scholarly journals Intensity warping for multisite MRI harmonization

2019 ◽  
Author(s):  
J Wrobel ◽  
ML Martin ◽  
R Bakshi ◽  
PA Calabresi ◽  
M Elliot ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Cross Validation ◽  
Biological Effects ◽  
Brain Magnetic Resonance Imaging ◽  
Time Frame ◽  
Resonance Imaging ◽  
Biological Features ◽  
Magnetic Resonance Imaging Mri ◽  
Short Time

AbstractIn multisite neuroimaging studies there is often unwanted technical variation across scanners and sites. These “scanner effects” can hinder detection of biological features of interest, produce inconsistent results, and lead to spurious associations. We assess scanner effects in two brain magnetic resonance imaging (MRI) studies where subjects were measured on multiple scanners within a short time frame, so that one could assume any differences between images were due to technical rather than biological effects. We propose mica (multisite image harmonization by CDF alignment), a tool to harmonize images taken on different scanners by identifying and removing within-subject scanner effects. Our goals in the present study were to (1) establish a method that removes scanner effects by leveraging multiple scans collected on the same subject, and, building on this, (2) develop a technique to quantify scanner effects in large multisite trials so these can be reduced as a preprocessing step. We found that unharmonized images were highly variable across site and scanner type, and our method effectively removed this variability by warping intensity distributions. We further studied the ability to predict intensity harmonization results for a scan taken on an existing subject at a new site using cross-validation.

scholarly journals Can we evaluate cranial aneurysms on conventional brain magnetic resonance imaging?

2016 ◽  
Vol 7 (01) ◽  
pp. 83-86 ◽  
Author(s):  
Emine Caliskan ◽  
Yeliz Pekcevik ◽  
Adnan Kaya
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Characteristic Curve ◽  
Brain Mri ◽  
Brain Magnetic Resonance Imaging ◽  
Kappa Statistics ◽  
Resonance Imaging ◽  
Vascular Structures ◽  
Magnetic Resonance Imaging Mri ◽  
Age Range

ABSTRACT Purpose: To evaluate the contribution of conventional brain magnetic resonance imaging (MRI) for the determination of intracranial aneurysms. Materials and Methods: Brain MRI and computed tomography angiography (CTA) of 45 patients (29 women and 16 men; age range, 32–80 years) with aneurysm were analyzed. A comparison was made between brain MRI and CTA based on size and presence of aneurysm. The comparisons between MRI and CTA were investigated through Bland-Altman graphics, receiver operating characteristic curve, and Kappa statistics. Results: Fifty-seven aneurysms were evaluated. Forty-five percent of 57 aneurysms on CTA were detected on conventional brain MRI. A significant correlation was found between CTA and brain MRI in the diagnosis of aneurysm (P < 0.05). In an analysis of the size measurement, a significant correlation was observed between CTA and brain MRI. Seventy-seven percent of aneurysms <4 mm was not detected and the efficiency of MRI in the detection of aneurysms <4 mm was found to be low. Conclusion: Aneurysms can also be appreciated on conventional brain MRI, and vascular structures should be reviewed carefully while analyzing brain MRI.

Brain magnetic resonance imaging does not contribute to the diagnosis of chronic neuroborreliosis

2007 ◽  
Vol 48 (7) ◽  
pp. 755-762 ◽  
Author(s):  
A. Aalto ◽  
J. Sjöwall ◽  
L. Davidsson ◽  
P. Forsberg ◽  
Ö. Smedby
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Disease Duration ◽  
Brain Magnetic Resonance Imaging ◽  
White Matter Lesions ◽  
Resonance Imaging ◽  
Mri Findings ◽  
Significant Difference ◽  
Fluid Attenuated Inversion Recovery ◽  
Magnetic Resonance Imaging Mri

Background: Borrelia infections, especially chronic neuroborreliosis (NB), may cause considerable diagnostic problems. This diagnosis is based on symptoms and findings in the cerebrospinal fluid but is not always conclusive. Purpose: To evaluate brain magnetic resonance imaging (MRI) in chronic NB, to compare the findings with healthy controls, and to correlate MRI findings with disease duration. Material and Methods: Sixteen well-characterized patients with chronic NB and 16 matched controls were examined in a 1.5T scanner with a standard head coil. T1- (with and without gadolinium), T2-, and diffusion-weighted imaging plus fluid-attenuated inversion recovery (FLAIR) imaging were used. Results: White matter lesions and lesions in the basal ganglia were seen in 12 patients and 10 controls (no significant difference). Subependymal lesions were detected in patients down to the age of 25 and in the controls down to the age of 43. The number of lesions was correlated to age both in patients (ρ = 0.83, P<0.01) and in controls (ρ = 0.61, P<0.05), but not to the duration of disease. Most lesions were detected with FLAIR, but many also with T2-weighted imaging. Conclusion: A number of MRI findings were detected in patients with chronic NB, although the findings were unspecific when compared with matched controls and did not correlate with disease duration. However, subependymal lesions may constitute a potential finding in chronic NB.

scholarly journals Classification of Abdominal Visceral and Subcutaneous Fat Distributions by Body Shape Descriptors

2020 ◽  
Author(s):  
BUGAO XU
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Body Shape ◽  
Cross Validation ◽  
Abdominal Fat ◽  
Support Vector ◽  
Shape Descriptors ◽  
Resonance Imaging ◽  
Selection Scheme ◽  
Magnetic Resonance Imaging Mri

<p>This study aims to explore new categorization that characterizes the distribution clusters of visceral and subcutaneous adipose tissues (VAT and SAT) measured by magnetic resonance imaging (MRI); to analyze the relationship between the VAT-SAT distribution patterns and the novel body shape descriptors (BSDs); and to develop a classifier to predict the fat distribution clusters using the BSDs. 66 male and 54 female participants were scanned by magnetic resonance imaging (MRI) and a stereovision body imaging (SBI) to measure participants’ abdominal VAT and SAT volumes and the BSDs. A fuzzy <i>c-</i>means algorithm was used to form the inherent grouping clusters of abdominal fat distributions. A support-vector-machine (SVM) classifier, with an embedded feature selection scheme, was employed to determine an optimal subset of the BSDs for predicting internal fat distributions. A five-fold cross-validation procedure was used to prevent over-fitting in the classification. The classification results of the BSDs were compared with those of the traditional anthropometric measurements and the Dual Energy X-Ray Absorptiometry (DXA) measurements.<b> </b>Four clusters were identified for abdominal fat distributions: low VAT and SAT, elevated VAT and SAT, higher SAT, and higher VAT. The cross-validation accuracies of the traditional anthropometric, DXA and BSD measurements are 85.0%, 87.5% and 90%, respectively. </p>

scholarly journals An availability of brain magnetic resonance imaging(MRI) in the early diagnosis of latent hepatic encephalopathy.

Kanzo ◽  
1996 ◽  
Vol 37 (3) ◽  
pp. 170-175
Author(s):  
Naoaki KUWAHARA ◽  
Toshihiro HIGASHI ◽  
Masako TANABE ◽  
Akiko FUJIWARA ◽  
Takeshi MINATO ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Hepatic Encephalopathy ◽  
Magnetic Resonance ◽  
Early Diagnosis ◽  
Brain Magnetic Resonance Imaging ◽  
Resonance Imaging ◽  
Magnetic Resonance Imaging Mri
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