14 citations · 27 across the 10 of their papers we have counts for
Showing eess.IVShow all
2 papers · 1 filter
eess.IV2021
Spatially Dependent U-Nets: Highly Accurate Architectures for Medical Imaging Segmentation
João B. S. Carvalho, João A. Santinha, Đorđe Miladinović +1
In clinical practice, regions of interest in medical imaging often need to be identified through a process of precise image segmentation. The quality of this image segmentation ste…
eess.IV2020
Neural collaborative filtering for unsupervised mitral valve segmentation in echocardiography
Luca Corinzia, Fabian Laumer, Alessandro Candreva +3
The segmentation of the mitral valve annulus and leaflets specifies a crucial first step to establish a machine learning pipeline that can support physicians in performing multiple…