Medical imaging is crucial in modern clinics to provide guidance to the diagnosis and
treatment of diseases. Medical image reconstruction is one of the most fundamental and …

This chapter surveys recent numerical advances in the phase field method for geometric
surface evolution and related geometric nonlinear partial differential equations (PDEs) …

Level set methods have been widely used in image processing and computer vision. In
conventional level set formulations, the level set function typically develops irregularities …

We propose a new multiphase level set framework for image segmentation using the
Mumford and Shah model, for piecewise constant and piecewise smooth optimal …

Deep neural networks have become the state-of-the-art models in numerous machine
learning tasks. However, general guidance to network architecture design is still missing. In …

Intensity inhomogeneity often occurs in real-world images, which presents a considerable
challenge in image segmentation. The most widely used image segmentation algorithms are …

Many recent computational photography techniques decompose an image into a piecewise
smooth base layer, containing large scale variations in intensity, and a residual detail layer …

Tensors are nowadays a common source of geometric information. In this paper, we
propose to endow the tensor space with an affine-invariant Riemannian metric. We …

We propose the use of nonlocal operators to define new types of flows and functionals for
image processing and elsewhere. A main advantage over classical PDE-based algorithms …

No time in human history has ever witnessed such explosive influence and impact of image
processing on modern society, sciences, and technologies. From nanotechnologies …