Literature DB >> 16965928

Shaving diffusion tensor images in discriminant analysis: a study into schizophrenia.

M W A Caan1, K A Vermeer, L J van Vliet, C B L M Majoie, B D Peters, G J den Heeten, F M Vos.   

Abstract

A technique called 'shaving' is introduced to automatically extract the combination of relevant image regions in a comparative study. No hypothesis is needed, as in conventional pre-defined or expert selected region of interest (ROI)-analysis. In contrast to traditional voxel based analysis (VBA), correlations within the data can be modeled using principal component analysis (PCA) and linear discriminant analysis (LDA). A study into schizophrenia using diffusion tensor imaging (DTI) serves as an application. Conventional VBA found a decreased fractional anisotropy (FA) in a part of the genu of the corpus callosum and an increased FA in larger parts of white matter. The proposed method reproduced the decrease in FA in the corpus callosum and found an increase in the posterior limb of the internal capsule and uncinate fasciculus. A correlation between the decrease in the corpus callosum and the increase in the uncinate fasciculus was demonstrated.

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Year:  2006        PMID: 16965928     DOI: 10.1016/j.media.2006.07.006

Source DB:  PubMed          Journal:  Med Image Anal        ISSN: 1361-8415            Impact factor:   8.545


  17 in total

1.  Biomarkers for identifying first-episode schizophrenia patients using diffusion weighted imaging.

Authors:  Yogesh Rathi; James Malcolm; Oleg Michailovich; Jill Goldstein; Larry Seidman; Robert W McCarley; Carl-Fredrik Westin; Martha E Shenton
Journal:  Med Image Comput Comput Assist Interv       Date:  2010

2.  Individualized prediction of schizophrenia based on the whole-brain pattern of altered white matter tract integrity.

Authors:  Yu-Jen Chen; Chih-Min Liu; Yung-Chin Hsu; Yu-Chun Lo; Tzung-Jeng Hwang; Hai-Gwo Hwu; Yi-Tin Lin; Wen-Yih Isaac Tseng
Journal:  Hum Brain Mapp       Date:  2017-10-28       Impact factor: 5.038

3.  Diffusion tensor imaging reliably differentiates patients with schizophrenia from healthy volunteers.

Authors:  Babak A Ardekani; Ali Tabesh; Serge Sevy; Delbert G Robinson; Robert M Bilder; Philip R Szeszko
Journal:  Hum Brain Mapp       Date:  2011-01       Impact factor: 5.038

4.  Diffusion based abnormality markers of pathology: toward learned diagnostic prediction of ASD.

Authors:  Madhura Ingalhalikar; Drew Parker; Luke Bloy; Timothy P L Roberts; Ragini Verma
Journal:  Neuroimage       Date:  2011-05-14       Impact factor: 6.556

5.  Complementary diffusion tensor imaging study of the corpus callosum in patients with first-episode and chronic schizophrenia.

Authors:  Xiangjuan Kong; Xuan Ouyang; Haojuan Tao; Haihong Liu; Li Li; Jingping Zhao; Zhimin Xue; Fei Wang; Shaoai Jiang; Baoci Shan; Zhening Liu
Journal:  J Psychiatry Neurosci       Date:  2011-03       Impact factor: 6.186

Review 6.  Machine learning and radiology.

Authors:  Shijun Wang; Ronald M Summers
Journal:  Med Image Anal       Date:  2012-02-23       Impact factor: 8.545

7.  HARDI based pattern classifiers for the identification of white matter pathologies.

Authors:  Luke Bloy; Madhura Ingalhalikar; Harini Eavani; Timothy P L Roberts; Robert T Schultz; Ragini Verma
Journal:  Med Image Comput Comput Assist Interv       Date:  2011

8.  Single-subject classification of schizophrenia using event-related potentials obtained during auditory and visual oddball paradigms.

Authors:  Andres H Neuhaus; Florin C Popescu; John A Bates; Terry E Goldberg; Anil K Malhotra
Journal:  Eur Arch Psychiatry Clin Neurosci       Date:  2012-05-15       Impact factor: 5.270

Review 9.  Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls.

Authors:  Mohammad R Arbabshirani; Sergey Plis; Jing Sui; Vince D Calhoun
Journal:  Neuroimage       Date:  2016-03-21       Impact factor: 6.556

10.  Towards a brain-based predictome of mental illness.

Authors:  Barnaly Rashid; Vince Calhoun
Journal:  Hum Brain Mapp       Date:  2020-05-06       Impact factor: 5.038

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