A New Deep Learning-Based Method for Automated Identification of Thoracic Lymph Node Stations in Endobronchial Ultrasound (EBUS): A Proof-of-Concept Study

A New Deep Learning-Based Method for Automated Identification of Thoracic Lymph Node Stations in Endobronchial Ultrasound (EBUS): A Proof-of-Concept Study

Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) is a cornerstone in minimally invasive thoracic lymph node sampling. In lung cancer staging, precise assessment of lymph node position is crucial for clinical decision-making. This study aimed to demonstrate a new deep lear...

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Bibliographic Details
Main Authors: Øyvind Ervik, Mia Rødde, Erlend Fagertun Hofstad, Ingrid Tveten, Thomas Langø, Håkon O. Leira, Tore Amundsen, Hanne Sorger
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Journal of Imaging
Subjects:
endobronchial ultrasound
AI-augmented EBUS
deep learning
deep neural networks
lymph node classification
lymph node staging
Online Access:https://www.mdpi.com/2313-433X/11/1/10
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