Detection and analysis of T2DM biomarkers from brain MR images using BrainLab

Author

Bo Peng ; Gang Li ; Zhiye Chen ; Bin Lv ; Dinggang Shen ; Lin Ma ; Yakang Dai

Author_Institution

Suzhou Inst. of Biomed. Eng. & Technol., Suzhou, China

fYear

2014

fDate

14-16 Oct. 2014

Firstpage

174

Lastpage

178

Abstract

Detection and analysis of the brain structural abnormalities from MR images are critical for early diagnosis of type 2 diabetes mellitus (T2DM). However, to date, T2DM biomarkers from brain MR images are still not completely clear. In this study, we investigated T2DM biomarkers using BrainLab, which is our recently developed toolbox for automated analysis of brain MR images. Specifically, our subjects included 10 patients with T2DM and 10 normal controls (NC). All subjects were processed using BrainLab toolbox automatically. Changes of gray matter volumes and cortical thickness were detected and analyzed. Atrophy of gray matter and cortical thickness in brain regions, such as temporal lobe, frontal lobe, and limbic lobe, revealed the potential T2DM biomarkers.

Keywords

biomedical MRI; brain; diseases; image segmentation; medical image processing; BrainLab toolbox; T2DM Biomarkers Analysis; T2DM biomarkers detection; automated analysis; brain MRI; brain magnetic resonance images; brain regions; brain structural abnormalities; cortical thickness; frontal lobe; gray matter atrophy; gray matter volumes; limbic lobe; temporal lobe; type 2 diabetes mellitus diagnosis; Atrophy; Diabetes; Image segmentation; Magnetic resonance imaging; Surface reconstruction; Temporal lobe; brain labeling; brain segmentation; cortical surface reconstruction; cortical thickness; magnetic resonance image; type 2 diabetes;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Engineering and Informatics (BMEI), 2014 7th International Conference on

Conference_Location

Dalian

Print_ISBN

978-1-4799-5837-5

Type

conf

DOI

10.1109/BMEI.2014.7002765

Filename

7002765