scholarly journals CO-OCCURRENCE MATRIX IN LONGITUDINAL DIFFERENTIATION OF MRI IMAGES OF PATIENTS WITH AD, MCI, AND HEALTHY INDIVIDUALS

2021 ◽  
Author(s):  
Daniella de Oliveira ◽  
Amanda Nascimento ◽  
Rafael da Silveira ◽  
Isadora Ribeiro ◽  
Thamires Magalhães ◽  
...  
Keyword(s):  
Brain Mri ◽  
Magnetic Resonance Images ◽  
Analysis Of Covariance ◽  
Precentral Gyrus ◽  
Test Results ◽  
Texture Parameters ◽  
Background Texture ◽  
Neurological Conditions ◽  
Longitudinal Differentiation ◽  
Occurrence Matrix

Background: Texture analysis based on the gray level co-occurrence matrix (GLCM) has been applied to brain magnetic resonance images (MRI) to detect subtle differences among healthy and lesioned tissue occurring in several neurological conditions, but it has rarely been used in longitudinal AD studies. Objectives: To perform a longitudinal study by applying GLCM to brain MRI of AD and MCI patients and of healthy controls (HC), to verify the suitability of this technique to help detect the evolution of these conditions. Methods: Participants were 14 AD, 21 MCI and 17 HC, who had 2 T1-MRI obtained ~12 months apart. MRI were segmented using the AAL atlas. 3D GLCMs were computed for five voxel distances, for 16 regions per subject. A total of 55 texture parameters were extracted per region per subject. Statistical differences were evaluated using a t test. Results: Significant differences were found only for the MCI group, for the left precentral gyrus and left supplementary motor area, for which the correlation parameter decreased over time at different distances. Conclusions: This result could be due to a subtle motor loss in the MCI group before the onset of AD symptoms, or even, patients in the MCI group could progress to neurodegenerative diseases other than AD. The next step is to compare the obtained texture parameters between groups using analysis of covariance.

scholarly journals Effect of Paper and E-Dictionaries on Iranian EFL Learners' Reading Comprehension

2017 ◽  
Vol 6 (5) ◽  
pp. 199
Author(s):  
Shiva Grami ◽  
Mahmood Hashemian
Keyword(s):  
Reading Comprehension ◽  
Foreign Language ◽  
Language Learners ◽  
Analysis Of Covariance ◽  
Control Group ◽  
Test Results ◽  
Efl Learners ◽  
Foreign Language Learners ◽  
Paired Samples ◽  
Treatment Design

The purpose of this study was to investigate the effects of paper and e-dictionaries on Iranian intermediate learners' reading comprehension. To this end, 90 female English Foreign language learners were randomly selected and assigned into 2 experimental groups (e-dictionaries and paper dictionaries groups) and 1 control group. All the groups took a pretest using no dictionaries. After 2 weeks of treatment design for the experimental groups, all the 3 groups took part in the posttest. The experimental groups did their task with their relevant dictionaries, whereas the control group did their task without using any kind of dictionary. Data were analyzed through analysis of covariance (ANCOVA) and paired samples t test. Results showed that the participants’ reading comprehension improved from the pretest to the posttest in both experimental groups. Results also indicated that the learners in the e-dictionaries group outperformed those in the paper dictionaries group. The outcome of study reveals that e-dictionaries could improve students’ reading comprehension by motivating them, shortening the time of searching words and reading a text, and increasing the number of look ups. 

Non-inflammation cerebrospinal fluid and normal brain magnetic resonance images of Autoimmune encephalits

2019 ◽  
Author(s):  
Yake Zheng ◽  
Peng Zhao ◽  
yajun lian ◽  
Lihao Li ◽  
Yuan Chen ◽  
...  
Keyword(s):  
Cerebrospinal Fluid ◽  
Magnetic Resonance ◽  
Clinical Symptoms ◽  
Brain Mri ◽  
Clinical Manifestations ◽  
Speech Disorders ◽  
Magnetic Resonance Images ◽  
Normal Brain ◽  
Recurrence Rates ◽  
Clinical Prognosis

Abstract Background We set out to investigate the characteristics and factors related to non-inflammation cerebrospinal fluid (CSF) and normal brain magnetic resonance images (MRI) of autoimmune encephalitis (AE) in patients. Methods The distribution and characteristics of brain MRI and CSF in 124 patients who were living with anti-NMDAR(71), LGI1(26),CASPR2(4),GABAR(23) encephalitis and who had been admitted between October 2016 and May 2018 were analyzed prospectively. Results 12 of the 124 patients(1%) had a normal MRI and non-inflammation CSF.Ten of them were LGI1(83%),while the remaining 1 patient was NMDAR(8.3%),1 patient was CASPR2(8.3%).The clinical symptoms including epilepsy, psychosis, cognitive disorders, conscious disorders, headache, faciobrachial dystonic seizure (FBDS), speech disorders and hypoventilation. AE with non-inflammation CSF and normal MRI with good clinical prognosis. The median modified Rankin Scale (mRS) was low, and recurrence rate was also low. Conclusion The clinical manifestations of on-inflammation CSF and brain MRI-negative patients with AE are not specific, but suggest a better prognosis and a lower recurrence rates.

scholarly journals An Efficient Automatic Midsagittal Plane Extraction in Brain MRI

2018 ◽  
Vol 8 (11) ◽  
pp. 2203 ◽  
Author(s):  
Hafiz Rehman ◽  
Sungon Lee
Keyword(s):  
Brain Mri ◽  
Principal Component ◽  
Bilateral Symmetry ◽  
Magnetic Resonance Images ◽  
Superior Performance ◽  
Computationally Efficient ◽  
Midsagittal Plane ◽  
Accuracy And Precision ◽  
Principal Axes ◽  
Plane Extraction

In this paper, a fully automatic and computationally efficient midsagittal plane (MSP) extraction technique in brain magnetic resonance images (MRIs) has been proposed. Automatic detection of MSP in neuroimages can significantly aid in registration of medical images, asymmetric analysis, and alignment or tilt correction (recenter and reorientation) in brain MRIs. The parameters of MSP are estimated in two steps. In the first step, symmetric features and principal component analysis (PCA)-based technique is used to vertically align the bilateral symmetric axis of the brain. In the second step, PCA is used to achieve a set of parallel lines (principal axes) from the selected two-dimensional (2-D) elliptical slices of brain MRIs, followed by a plane fitting using orthogonal regression. The developed algorithm has been tested on 157 real T1-weighted brain MRI datasets including 14 cases from the patients with brain tumors. The presented algorithm is compared with a state-of-the-art approach based on bilateral symmetry maximization. Experimental results revealed that the proposed algorithm is fast (<1.04 s per MRI volume) and exhibits superior performance in terms of accuracy and precision (a mean z-distance of 0.336 voxels and a mean angle difference of 0.06).

scholarly journals Reliability of Synthetic Brain MRI for Assessment of Ischemic Stroke with Phantom Validation of a Relaxation Time Determination Method

2020 ◽  
Vol 9 (6) ◽  
pp. 1857
Author(s):  
Chia-Wei Li ◽  
Ai-Ling Hsu ◽  
Chi-Wen C. Huang ◽  
Shih-Hung Yang ◽  
Chien-Yuan Lin ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Relaxation Time ◽  
Brain Mri ◽  
Relaxation Times ◽  
Onset Time ◽  
Magnetic Resonance Images ◽  
Diagnostic Tools ◽  
Cupric Sulfate ◽  
T2 Relaxation ◽  
T1 And T2

The reliability of relaxation time measures in synthetic magnetic resonance images (MRIs) of homemade phantoms were validated, and the diagnostic suitability of synthetic imaging was compared to that of conventional MRIs for detecting ischemic lesions. Phantoms filled with aqueous cupric-sulfate (CuSO4) were designed to mimic spin-lattice (T1) and spin-spin (T2) relaxation properties and were used to compare their accuracies and stabilities between synthetic and conventional scans of various brain tissues. To validate the accuracy of synthetic imaging in ischemic stroke diagnoses, the synthetic and clinical scans of 18 patients with ischemic stroke were compared, and the quantitative contrast-to-noise ratios (CNRs) were measured, using the Friedman test to determine significance in differences. Results using the phantoms showed no significant differences in the interday and intersession synthetic quantitative T1 and T2 values. However, between synthetic and referenced T1 and T2 values, differences were larger for longer relaxation times, showing that image intensities in synthetic scans are relatively inaccurate in the cerebrospinal fluid (CSF). Similarly, CNRs in CSF regions of stroke patients were significantly different on synthetic T2-weighted and T2-fluid-attenuated inversion recovery images. In contrast, differences in stroke lesions were insignificant between the two. Therefore, interday and intersession synthetic T1 and T2 values are highly reliable, and discrepancies in synthetic T1 and T2 relaxation times and image contrasts in CSF regions do not affect stroke lesion diagnoses. Additionally, quantitative relaxation times from synthetic images allow better estimations of ischemic stroke onset time, consequently increasing confidence in synthetic MRIs as diagnostic tools for ischemic stroke.

scholarly journals Volume and shape of subcortical grey matter structures related to headache: A cross-sectional population-based imaging study in the Nord-Trøndelag Health Study

Cephalalgia ◽  
2018 ◽  
Vol 39 (2) ◽  
pp. 173-184 ◽  
Author(s):  
Andreas Kattem Husøy ◽  
Carl Pintzka ◽  
Live Eikenes ◽  
Asta K Håberg ◽  
Knut Hagen ◽  
...  
Keyword(s):  
Brain Mri ◽  
Depression Scale ◽  
Imaging Study ◽  
Population Based ◽  
Tension Type Headache ◽  
Analysis Of Covariance ◽  
Health Study ◽  
Intracranial Volume ◽  
Cross Sectional ◽  
Subcortical Nuclei

Background The relationship between subcortical nuclei and headache is unclear. Most previous studies were conducted in small clinical migraine samples. In the present population-based MRI study, we hypothesized that headache sufferers exhibit reduced volume and deformation of the nucleus accumbens compared to non-sufferers. In addition, volume and deformation of the amygdala, caudate, hippocampus, pallidum, putamen and thalamus were examined. Methods In all, 1006 participants (50–66 years) from the third Nord-Trøndelag Health Survey, were randomly selected to undergo a brain MRI at 1.5 T. Volume and shape of the subcortical nuclei from T1 weighted 3D scans were obtained in FreeSurfer and FSL. The association with questionnaire-based headache categories (migraine and tension-type headache included) was evaluated using analysis of covariance. Individuals not suffering from headache were used as controls. Age, sex, intracranial volume and Hospital Anxiety and Depression Scale were used as covariates. Results No effect of headache status on accumbens volume and shape was present. Exploratory analyses showed significant but small differences in volume of caudate and putamen and in putamen shape between those with non-migrainous headache and the controls. A post hoc analysis showed that caudate volume was strongly associated with white matter hyperintensities. Conclusion We did not confirm our hypothesis that headache sufferers have smaller volume and different shape of the accumbens compared to non-sufferers. No or only small differences in volume and shape of subcortical nuclei between headache sufferers and non-sufferers appear to exist in the general population.

scholarly journals ALTEA: A Software Tool for the Evaluation of New Biomarkers for Alzheimer’s Disease by Means of Textures Analysis on Magnetic Resonance Images

Diagnostics ◽  
2018 ◽  
Vol 8 (3) ◽  
pp. 47 ◽  
Author(s):  
Carlos López-Gómez ◽  
Rafael Ortiz-Ramón ◽  
Enrique Mollá-Olmos ◽  
David Moratal ◽  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Magnetic Resonance ◽  
Texture Analysis ◽  
Software Tool ◽  
Magnetic Resonance Images ◽  
Gray Level ◽  
Predictive Capacity ◽  
Texture Parameters ◽  
New Biomarkers

The current criteria for diagnosing Alzheimer’s disease (AD) require the presence of relevant cognitive deficits, so the underlying neuropathological damage is important by the time the diagnosis is made. Therefore, the evaluation of new biomarkers to detect AD in its early stages has become one of the main research focuses. The purpose of the present study was to evaluate a set of texture parameters as potential biomarkers of the disease. To this end, the ALTEA (ALzheimer TExture Analyzer) software tool was created to perform 2D and 3D texture analysis on magnetic resonance images. This intuitive tool was used to analyze textures of circular and spherical regions situated in the right and left hippocampi of a cohort of 105 patients: 35 AD patients, 35 patients with early mild cognitive impairment (EMCI) and 35 cognitively normal (CN) subjects. A total of 25 statistical texture parameters derived from the histogram, the Gray-Level Co-occurrence Matrix and the Gray-Level Run-Length Matrix, were extracted from each region and analyzed statistically to study their predictive capacity. Several textural parameters were statistically significant (p < 0.05) when differentiating AD subjects from CN and EMCI patients, which indicates that texture analysis could help to identify the presence of AD.

scholarly journals Analysis of patients with obstructive sleep apnea with and without pharyngeal myopathy using brain neuroimaging

SLEEP ◽  
2019 ◽  
Author(s):  
Camila Bonfanti Baima ◽  
Natália Castro Fim ◽  
Karen Fernanda Alves ◽  
Luiz Antonio de Lima Resende ◽  
Ronaldo Guimarães Fonseca ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Brain Mri ◽  
Sleep Apnea Syndrome ◽  
Upper Airway ◽  
Middle Temporal Gyrus ◽  
Precentral Gyrus ◽  
Obstructive Sleep ◽  
Volumetric Images ◽  
Magnetic Resonance Imaging Mri

Abstract Study Objectives Elements impairing upper airway anatomy or muscle function (e.g. pharyngeal neuromyopathy) contribute to obstructive sleep apnea syndrome (OSAS). Structural brain imaging may differ in patients with OSAS according to dilator muscle dysfunction. Magnetic resonance imaging (MRI) with voxel-based morphometry (VBM) and surface-based morphometry (SBM) was used to investigate this hypothesis. Methods Eighteen patients with OSAS and 32 controls underwent 3T brain MRI. T1 volumetric images were used for structural analysis. Pharyngeal electroneuromyography was performed; patients with OSAS were classified as with or without neuromyopathy. VBM and SBM analyses were conducted using SPM12 and CAT12 software. Image processing was standard. Cortical surface parameters and gray and white matter volumes from participants with OSAS with and without neuromyopathy were compared with those from controls. Results Eleven patients had OSAS with neuromyopathy and seven patients had OSAS without neuromyopathy (normal pharyngeal electroneuromyography). Comparing these groups to the controls, VBM revealed: four clusters (total volume 15,368 mm3) for patients with neuromyopathy, the largest cluster in the left cerebellum (9,263 mm3, p = 0.0001), and three clusters (total 8,971 mm3) for patients without neuromyopathy, the largest cluster in the left cerebellum (5,017 mm3, p = 0.002). Patients with OSAS with neuromyopathy showed increased proportion of atrophy (p < 0.0001). SBM showed abnormalities in patients without neuromyopathy (decreased cortical thickness, left precentral gyrus [672 vertices, p = 0.04]; increased cortical complexity, right middle temporal gyrus [578 vertices, p = 0.032]). Conclusion Damaged areas were larger in patients with OSAS with than in those without neuromyopathy, suggesting differences in brain involvement. Patients with OSAS and neuromyopathy may be more susceptible to cerebral damage.

Research on Predicting Model of Surface Roughness for Ground Engineering Ceramics

2012 ◽  
Vol 476-478 ◽  
pp. 1036-1040
Author(s):  
Xin Li Tian ◽  
Jian Quan Wang ◽  
Bao Guo Zhang ◽  
Fu Qiang Li
Keyword(s):  
Ground Surface ◽  
Texture Features ◽  
Engineering Ceramics ◽  
Texture Parameters ◽  
Digital Microscope ◽  
Occurrence Matrix ◽  
The Relationship ◽  
Regression Theory ◽  
Surface Images

Grinding is the mostly leading machining technology for engineering ceramics. The quality of ground surface can be evaluated by various roughness parameters. And a textural analysis method based on Gray Level Co-occurrence Matrix was employed in researching the roughness of ground ceramics. The relationship between texture features and roughness was investigated through a series of surface images of engineering ceramics collected by a digital microscope. The sampling offset and total gray levels of surface images were determined firstly. Then 4 GLCMs were built up to calculate the average of texture features. And 6 parameters were fixed as main texture parameters. Furthermore, the multiple nonlinear regression theory was used to assess the relation between the texture features and roughness Ra. By statistic test and comparison, the deviation of calculated Ra and actual Ra is less than 0.25. It is shown that this relation is much satisfactory and the method may be suitable for quickly measuring the roughness of ground ceramics.

Computer Aided Interpretation of Fibrous Texture in Hepatic Magnetic Resonance Images

2013 ◽  
Vol 647 ◽  
pp. 325-330 ◽  
Author(s):  
Yu Fan Zeng ◽  
Xue Jun Zhang ◽  
Wen Yan ◽  
Li Ling Long ◽  
Yu Kun Huang ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Hepatic Fibrosis ◽  
Region Of Interest ◽  
Texture Features ◽  
Magnetic Resonance Images ◽  
Optimal Number ◽  
Support Vector ◽  
Mr Images ◽  
Accuracy Rate ◽  
Occurrence Matrix

The fibrous texture in liver is one of important signs for interpreting the chronic liver diseases in radiologists’ routines. In order to investigate the usefulness of various texture features calculated by computer algorithm on hepatic magnetic resonance (MR) images, 15 texture features were calculated from the gray level co-occurrence matrix (GLCM) within a region of interest (ROI) which was selected from the MR images with 6 stages of hepatic fibrosis. By different combination of 15 features as input vectors, the classifier had different performance in staging the hepatic fibrosis. Each combination of texture features was tested by Support Vector Machine (SVM) with leave one case out method. 173 patients’ MR images including 6 stages of hepatic fibrosis were scanned within recent two years. The result showed that optimal number of features was confirmed from 3 to 7 by investigating the classified accuracy rate between each stage/group. It is evident that angular second moment, entropy, sum average and sum entropy played the most significant role in classification.

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