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Communication Dans Un Congrès Année : 2023

Machine-learning based guided diagnosis of parotid tumours from MRI

Résumé

Diagnosis of parotid gland tumours rely on magnetic resonance examination, fine-needle aspiration biopsy, or in some cases, invasive surgery that can damage facial nerves. In this work, we propose a machine learning model that can discriminate parotid tumours into histopathological subtypes from magnetic resonance imaging (MRI) scans, and further evaluate its impact on the diagnostic decisions of radiologists. We aim at improving the diagnosis of parotid neoplasms while avoiding any physical harm to patients. The radiologists improved their performance after observing the predictions of the algorithm. We conclude that machine-learning-based radiomics classification can assist radiologists.
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Dates et versions

hal-04407914 , version 1 (21-01-2024)

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  • HAL Id : hal-04407914 , version 1

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Arnaud Quillent, Samy Ammari, Emilie Chouzenoux, Víctor Elvira, Nathalie Lassau. Machine-learning based guided diagnosis of parotid tumours from MRI. ISBI 2023 - IEEE International Symposium on Biomedical Imaging, Apr 2023, Cartagena (Colombia), Colombia. ⟨hal-04407914⟩
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