Diagnosis of Benign and Malignant Breast Lesions on DCE-MRI by Using Radiomics and Deep Learning With Consideration of Peritumor Tissue.

ABSTRACT:

Background

Computer-aided methods have been widely applied to diagnose lesions detected on breast MRI, but fully-automatic diagnosis using deep learning is rarely reported.

Purpose

To evaluate the diagnostic accuracy of mass lesions using region of interest (ROI)-based, radiomics and deep-learning methods, by taking peritumor tissues into consideration.

Study type

Retrospective.

Population

In all, 133 patients with histologically confirmed 91 malignant and 62 benign mass lesions for training (74 patients with 48 malignant and 26 benign lesions for testing).

Field strength/sequence

3T, using the volume imaging for breast assessment (VIBRANT) dynamic contrast-enhanced (DCE) sequence.

Assessment

3D tumor segmentation was done automatically by using f

SUBMITTER: Zhou J 

PROVIDER: S-EPMC7709823 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature