Visual assessment of AI-reconstructed knee MRI: A pilot study

AI can reduce scan time without lowering image quality, improving workflow and patient throughput. Understanding how acquisition parameters affect image quality and artefacts is crucial when integrating AI reconstruction into protocols.

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Publication Details

Journal
Radiography
Published
2026-03-03
DOI
https://doi.org/10.1016/j.radi.2026.103380
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Visual assessment of AI-reconstructed knee MRI: A pilot study

S.S. Ghotra, L. Gallus, L. Buttex, J. McNulty et al.
Radiography
Artificial Intelligence in Healthcare and Education
article

Visual assessment of AI-reconstructed knee MRI: A pilot study

S.S. Ghotra, L. Gallus, L. Buttex, J. McNulty, A. McGee, C. Sá dos Reis, Y. Cottier
article en

Abstract

AI can reduce scan time without lowering image quality, improving workflow and patient throughput. Understanding how acquisition parameters affect image quality and artefacts is crucial when integrating AI reconstruction into protocols.

RadiographyVol. 32(4)
University College Dublin (IE), HES-SO University of Applied Sciences and Arts Western Switzerland (CH), University of St.Gallen (CH), Centre Hospitalier Universitaire Vaudois (CH), Centre d'Imagerie BioMedicale (CH), University of Lausanne (CH)
Openalex Percentile: Top 39%
Artificial Intelligence in Healthcare and Education
DOIOpen Access PDFOpenAlex
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