Automated rating of background parenchymal enhancement in MRI of extremely dense breasts without compromising the association with breast cancer in the DENSE trial
Open Access
- 24 March 2024
- journal article
- research article
- Published by Elsevier in European Journal of Radiology
- Vol. 175, 111442
Abstract
No abstract availableKeywords
Funding Information
- KWF Kankerbestrijding
This publication has 36 references indexed in Scilit:
- Breast MRI Background Parenchymal Enhancement Categorization Using Deep Learning: Outperforming the RadiologistJournal of Magnetic Resonance Imaging, 2022
- Fully Automatic Assessment of Background Parenchymal Enhancement on Breast MRI Using Machine‐Learning ModelsJournal of Magnetic Resonance Imaging, 2020
- Second International Consensus Conference on lesions of uncertain malignant potential in the breast (B3 lesions)Breast Cancer Research and Treatment, 2018
- Contrast-enhanced MRI after neoadjuvant chemotherapy of breast cancer: lesion-to-background parenchymal signal enhancement ratio for discriminating pathological complete response from minimal residual tumourEuropean Radiology, 2018
- Association Between Background Parenchymal Enhancement and Pathologic Complete Remission Throughout the Neoadjuvant Chemotherapy in Breast Cancer PatientsTranslational Oncology, 2017
- BI-RADS ® fifth edition: A summary of changesDiagnostic and Interventional Imaging, 2017
- Volumetric breast density affects performance of digital screening mammographyBreast Cancer Research and Treatment, 2016
- Multiple imputation was an efficient method for harmonizing the Mini-Mental State Examination with missing item-level dataJournal of Clinical Epidemiology, 2011
- Signal-detection analysis of group decision making.Psychological Review, 2001
- Multiple Imputation for Nonresponse in Surveys1987