Surgical optomics: hyperspectral imaging and deep learning towards precision intraoperative automatic tissue recognition-results from the EX-MACHYNA trial.
Fiche publication
Date publication
mai 2024
Journal
Surgical endoscopy
Auteurs
Membres identifiés du Cancéropôle Est :
Pr MARESCAUX Jacques, Pr PESSAUX Patrick
Tous les auteurs :
Bannone E, Collins T, Esposito A, Cinelli L, De Pastena M, Pessaux P, Felli E, Andreotti E, Okamoto N, Barberio M, Felli E, Montorsi RM, Ingaglio N, Rodríguez-Luna MR, Nkusi R, Marescaux J, Hostettler A, Salvia R, Diana M
Lien Pubmed
Résumé
Hyperspectral imaging (HSI), combined with machine learning, can help to identify characteristic tissue signatures enabling automatic tissue recognition during surgery. This study aims to develop the first HSI-based automatic abdominal tissue recognition with human data in a prospective bi-center setting.
Mots clés
Convolutional neural networks, Deep learning, Hyperspectral imaging, Image-guided surgery, Semantic scene segmentation, Surgical data science
Référence
Surg Endosc. 2024 05 24;: