Deep Learning Analysis of In Vivo Hyperspectral Images for Automated Intraoperative Nerve Detection.

ABSTRACT: Nerves are critical structures that may be difficult to recognize during surgery. Inadvertent nerve injuries can have catastrophic consequences for the patient and lead to life-long pain and a reduced quality of life. Hyperspectral imaging (HSI) is a non-invasive technique combining photography with spectroscopy, allowing non-invasive intraoperative biological tissue property quantification. We show, for the first time, that HSI combined with deep learning allows nerves and other tissue types to be automatically recognized in in vivo hyperspectral images. An animal model was used, and eight anesthetized pigs underwent neck midline incisions, exposing several structures (nerve, artery, vein, muscle, fat, skin). State-of-the-art machine learning models were trained to recognize these tissue

SUBMITTER: Barberio M 

PROVIDER: S-EPMC8391550 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature