Humans perceive physical properties such as motion and elastic force by observing objects
in visual scenes. Recent research has proven that computers are capable of inferring …

Purpose We analyzed clinical features and the representative HE-stained pathologic images
to predict 5-year overall survival via the deep-learning approach in cervical cancer patients …

The fusion and combination of images from multiple modalities is important in many
applications. Typically, this process consists of the alignment of the images and the …

Converging evidence shows that disease-relevant brain alterations do not appear in random
brain locations, instead, their spatial patterns follow large-scale brain networks. In this …

Multi-view networks constructed from multiple brain functional or structural measures (eg,
fractional anisotropy, fiber number, and fiber length, etc.) describe brain connectivity from …

Uncovering the complex network of the brain is of great interest to the field of neuroimaging.
Mining from these rich datasets, scientists try to unveil the fundamental biological …

In recent years, brain network analysis has attracted considerable interests in the field of
neuroimaging analysis. It plays a vital role in understanding biologically fundamental …

Spatio Temporal Modelling plays an important role in personalized medicine, virtual clinical
trials or drug target identification. It enables the encoding of trajectories of complex diseases …

A broad range of problems in Computer Vision are posed as numerical optimizations of an
objective function that acts as a surrogate for a perceptual model of image interpretation and …