Literature DB >> 22101754

3D texture analysis on MRI images of Alzheimer's disease.

Jing Zhang1, Chunshui Yu, Guilian Jiang, Weifang Liu, Longzheng Tong.   

Abstract

This study investigated three-dimensional (3D) texture as a possible diagnostic marker of Alzheimer's disease (AD). T1-weighted magnetic resonance (MR) images were obtained from 17 AD patients and 17 age and gender-matched healthy controls. 3D texture features were extracted from the circular 3D ROIs placed using a semi-automated technique in the hippocampus and entorhinal cortex. We found that classification accuracies based on texture analysis of the ROIs varied from 64.3% to 96.4% due to different ROI selection, feature extraction and selection options, and that most 3D texture features selected were correlated with the mini-mental state examination (MMSE) scores. The results indicated that 3D texture could detect the subtle texture differences between tissues in AD patients and normal controls, and texture features of MR images in the hippocampus and entorhinal cortex might be related to the severity of AD cognitive impairment. These results suggest that 3D texture might be a useful aid in AD diagnosis.

Entities:  

Mesh:

Year:  2012        PMID: 22101754     DOI: 10.1007/s11682-011-9142-3

Source DB:  PubMed          Journal:  Brain Imaging Behav        ISSN: 1931-7557            Impact factor:   3.978


  27 in total

1.  Early detection of Alzheimer's disease using MRI hippocampal texture.

Authors:  Lauge Sørensen; Christian Igel; Naja Liv Hansen; Merete Osler; Martin Lauritzen; Egill Rostrup; Mads Nielsen
Journal:  Hum Brain Mapp       Date:  2015-12-21       Impact factor: 5.038

2.  Magnetic resonance imaging texture predicts progression to dementia due to Alzheimer disease earlier than hippocampal volume

Authors:  Subin Lee; Hyunna Lee; Ki Woong Kim
Journal:  J Psychiatry Neurosci       Date:  2020-01-01       Impact factor: 6.186

3.  Edge Contrast of the FLAIR Hyperintense Region Predicts Survival in Patients with High-Grade Gliomas following Treatment with Bevacizumab.

Authors:  N Bahrami; D Piccioni; R Karunamuni; Y-H Chang; N White; R Delfanti; T M Seibert; J A Hattangadi-Gluth; A Dale; N Farid; C R McDonald
Journal:  AJNR Am J Neuroradiol       Date:  2018-04-05       Impact factor: 3.825

4.  A computerized MRI biomarker quantification scheme for a canine model of Duchenne muscular dystrophy.

Authors:  Jiahui Wang; Zheng Fan; Krista Vandenborne; Glenn Walter; Yael Shiloh-Malawsky; Hongyu An; Joe N Kornegay; Martin A Styner
Journal:  Int J Comput Assist Radiol Surg       Date:  2013-01-09       Impact factor: 2.924

5.  MRI texture analysis predicts p53 status in head and neck squamous cell carcinoma.

Authors:  M Dang; J T Lysack; T Wu; T W Matthews; S P Chandarana; N T Brockton; P Bose; G Bansal; H Cheng; J R Mitchell; J C Dort
Journal:  AJNR Am J Neuroradiol       Date:  2014-09-25       Impact factor: 3.825

6.  Sevoflurane exposure in postnatal rats induced long-term cognitive impairment through upregulating caspase-3/cleaved-poly (ADP-ribose) polymerase pathway.

Authors:  Yunzhi Ling; Xiaohong Li; Li Yu; Qisheng Liang; Xuewu Lin; Xiaodi Yang; Hongtao Wang; Ye Zhang
Journal:  Exp Ther Med       Date:  2017-08-22       Impact factor: 2.447

7.  Molecular classification of patients with grade II/III glioma using quantitative MRI characteristics.

Authors:  Naeim Bahrami; Stephen J Hartman; Yu-Hsuan Chang; Rachel Delfanti; Nathan S White; Roshan Karunamuni; Tyler M Seibert; Anders M Dale; Jona A Hattangadi-Gluth; David Piccioni; Nikdokht Farid; Carrie R McDonald
Journal:  J Neurooncol       Date:  2018-06-02       Impact factor: 4.130

8.  Brain MR Radiomics to Differentiate Cognitive Disorders.

Authors:  Sara Ranjbar; Stefanie N Velgos; Amylou C Dueck; Yonas E Geda; J Ross Mitchell
Journal:  J Neuropsychiatry Clin Neurosci       Date:  2019-01-14       Impact factor: 2.198

9.  Identification of voxel-based texture abnormalities as new biomarkers for schizophrenia and major depressive patients using layer-wise relevance propagation on deep learning decisions.

Authors:  A I Korda; A Ruef; S Neufang; C Davatzikos; S Borgwardt; E M Meisenzahl; N Koutsouleris
Journal:  Psychiatry Res Neuroimaging       Date:  2021-05-16       Impact factor: 2.493

10.  Classifying dementia using local binary patterns from different regions in magnetic resonance images.

Authors:  Ketil Oppedal; Trygve Eftestøl; Kjersti Engan; Mona K Beyer; Dag Aarsland
Journal:  Int J Biomed Imaging       Date:  2015-03-22
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