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) …

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 …

This paper introduces two very fast and competitive hyperspectral image (HSI) restoration
algorithms: fast hyperspectral denoising (FastHyDe), a denoising algorithm able to cope with …

This book contains mathematical preliminaries in which basic definitions of fractional
derivatives and spaces are presented. The central part of the book contains various …

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 …

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

Relating brain tissue properties to diffusion tensor imaging (DTI) is limited when an image
voxel contains partial volume of brain tissue with free water, such as cerebrospinal fluid or …

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 …

Since its original introduction in structural design, density-based topology optimization has
been applied to a number of other fields such as microelectromechanical systems …