Medical Imaging (MI) plays a crucial role in healthcare, including disease diagnosis,
treatment, and continuous monitoring. The integration of non-invasive techniques such as X …

This review focuses on positron emission tomography (PET) imaging algorithms and traces
the evolution of PET image reconstruction methods. First, we provide an overview of …

Deep image prior (DIP) and its variants have showed remarkable potential for solving
inverse problems in computer vision, without any extra training data. Practical DIP models …

The high noise level of dynamic Positron Emission Tomography (PET) images degrades the
quality of parametric images. In this study, we aim to improve the quality and quantitative …

List-mode positron emission tomography (PET) image reconstruction is an important tool for
PET scanners with many lines-of-response and additional information such as time-of-flight …

Objective. Deep image prior (DIP) has recently attracted attention owing to its unsupervised
positron emission tomography (PET) image reconstruction method, which does not require …

Image reconstruction for positron emission tomography (PET) has been developed over
many decades, with advances coming from improved modelling of the data statistics and …

Electrical impedance tomography (EIT) is a new imaging modality for nonionizing radiation
that uses a safe current applied to the surface and measures the response voltage on a …

Deep image prior (DIP) has been successfully applied to positron emission tomography
(PET) image restoration, enabling represent implicit prior using only convolutional neural …

Better algorithms for medical image reconstruction can improve image quality and enable
reductions in acquisition time and radiation dose. A prior understanding of the distribution of …