In this paper, we propose a novel deep convolutional neural network (CNN)-based
algorithm for solving ill-posed inverse problems. Regularized iterative algorithms have …

Background and objectives Computer-assisted technologies, such as image-based
segmentation, play an important role in the diagnosis and treatment support in cranio …

Although X-rays generated from a laboratory-based tube cannot be compared with
synchrotron radiation in brilliance and monochromaticity, they are still viable and accessible …

The proposed paper addresses the inverse problems using a novel deep convolutional
neural network (CNN). Over the years, regularized iterative algorithms have been observed …

Since the compressed sensing (CS) theory broke through the limitation of the traditional
Nyquist sampling theory, it has attracted extensive attention in the field of microwave …

Introduction Computer assisted technologies based on algorithmic software segmentation
are an increasing topic of interest in complex surgical cases. However—due to functional …

This tutorial covers biomedical image reconstruction, from the foundational concepts of
system modeling and direct reconstruction to modern sparsity and learning-based …

Many subsurface engineering technologies or natural processes cause porous medium
properties, such as porosity or permeability, to evolve in time. Studying and understanding …

Image-based algorithmic software segmentation is an increasingly important topic in many
medical fields. Algorithmic segmentation is used for medical three-dimensional visualization …

GlobalBioIm is an open-source MATLAB® library for solving inverse problems. The library
capitalizes on the strong commonalities between forward models to standardize the …