Radiomics Harmonization in Ultrasound Images for Cervical Cancer Lymph Node Metastasis Prediction Using Cycle-GAN.

ABSTRACT: Background: Ultrasound (US) based radiomics is susceptible to variations in scanners, sonographers. Objective: To retrospectively investigate the feasibility of an adapted cycle generative adversarial networks (CycleGAN) in the style transfer to improve US based radiomics in the prediction of lymph node metastasis (LNM) with images from multiple scanners for patients with early cervical cancer (ECC). Methods: The CycleGAN was firstly trained to transfer paired US phantom images from one US device to another one; the model was then further trained and tested with clinical US images of ECC by transferring images from four US devices to one specific device; finally, the adapted model was tested with its effects on the radiomics feature harmonization and accuracy of LNM pr

SUBMITTER: Zhao Z 

PROVIDER: S-EPMC11788812 | biostudies-literature | 2024 Jan-Dec

REPOSITORIES: biostudies-literature