Using deep learning to safely exclude lesions with only ultrafast breast MRI to shorten acquisition and reading time.

ABSTRACT:

Objectives

To investigate the feasibility of automatically identifying normal scans in ultrafast breast MRI with artificial intelligence (AI) to increase efficiency and reduce workload.

Methods

In this retrospective analysis, 837 breast MRI examinations performed on 438 women from April 2016 to October 2019 were included. The left and right breasts in each examination were labelled normal (without suspicious lesions) or abnormal (with suspicious lesions) based on final interpretation. Maximum intensity projection (MIP) images of each breast were then used to train a deep learning model. A high sensitivity threshold was calculated based on the detection trade - off (DET) curve on the validation set. The performance of the model was evaluated by receiver operating characterist

SUBMITTER: Jing X 

PROVIDER: S-EPMC9705471 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature