2 citations · 3 across the 3 of their papers we have counts for
3 papers
Semi-Supervised Segmentation via Embedding Matching
Weiyi Xie, Nathalie Willems, Nikolas Lessmann +2
Deep convolutional neural networks are widely used in medical image segmentation but require many labeled images for training. Annotating three-dimensional medical images is a time…
Transfer learning from a sparsely annotated dataset of 3D medical images
Gabriel Efrain Humpire-Mamani, Colin Jacobs, Mathias Prokop +2
Transfer learning leverages pre-trained model features from a large dataset to save time and resources when training new models for various tasks, potentially enhancing performance…
Kidney abnormality segmentation in thorax-abdomen CT scans
Gabriel Efrain Humpire Mamani, Nikolas Lessmann, Ernst Th. Scholten +3
In this study, we introduce a deep learning approach for segmenting kidney parenchyma and kidney abnormalities to support clinicians in identifying and quantifying renal abnormalit…