Deep learning

Differentiable Histogram Loss Functions for Intensity-based Image-to-Image Translation
We introduce the HueNet - a novel deep learning framework for a differentiable construction of intensity (1D) and joint (2D) histograms …
Cite DOI
A Deep Ensemble Learning Approach to Lung CT Segmentation for Covid-19 Severity Assessment
We present a novel deep learning approach to categorical segmentation of lung CTs of COVID-19 patients. Specifically, we partition the …
Cite DOI
Dual-Task ConvLSTM-UNet for Instance Segmentation of Weakly Annotated Microscopy Videos
Convolutional Neural Networks (CNNs) are considered state of the art segmentation methods for biomedical images in general and …
Cite DOI
Deep Semi-Supervised Bias Field Correction Of Mr Images
A bias field is an artifact inherent to MRI scanners which is manifested by a smooth intensity variation across the scans. We present …
Cite DOI
Subsampled brain MRI reconstruction by generative adversarial neural networks
A main challenge in magnetic resonance imaging (MRI) is speeding up scan time. Beyond improving patient experience and reducing …
PDF Cite DOI
From a deep learning model back to the brain—Identifying regional predictors and their relation to aging
We present a Deep Learning framework for the prediction of chronological age from structural magnetic resonance imaging scans. Previous …
PDF Cite DOI