Auto-Segmentation via deep-learning approaches for the assessment of flap volume after reconstructive surgery or radiotherapy in head and neck cancer

Auto-Segmentation via deep-learning approaches for the assessment of flap volume after reconstructive surgery or radiotherapy in head and neck cancer

Abstract Reconstructive flap surgery aims to restore the substance and function losses associated with tumor resection. Automatic flap segmentation could allow quantification of flap volume and correlations with functional outcomes after surgery or post-operative RT (poRT). Flaps being ectopic tissu...

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Bibliographic Details
Main Authors: Juliette Thariat, Zacharia Mesbah, Youssef Chahir, Arnaud Beddok, Alice Blache, Jean Bourhis, Abir Fatallah, Mathieu Hatt, Romain Modzelewski
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Head and neck neoplasms
Surgery
Flap
Volume
Neural networks (Computer)
Online Access:https://doi.org/10.1038/s41598-025-08073-4
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