We have worked on the measurement protocol and related image reconstruction of 4D data sets in the field of time-resolved Contrast-Enhanced Magnetic Resonance Angiography (CE-MRA). The method aims at improving the interpolation of sparsely sampled -space data. It is based on exploiting prior knowledge on the time courses (TCs) of the image pixels, when monitoring the uptake of contrast agents i...

In recent years many authors have introduced certain nonlinear algorithms for data compression, noise removal, and image reconstruction. These methods include wavelet and quadrature-mirror filters combined with quantization of filter coefficients for image compression, wavelet shrinkage estimation for Gaussian noise removal, and certain minimization techniques for image reconstruction. In many ...

BACKGROUND This study was performed to assess whether iterative reconstruction can reduce radiation dose while maintaining acceptable image quality, and to investigate whether perfusion parameters vary from conventional filtered back projection (FBP) at the low-tube-voltage (80-kVp) during whole-pancreas perfusion examination using a 256-slice CT. METHODS 76 patients with known or suspected p...

This paper describes a new reconstruction method for digital breast tomosynthesis (DBT). The new method incorporates detector blur into the forward model. The detector blur introduces correlation in the measurement noise. We formulate it as a regularized quadratic optimization problem with data-fit term that accounts for the non-diagonal noise covariance matrix. By making a few assumptions base...

Accurate registration of multiple low resolution images is of central importance in many advanced image processing applications, since capturing of multiple low-resolution images taken of the same scene results in a distortion between each image. Image super-resolution is a typical application where the quality of the super-resolved image is degraded as registration errors increase. In this pap...

A new method for the detection of blood vessels that improves the detection of exudates in fundus photographs. The method starts with pre-processing to enhance the input image. The initial estimation of exudates is obtained by segmenting the optic disc and blood vessels from the fundus image. In order to segment the optic disc and blood vessel separate algorithm were used. First, optic disc is ...

Abstract The linear canonical transform (LCT) plays an important role in signal and image processing from both theoretical practical points of view. Various sampling representations for band-limited non-band-limited signals the LCT domain have been established. We focus this paper on derivative reconstruction, where reconstruction procedure utilizes samples its first derivative. Our major aim w...

The edges of an image define the image boundary. When the image is noisy, it does not become easy to identify the edges. Therefore, a method requests to be developed that can identify edges clearly in a noisy image. Many methods have been proposed earlier using filters, transforms and wavelets with Ant colony optimization (ACO) that detect edges. We here used ACO for edge detection of noisy ima...

1 The popularity of Bayesian methods in image processing applications has generated a lot of interest in the eld of image modeling. A good image model needs to be non-homogeneous to be able to adapt to the local characteristics of the diierent regions in an image. Toward this end, we propose a non-homogeneous Markov random eld (MRF) model that has space-varying scale parameters. This formulatio...

A vertex reconstruction algorithm was developed based on the Gaussian-sum filter (GSF) and implemented in the framework of the CMS reconstruction program. While linear least-square estimators are optimal in case all observation errors are Gaussian distributed, the GSF offers a better treatment of non-Gaussian distributions of track parameter errors when these are modelled by Gaussian mixtures. ...