The Application of High Temporal Resolution Semi-quantitative Dynamic Contrast Enhanced MRI in Predicting Ki-67 Expression in Breast Cancer

Comparison of two deep learning models for contrast agent dose reduction in dynamic contrast enhanced breast MRI

DCE-MRI Tumor Volumetric Changes Predict Response to Neoadjuvant Immunochemotherapy in Triple Negative Breast Cancer Patients

Development and external validation of a combined clinical-mammographic-MRI model for differentiating benign and malignant NME breast lesions

Author:Linhua Wu  Wei Yang  Jian Li  

Session Type:Digital Poster  

Session Date:Thursday, 09 May 2024  

Session Name:Fostering MRI for Breast Cancer Management  

Program Number:4595  

Room Session:Exhibition Hall (Hall 403)  

Institution:General Hospital of Ningxia Medical University  

Enhancing Breast Lesion Diagnosis Through DISCO and Deep Learning Reconstruction-Based DWI

Evaluation Molecular Receptors Status in Breast Cancer Using an mpMRI-based Feature Fusion Radiomics Model: Mimicking Radiologists’ Diagnosis

Machine Learning with Multiparametric MRI for preoperative prediction of intraductal component in invasive breast cancer

Microcalcification Detection and Differentiation in Breast Cancer using Ultrashort Echo Time (UTE) MRI

MRI Diagnosis of Lesions Presenting as Architectural Distortion on DBT: Comparison of Diagnostic Performance Using BI-RADS and Radiomics Models

Precision Diagnosis of BI-RADS4 Breast Lesions: A Promising Approach with DCE and 3D-MIP Parameters

Prediction of axillary lymph nodes metastases in patients with breast cancer : Can synthetic MRI provide additional value to DWI?

Preoperative Prediction of Recurrence Risk in Breast Cancer Patients Based on MRI Features

Quantitative Background Parenchymal Enhancement: Association with Lifetime Risk Factors on Breast Cancer Screening MRI

Reliability and repeatability of texture features extracted from quantitative T1 & T2 of fresh breast tumour specimens at 3T

Whole-tumor histogram models based on quantitative maps from SyMRI for predicting axillary lymph node status in invasive ductal breast cancer