Deep learning based on ultrasound images assists breast lesion diagnosis in China: a multicenter diagnostic study.

ABSTRACT:

Background

Studies on deep learning (DL)-based models in breast ultrasound (US) remain at the early stage due to a lack of large datasets for training and independent test sets for verification. We aimed to develop a DL model for differentiating benign from malignant breast lesions on US using a large multicenter dataset and explore the model's ability to assist the radiologists.

Methods

A total of 14,043 US images from 5012 women were prospectively collected from 32 hospitals. To develop the DL model, the patients from 30 hospitals were randomly divided into a training cohort (n = 4149) and an internal test cohort (n = 466). The remaining 2 hospitals (n = 397) were used as the external test cohorts (ETC). We compared the model with the prospective Breast Imaging Reporting a

SUBMITTER: Gu Y 

PROVIDER: S-EPMC9334487 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature