Results 41 to 50 of about 161,991 (287)
SCSA based MATLAB pre-processing toolbox for 1H MR spectroscopic water suppression and denoising [PDF]
, 2018 In vivo 1H Magnetic Resonance Spectroscopy (MRS) is a useful tool in assessing neurological and metabolic disease, and to improve tumor treatment. Different pre-processing pipelines have been developed to obtain optimal results from the acquired data ...
Achten, Eric +4 more
core +2 more sources
From denoising diffusions to denoising Markov models
Journal of the Royal Statistical Society Series B: Statistical MethodologyAbstract Denoising diffusions are state-of-the-art generative models exhibiting remarkable empirical performance. They work by diffusing the data distribution into a Gaussian distribution and then learning to reverse this noising process to obtain synthetic datapoints.
Joe Benton +4 more
openaire +3 more sources
Bayesian demosaicing using Gaussian scale mixture priors with local adaptivity in the dual tree complex wavelet packet transform domain [PDF]
, 2013 In digital cameras and mobile phones, there is an ongoing trend to increase the image resolution, decrease the sensor size and to use lower exposure times. Because smaller sensors inherently lead to more noise and a worse spatial resolution, digital post-
Aelterman, Jan +4 more
core +1 more source
FEBS Open Bio, EarlyView.This protocol paper outlines methods to establish the success of a time‐resolved serial crystallographic experiment, by means of statistical analysis of timepoint data in reciprocal space and models in real space. We show how to amplify the signal from excited states to visualise structural changes in successful experiments.
Jake Hill +4 more
wiley +1 more source
Overview of Research on Digital Image Denoising Methods
SensorsDuring image collection, images are often polluted by noise because of imaging conditions and equipment limitations. Images are also disturbed by external noise during compression and transmission, which adversely affects consequent processing, like ...
Jing Mao +3 more
doaj +1 more source
Medical Image Denoising using Adaptive Threshold Based on Contourlet Transform
, 2011 Image denoising has become an essential exercise in medical imaging especially the Magnetic Resonance Imaging (MRI). This paper proposes a medical image denoising algorithm using contourlet transform.
Prasad, KVSVR, Satheesh, S.
core +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background and Objectives Multiple sclerosis (MS) exhibits racially disparate rates of disease progression. Black people with MS (B‐PwMS) experience a more severe disease course than non‐Hispanic White people with MS (NHW‐PwMS). Here we investigated structural and functional connectivity as well as structure–function decoupling in the ...
Emilio Cipriano +11 more
wiley +1 more source
Edge-aware image denoising algorithm
Journal of Algorithms & Computational Technology, 2018 The key of image denoising algorithms is to preserve the details of the original image while denoising the noise in the image. The existing algorithms use the external information to better preserve the details of the image, but the use of external ...
Xiangning Zhang, Yan Yang, Lening Lin
doaj +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To explore how cerebral hypoxia and Normal‐Appearing White Matter (NAWM) integrity affect MS lesion burden and clinical course. Methods Seventy‐nine MS patients, including 13 clinically isolated syndrome (CIS) patients and 66 relapsing–remitting multiple sclerosis (RRMS) patients, and 44 healthy controls (HCs) were recruited from ...
Xinli Wang +8 more
wiley +1 more source
DENOISING OF GEOACOUSTIC EMISSION SIGNALS FROM NATIVE AND TECHNOGENIC NOISES USING THE SPARSE APPROXIMATION METHOD [PDF]
Vestnik KRAUNC: Fiziko-Matematičeskie Nauki, 2015 The approach of geoacoustic emission signals denoising from native and technogenic noises based on sparse approximation method is offered in this paper.
O.O. Lukovenkova
doaj +1 more source