Deep learning-based automatic pipeline system for predicting lateral cervical lymph node metastasis in patients with papillary thyroid carcinoma using computed tomography: A multi-center study.

ABSTRACT:

Objective

The assessment of lateral lymph node metastasis (LLNM) in patients with papillary thyroid carcinoma (PTC) holds great significance. This study aims to develop and evaluate a deep learning-based automatic pipeline system (DLAPS) for diagnosing LLNM in PTC using computed tomography (CT).

Methods

A total of 1,266 lateral lymph nodes (LLNs) from 519 PTC patients who underwent CT examinations from January 2019 to November 2022 were included and divided into training and validation set, internal test set, pooled external test set, and prospective test set. The DLAPS consists of an auto-segmentation network based on RefineNet model and a classification network based on ensemble model (ResNet, Xception, and DenseNet). The performance of the DLAPS was compared with that of

SUBMITTER: Yu P 

PROVIDER: S-EPMC11555202 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature