Deep learning models for medical image segmentation can fail unexpectedl...
This paper describes our method for our participation in the FeTA
challe...
Automatic medical image segmentation via convolutional neural networks (...
The performance of deep neural networks typically increases with the num...
Twin-to-twin transfusion syndrome treatment requires fetoscopic laser
ph...
Despite the state-of-the-art performance for medical image segmentation,...
Data augmentation has been widely used for training deep learning system...
Purpose: The standard clinical treatment of Twin-to-Twin Transfusion Syn...
We propose a spatial compounding technique and variational framework to
...
Segmentation of the levator hiatus in ultrasound allows to extract biome...
Convolutional neural networks (CNNs) have achieved state-of-the-art
perf...
Accurate medical image segmentation is essential for diagnosis, surgical...
Real-time tool segmentation from endoscopic videos is an essential part ...