Deep learning has become the most widely used approach for cardiac image segmentation
in recent years. In this paper, we provide a review of over 100 cardiac image segmentation …

Recent high throughput experimental methods have been used to collect large biomedical
omics datasets. Clustering of single omic datasets has proven invaluable for biological and …

We define a class of machine-learned flow-based sampling algorithms for lattice gauge
theories that are gauge invariant by construction. We demonstrate the application of this …

In order to reduce the potential radiation risk, low-dose CT has attracted an increasing
attention. However, simply lowering the radiation dose will significantly degrade the image …

Recent advances in whole‐slide imaging (WSI) technology have led to the development of a
myriad of computer vision and artificial intelligence‐based diagnostic, prognostic, and …

We demonstrate a convolutional neural network trained to reproduce the Kohn–Sham
kinetic energy of hydrocarbons from an input electron density. The output of the network is …

Image segmentation is an important step in many computer vision and image processing
algorithms. It is often adopted in tasks such as object detection, classification, and tracking …

Wearable sensing devices can provide high-resolution data useful to characterise and
identify complex human behaviours. Sensing human social interactions through wearable …

Stereoscopic 3D (S3D) displays provide an additional sense of depth compared to non-
stereoscopic displays by sending slightly different images to the two eyes. But conventional …

Non-invasive fetal electrocardiography represents a valuable alternative continuous fetal
monitoring method that has recently received considerable attention in assessing fetal …