Abstract：
:Magnetic resonance images tend to be influenced by various random factors usually referred to as "noise". The principal sources of noise and related artefacts can be divided into two types: arising from hardware (acquisition coil arrays, gradient coils, field inhomogeneity); and arising from the subject (physiological noise including body motion, cardiac pulsation or respiratory motion). These factors negatively affect the resolution and reproducibility of the images. Therefore, a proper noise treatment is important for improving the performance of clinical and research investigations. Noise reduction becomes especially critical for the images with a low signal-to-noise ratio, such as those typically acquired in diffusion tensor imaging at high diffusion weightings. The standard methods of signal correction usually assume a uniform distribution of the standard deviation of the noise across the image and evaluate a single correction parameter for the whole image. We pursue a more advanced approach based on the assumption of an inhomogeneous distribution of noise in space and evaluate correction factors for each voxel individually. The Rician nature of the underlying noise is considered for low and high signal-to-noise ratios. The approach developed here has been examined using numerical simulations and in vivo brain diffusion tensor imaging experiments. The efficacy and usefulness of this approach is demonstrated here and the resultant effective tool is described.
journal_name
Med Image Analjournal_title
Medical image analysisauthors
Maximov II,Farrher E,Grinberg F,Shah NJdoi
10.1016/j.media.2011.12.002subject
Has Abstractpub_date
2012-02-01 00:00:00pages
536-48issue
2eissn
1361-8415issn
1361-8423pii
S1361-8415(11)00172-1journal_volume
16pub_type
杂志文章abstract：:This paper presents a new hybrid camera motion tracking method for bronchoscopic navigation combining SIFT, epipolar geometry analysis, Kalman filtering, and image registration. In a thorough evaluation, we compare it to state-of-the-art tracking methods. Our hybrid algorithm for predicting bronchoscope motion uses SI...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2010.11.001
更新日期：2012-04-01 00:00:00
abstract：:Creating a feature-preserving average of three dimensional anatomical surfaces extracted from volume image data is a complex task. Unlike individual images, averages present right-left symmetry and smooth surfaces which give insight into typical proportions. Averaging multiple biological surface images requires carefu...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/s1361-8415(00)00031-1
更新日期：2000-12-01 00:00:00
abstract：:Dynamic-susceptibility-contrast (DSC) magnetic resonance imaging records signal changes on images when the injected contrast-agent particles pass through a human brain. The temporal signal changes on different brain tissues manifest distinct blood-supply patterns which are vital for the profound analysis of cerebral h...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2007.02.002
更新日期：2007-06-01 00:00:00
abstract：:Mutual information (MI) has been widely used as a similarity measure for rigid registration of multi-modal and uni-modal medical images. However, robust application of MI to deformable registration is challenging mainly because rich structural information, which are critical cues for successful deformable registration...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2013.12.003
更新日期：2014-02-01 00:00:00
abstract：:Recent progress in cardiac catheterization and devices has allowed the development of new therapies for severe cardiac diseases like arrhythmias and heart failure. The skills required for such interventions are very challenging to learn, and are typically acquired over several years. Virtual reality simulators may red...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2016.06.040
更新日期：2017-01-01 00:00:00
abstract：:During neurosurgical procedures the objective of the neurosurgeon is to achieve the resection of as much diseased tissue as possible while achieving the preservation of healthy brain tissue. The restricted capacity of the conventional operating room to enable the surgeon to visualize critical healthy brain structures ...
journal_title：Medical image analysis
pub_type： 杂志文章,评审
doi：10.1016/j.media.2004.11.005
更新日期：2005-04-01 00:00:00
abstract：:This paper presents a symbolic visualization environment known as the Corner Cube environment, which was developed to facilitate rapid examination and comparison of activated foci defined by analyses of functional neuroimaging datasets. We have performed a comparative evaluation of this environment against maximum-int...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/s1361-8415(98)80020-0
更新日期：1998-09-01 00:00:00
abstract：:We address the medical image analysis issue of predicting the final lesion in stroke from early perfusion magnetic resonance imaging. The classical processing approach for the dynamical perfusion images consists in a temporal deconvolution to improve the temporal signals associated with each voxel before performing pr...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2018.08.008
更新日期：2018-12-01 00:00:00
abstract：:We propose two information theoretic similarity measures that allow to incorporate tissue class information in non-rigid image registration. The first measure assumes that tissue class probabilities have been assigned to each of the images to be registered by prior segmentation of both of them. One image is then non-r...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2005.03.004
更新日期：2006-06-01 00:00:00
abstract：:The dynamics of the carotid artery wall has been recognized as a valuable indicator to evaluate the status of atherosclerotic disease in the preclinical stage. However, it is still a challenge to accurately measure this dynamics from ultrasound images. This paper aims at developing an elasticity-based state-space appr...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2017.01.004
更新日期：2017-04-01 00:00:00
abstract：:Segmentation of abdominal organs has been a comprehensive, yet unresolved, research field for many years. In the last decade, intensive developments in deep learning (DL) introduced new state-of-the-art segmentation systems. Despite outperforming the overall accuracy of existing systems, the effects of DL model proper...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2020.101950
更新日期：2020-12-25 00:00:00
abstract：:With the advent of large-scale imaging studies and big health data, and the corresponding growth in analytics, machine learning and computational image analysis methods, there are now exciting opportunities for deepening our understanding of the mechanisms and characteristics of heart disease. Two emerging fields are ...
journal_title：Medical image analysis
pub_type： 社论,评审
doi：10.1016/j.media.2016.06.027
更新日期：2016-10-01 00:00:00
abstract：:Robust and fast detection of anatomical structures represents an important component of medical image analysis technologies. Current solutions for anatomy detection are based on machine learning, and are generally driven by suboptimal and exhaustive search strategies. In particular, these techniques do not effectively...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2018.06.007
更新日期：2018-08-01 00:00:00
abstract：:Automated quantitative estimation of spinal curvature is an important task for the ongoing evaluation and treatment planning of Adolescent Idiopathic Scoliosis (AIS). It solves the widely accepted disadvantage of manual Cobb angle measurement (time-consuming and unreliable) which is currently the gold standard for AIS...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2018.05.005
更新日期：2018-08-01 00:00:00
abstract：:Accurate vertebral body (VB) detection and segmentation are critical for spine disease identification and diagnosis. Existing automatic VB detection and segmentation methods may cause false-positive results to the background tissue or inaccurate results to the desirable VB. Because they usually cannot take both the gl...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2020.101861
更新日期：2021-01-01 00:00:00
abstract：:Diffusion magnetic resonance imaging (dMRI) provides a noninvasive method for measuring brain tissue microstructure. q-Space deep learning(q-DL) methods have been developed to accurately estimate tissue microstructure from dMRI scans acquired with a reduced number of diffusion gradients. In these methods, deep network...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2020.101885
更新日期：2021-01-01 00:00:00
abstract：:In this work, we first propose an original and efficient computational framework to model continuous diffusion MRI (dMRI) signals and analytically recover important diffusion features such as the Ensemble Average Propagator (EAP) and the Orientation Distribution Function (ODF). Then, we develop an efficient parametric...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2013.04.011
更新日期：2013-10-01 00:00:00
abstract：:We describe a system for respiratory motion correction of MRI-derived roadmaps for use in X-ray guided cardiac catheterisation procedures. The technique uses a subject-specific affine motion model that is quickly constructed from a short pre-procedure MRI scan. We test a dynamic MRI sequence that acquires a small numb...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2009.01.003
更新日期：2009-06-01 00:00:00
abstract：:Accurate automated segmentation and detection of ovarian cancer metastases may improve the diagnosis and prognosis of women with ovarian cancer. In this paper, we focus on an important subset of ovarian cancer metastases that spread to the surface of the liver and spleen. Automated ovarian cancer metastasis detection ...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2014.04.001
更新日期：2014-07-01 00:00:00
abstract：:Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is increasingly being used for the detection and diagnosis of breast cancer. Compared to mammography, DCE-MRI provides higher sensitivity, however its specificity is variable. Moreover, DCE-MRI data analysis is time consuming and depends on reader expertis...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2014.12.001
更新日期：2015-02-01 00:00:00
abstract：:Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive impairment of memory and other cognitive functions. Currently, many multi-task learning approaches have been proposed to predict the disease progression at the early stage using longitudinal data, with each task corresponding to a pa...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2019.01.007
更新日期：2019-04-01 00:00:00
abstract：:Diabetic Retinopathy (DR) is the most common cause of avoidable vision loss, predominantly affecting the working-age population across the globe. Screening for DR, coupled with timely consultation and treatment, is a globally trusted policy to avoid vision loss. However, implementation of DR screening programs is chal...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2019.101561
更新日期：2020-01-01 00:00:00
abstract：:Accurate cortical thickness estimation is important for the study of many neurodegenerative diseases. Many approaches have been previously proposed, which can be broadly categorised as mesh-based and voxel-based. While the mesh-based approaches can potentially achieve subvoxel resolution, they usually lack the computa...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2009.07.003
更新日期：2009-10-01 00:00:00
abstract：:After two decades of increasing interest and research activity, computer-assisted diagnostic approaches are reaching the stage where more routine deployment in clinical practice is becoming a possibility [Kruppinski, E.A., 2004. Computer-aided detection in clinical environment: Benefits and challenges for radiologists...
journal_title：Medical image analysis
pub_type： 杂志文章,评审
doi：10.1016/j.media.2005.06.003
更新日期：2006-04-01 00:00:00
abstract：:Numerous algorithms are available for segmenting medical images. Empirical discrepancy metrics are commonly used in measuring the similarity or difference between segmentations by algorithms and "true" segmentations. However, one issue with the commonly used metrics is that the same metric value often represents diffe...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2019.101601
更新日期：2020-02-01 00:00:00
abstract：:As a common disease in the elderly, neural foramina stenosis (NFS) brings a significantly negative impact on the quality of life due to its symptoms including pain, disability, fall risk and depression. Accurate boundary delineation is essential to the clinical diagnosis and treatment of NFS. However, existing clinica...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2016.10.009
更新日期：2017-02-01 00:00:00
abstract：:Current neuroimaging investigation of the white matter typically focuses on measurements derived from diffusion tensor imaging, such as fractional anisotropy (FA). In contrast, imaging studies of the gray matter oftentimes focus on morphological features such as cortical thickness, folding and surface curvature. As a ...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2014.06.013
更新日期：2014-12-01 00:00:00
abstract：:Phase contrast, a noninvasive microscopy imaging technique, is widely used to capture time-lapse images to monitor the behavior of transparent cells without staining or altering them. Due to the optical principle, phase contrast microscopy images contain artifacts such as the halo and shade-off that hinder image segme...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2011.12.006
更新日期：2012-07-01 00:00:00
abstract：:We performed a systematic review of studies focusing on the automatic prediction of the progression of mild cognitive impairment to Alzheimer's disease (AD) dementia, and a quantitative analysis of the methodological choices impacting performance. This review included 172 articles, from which 234 experiments were extr...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2020.101848
更新日期：2021-01-01 00:00:00
abstract：:We evaluate the accuracy of whole-body bone extraction from whole-body MR images using a number of atlas-based segmentation methods. The motivation behind this work is to find the most promising approach for the purpose of MRI-guided derivation of PET attenuation maps in whole-body PET/MRI. To this end, a variety of a...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2016.11.003
更新日期：2017-02-01 00:00:00
