The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
A novel method for denoising MR images is proposed that is based on the principle of k-space data substitution. The method consists of classifying the k-space data of the image to be denoised into two subsets: the preserved set containing original higher SNR samples that are kept unchanged during denoising process, and the substitution set where the original samples having lower SNR are substituted...
In clinical Magnetic Resonance Imaging (MRI), any reduction in scan time offers a number of potential benefits ranging from high-temporal-rate observation of physiological processes to improvements in patient comfort. In this paper we proposed a reconstruction algorithm by applying contourlet thresholding in inverse scale space flows. We improved the inverse scale space with the noise item in which...
Noise is inevitably introduced to medical images because of various factors in medical imaging. The noise in medical images degrades the quality of images, blurring boundaries and suppressing structural details, thus bring difficulties to medical diagnosis. Therefore, the key to medical image de-noising is to remove the noise while preserving important features. In this paper, we analyze and compare...
In the field of magnetic resonance imaging (MRI), reconstruction from partial k-space data is a common strategy. Projection onto convex set (POCS) method has been applied to dealing with one-dimensional (ID) partial k-space. This paper applied POCS method to MR imaging from two-dimensional (2D) partial k-space data. This method is evaluated with experiments using simulate data. Compared with the zero...
A novel denoising approach is proposed that is based on averaging reconstructed images. The approach first divides the spectrum of the image to be denoised into different parts. From every such partial spectrum is then reconstructed an image using a 2-D singularity function analysis model. By expressing each of the reconstructed images as the sum of the same noise-free image and a different smaller...
This paper presents a method of reconstructing magnetic resonance (MR) images from partial k-space using a so-called singularity function model. To estimate the parameters of the model, we propose a new technique based on equation system solving. The proposed reconstruction method is evaluated on both simulated and real brain MR data. It is also compared with existing techniques. The results show...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.