Auto-detection and segmentation of involved lymph nodes in HPV-associated oropharyngeal cancer using a convolutional deep learning neural network

ABSTRACT: Highlights • Patients diagnosed with HPV-associated OPC are often found to have clinical evidence of lymph node involvement at the time of diagnosis.• Manual segmentation of radiographically involved lymph nodes is an integral part of treatment planning for those patients dispositioned to definitive radiotherapy.• We present a deep learning, convolutional neural network that can be used to automate the process of lymph node detection and segmentation and with potential to increase the efficiency to the radiotherapy workflow.

Purpose

Segmentation of involved lymph nodes on head and neck computed tomography (HN-CT) scans is necessary for the radiotherapy planning of early-stage human papilloma virus (HPV) associated oropharynx cancers (OPC). We aimed to train a deep learning convolu

SUBMITTER: Taku N 

PROVIDER: S-EPMC9240370 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature