripa Spagnolo, G., Leccese, F. (2022). Medical Imaging: Artificial Intelligence (AI) and Decision Uncertainty - a Short Survey. In 2022 IEEE International Workshop on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering, MetroXRAINE 2022 - Proceedings (pp.110-115). Institute of Electrical and Electronics Engineers Inc. [10.1109/MetroXRAINE54828.2022.9967587].

Medical Imaging: Artificial Intelligence (AI) and Decision Uncertainty - a Short Survey

Schirripa Spagnolo G.;Leccese F.
2022-01-01

Abstract

In space missions, medical control and any therapeutic suggestions are provided by control center on the ground. Indeed, although astronauts are highly trained, they need aid when performing 'complex' medical diagnosis or procedures. In general, medical imaging and plotting vs. time of physiological variables are routine medical procedures. Medical Imaging Techniques (MITs) are standard tools used by clinicians to diagnose, establish appropriate therapies, and/or plan for surgery. MITs consists of image acquisition, image transformation, and image visualization. Uncertainty affects each of these steps. It can degrade information and greatly influence doctors' decision making. In this article, we aim to summarize the current state of the art on the characterization of uncertainty existing in medical imaging. In addition, we briefly illustrate the open problems on the treatment of uncertainty in medical imaging.
2022
978-1-6654-8574-6
Schirripa Spagnolo, G., Leccese, F. (2022). Medical Imaging: Artificial Intelligence (AI) and Decision Uncertainty - a Short Survey. In 2022 IEEE International Workshop on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering, MetroXRAINE 2022 - Proceedings (pp.110-115). Institute of Electrical and Electronics Engineers Inc. [10.1109/MetroXRAINE54828.2022.9967587].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11590/426288
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