Zobrazeno 1 - 10
of 13 422
pro vyhledávání: '"medical imaging applications"'
Autor:
Ferrante, Enzo, Echeveste, Rodrigo
Recently, the research community of computerized medical imaging has started to discuss and address potential fairness issues that may emerge when developing and deploying AI systems for medical image analysis. This chapter covers some of the pressin
Externí odkaz:
http://arxiv.org/abs/2407.16953
Autor:
Ballester, Manuel, Kaspar, Jaromir, Massanes, Francesc, Banerjee, Srutarshi, Vija, Alexander Hans, Katsaggelos, Aggelos K.
Photon-counting detectors based on CZT are essential in nuclear medical imaging, particularly for SPECT applications. Although CZT detectors are known for their precise energy resolution, defects within the CZT crystals significantly impact their per
Externí odkaz:
http://arxiv.org/abs/2405.13168
Autor:
De Santi, Lisa Anita1,2 (AUTHOR) lisa.desanti@phd.unipi.it, Piparo, Franco Italo1 (AUTHOR) f.piparo@studenti.unipi.it, Bargagna, Filippo1,2 (AUTHOR) filippo.bargagna@phd.unipi.it, Santarelli, Maria Filomena3 (AUTHOR) santarel@ifc.cnr.it, Celi, Simona2 (AUTHOR), Positano, Vincenzo2 (AUTHOR) positano@ftgm.it
Publikováno v:
BioMedInformatics. Dec2024, Vol. 4 Issue 4, p2149-2172. 24p.
Akademický článek
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Multi-task learning (MTL) is a powerful approach in deep learning that leverages the information from multiple tasks during training to improve model performance. In medical imaging, MTL has shown great potential to solve various tasks. However, exis
Externí odkaz:
http://arxiv.org/abs/2309.03837
This work highlights the significance of equivariant networks as efficient and high-performance approaches for tomography applications. Our study builds upon the limitations of conventional Convolutional Neural Networks (CNNs), which have shown promi
Externí odkaz:
http://arxiv.org/abs/2307.03298
Akademický článek
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Publikováno v:
In Arthroscopy: The Journal of Arthroscopic and Related Surgery January 2024