Development and validation of a deep learning model for breast lesion segmentation and characterization in multiparametric MRI.

ABSTRACT:

Importance

The utilization of artificial intelligence for the differentiation of benign and malignant breast lesions in multiparametric MRI (mpMRI) assists radiologists to improve diagnostic performance.

Objectives

To develop an automated deep learning model for breast lesion segmentation and characterization and to evaluate the characterization performance of AI models and radiologists.

Materials and methods

For lesion segmentation, 2,823 patients were used for the training, validation, and testing of the VNet-based segmentation models, and the average Dice similarity coefficient (DSC) between the manual segmentation by radiologists and the mask generated by VNet was calculated. For lesion characterization, 3,303 female patients with 3,607 pathologically confirmed le

SUBMITTER: Zhu J 

PROVIDER: S-EPMC9402900 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature