Deep learning radiomics on grayscale ultrasound images assists in diagnosing benign and malignant of BI-RADS 4 lesions.

ABSTRACT: This study aimed to explore a deep learning radiomics (DLR) model based on grayscale ultrasound images to assist radiologists in distinguishing between benign breast lesions (BBL) and malignant breast lesions (MBL). A total of 382 patients with breast lesions were included, comprising 183 benign lesions and 199 malignant lesions that were collected and confirmed through clinical pathology or biopsy. The enrolled patients were randomly allocated into two groups: a training cohort and an independent test cohort, maintaining a ratio of 7:3.We created a model called CLDLR that utilizes clinical parameters and DLR to diagnose both BBL and MBL through grayscale ultrasound images. In order to assess the practicality of the CLDLR model, two rounds of evaluations were conducted by radiologists. The

SUBMITTER: Yang L 

PROVIDER: S-EPMC11682229 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature