Generalizable attention U-Net for segmentation of fibroglandular tissue and background parenchymal enhancement in breast DCE-MRI

Generalizable attention U-Net for segmentation of fibroglandular tissue and background parenchymal enhancement in breast DCE-MRI

Abstract Objectives Development of automated segmentation models enabling standardized volumetric quantification of fibroglandular tissue (FGT) from native volumes and background parenchymal enhancement (BPE) from subtraction volumes of dynamic contrast-enhanced breast MRI. Subsequent assessment of...

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Bibliographic Details
Main Authors: Sylwia Nowakowska, Karol Borkowski, Carlotta M. Ruppert, Anna Landsmann, Magda Marcon, Nicole Berger, Andreas Boss, Alexander Ciritsis, Cristina Rossi
Format: Article
Language:English
Published: SpringerOpen 2023-11-01
Series:Insights into Imaging
Subjects:
Fibroglandular tissue segmentation
Background parenchymal enhancement segmentation
Deep learning
Breast MRI
Assessment standardization
Online Access:https://doi.org/10.1186/s13244-023-01531-5

Internet

https://doi.org/10.1186/s13244-023-01531-5

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