Investigation of spatial resolution, partial volume effects and smoothing in functional MRI using artificial 3D time series

Weibull, Andreas; Gustavsson, Helen; Mattsson, Sören; Svensson, Jonas

doi:10.1016/j.neuroimage.2008.02.015

Cited by 37 publications

(29 citation statements)

References 28 publications

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“…These could have resulted from problems in the normal distribution of error terms in the statistical model used by VBM8 to construct parametric statistical tests [50,56,57]. Furthermore, it helped to better minimize the influence of noise [58] and the effect of individual differences in gyral anatomy [59]. A limitation of using bigger smoothing kernels is a loss of spatial detail [56].…”

Section: Pre-processingmentioning

confidence: 99%

Structural brain injury in patients with disorders of consciousness: A voxel-based morphometry study

et al. 2016

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Main objective: Disorders of consciousness (DOC; encompassing coma, vegetative state/unresponsive wakefulness syndrome (VS/UWS) and minimally conscious state minus/plus (MCS-/+)) are associated with structural brain injury. The extent of this damage remains poorly understood and merits a detailed examination using novel analysis techniques. Research design/methods and procedures: This study used voxel-based morphometry (VBM) on structural magnetic resonance imaging scans of 61 patients with DOC to examine grey and white matter injury associated with DOC, time spent in DOC, aetiology and diagnosis. Main outcomes and results: DOC and time spent in DOC were found to be associated with widespread structural brain injury, although the latter did not correlate strongly with injury in the right cerebral hemisphere. Traumatic, as compared to non-traumatic aetiology, was related to more injury in the brainstem, midbrain, thalamus, hypothalamus, basal forebrain, cerebellum, and posterior corpus callosum. Potential structural differences were found between VS/ UWS and MCS and between MCS-and MCS+, but need further examination. Conclusions: The findings indicate that both traumatic and non-traumatic DOC are associated with widespread structural brain injury, although differences exist that could lead to aetiologyspecific treatment strategies. Furthermore, the high degree of atrophy occurring after initial brain injury prompts the development and use of neuroprotective techniques to potentially increase patients' chances of recovery. KeywordsVegetative state/unresponsive wakefulness syndrome, minimally conscious state, structural brain injury, voxel-based morphometry History

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Section: Pre-processingmentioning

confidence: 99%

Structural brain injury in patients with disorders of consciousness: A voxel-based morphometry study

et al. 2016

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“…The impact of partial volume effect is particularly important for MRI, as the voxel size is generally much larger than that of CT. Studies have shown that ignoring this effect in MRI by establishing binary voxel-based segmentations introduces significant errors in quantitative measurements. 38,39 Most of these errors are associated with accurate quantification of small volumes, such as lesions, where the boundary contributes significantly in the total volume estimation. In the current breast density study, however, the quantification was carried out by averaging a large number of voxels, where the partial volume effects may be largely alleviated.…”

Section: Discussionmentioning

confidence: 99%

Breast density quantification using magnetic resonance imaging (MRI) with bias field correction: A postmortem study

et al. 2013

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Purpose: Quantification of breast density based on three-dimensional breast MRI may provide useful information for the early detection of breast cancer. However, the field inhomogeneity can severely challenge the computerized image segmentation process. In this work, the effect of the bias field in breast density quantification has been investigated with a postmortem study. Methods: T1-weighted images of 20 pairs of postmortem breasts were acquired on a 1.5 T breast MRI scanner. Two computer-assisted algorithms were used to quantify the volumetric breast density. First, standard fuzzy c-means (FCM) clustering was used on raw images with the bias field present. Then, the coherent local intensity clustering (CLIC) method estimated and corrected the bias field during the iterative tissue segmentation process. Finally, FCM clustering was performed on the bias-fieldcorrected images produced by CLIC method. The left-right correlation for breasts in the same pair was studied for both segmentation algorithms to evaluate the precision of the tissue classification. Finally, the breast densities measured with the three methods were compared to the gold standard tissue compositions obtained from chemical analysis. The linear correlation coefficient, Pearson's r, was used to evaluate the two image segmentation algorithms and the effect of bias field. Results: The CLIC method successfully corrected the intensity inhomogeneity induced by the bias field. In left-right comparisons, the CLIC method significantly improved the slope and the correlation coefficient of the linear fitting for the glandular volume estimation. The left-right breast density correlation was also increased from 0.93 to 0.98. When compared with the percent fibroglandular volume (%FGV) from chemical analysis, results after bias field correction from both the CLIC the FCM algorithms showed improved linear correlation. As a result, the Pearson's r increased from 0.86 to 0.92 with the bias field correction. Conclusions:The investigated CLIC method significantly increased the precision and accuracy of breast density quantification using breast MRI images by effectively correcting the bias field. It is expected that a fully automated computerized algorithm for breast density quantification may have great potential in clinical MRI applications.

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“…Another approach of creating hybrid simulations (e.g. Weibull et al, 2008), mixing known activation with real measured noise, does include this type of noise, but suffers from the major disadvantage that the data can contain unwanted activity, so the ground truth is not entirely known. The question is if a simplification of the noise model is justified when assessing statistical properties like sensitivity and specificity of activation detection.…”

Section: Discussionmentioning

confidence: 99%

“…The currently most used method is the so-called hybrid simulation (Bianciardi et al, 2004;Lange, 1999;Weibull et al, 2008;Lee et al, 2008;Lange et al, 1999;Hansen et al, 2001;Skudlarski et al, 1999). This technique combines known activation with "real" noise.…”

Section: Data Generating Methodsmentioning

confidence: 99%

How ignoring physiological noise can bias the conclusions from fMRI simulation results

Welvaert

Rosseel

2012

Journal of Neuroscience Methods

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Investigation of spatial resolution, partial volume effects and smoothing in functional MRI using artificial 3D time series

Cited by 37 publications

References 28 publications

Structural brain injury in patients with disorders of consciousness: A voxel-based morphometry study

Structural brain injury in patients with disorders of consciousness: A voxel-based morphometry study

Breast density quantification using magnetic resonance imaging (MRI) with bias field correction: A postmortem study

How ignoring physiological noise can bias the conclusions from fMRI simulation results

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