File Download

There are no files associated with this item.

  • Find it @ UNIST can give you direct access to the published full text of this article. (UNISTARs only)
Related Researcher


Lyu, Ilwoo
3D Shape Analysis Lab.
Read More

Views & Downloads

Detailed Information

Cited time in webofscience Cited time in scopus
Metadata Downloads

Automated Volumetric Determination of High R2* Regions in Substantia Nigra : A Feasibility Study of Quantifying SN Atrophy in Progressive Supranulcear Palsy

Tessema, Abel WorkuLee, HansolGong, YelimCho, HwapyeongAdem, Hamdia MuradLyu, IlwooLee, JaehyeokCho, Hyungjoon
Issued Date
NMR IN BIOMEDICINE, v.35, no.11, pp.e4795
The establishment of an unbiased protocol for the automated volumetric measurement of iron-rich regions in the substantia nigra (SN) is clinically important for diagnosing neurodegenerative diseases exhibiting midbrain atrophy, such as progressive supranuclear palsy (PSP). This study aimed to automatically quantify the volume and surface properties of the iron-rich 3D regions in the SN using the quantitative MRI-R2* map. Three hundred and sixty-seven slices of R2* map and susceptibility-weighted imaging (SWI) at 3-T MRI from healthy control (HC) individuals and Parkinson's disease (PD) patients were used to train customized U-net++ convolutional neural network based on expert-segmented masks. Age- and sex-matched participants were selected from HC, PD, and PSP groups to automate the volumetric determination of iron-rich areas in the SN. Dice similarity coefficient values between expert-segmented and detected masks from the proposed network were for R2* maps and for SWI. Reductions in iron-rich SN volume from the R2* map (SWI) were observed in PSP with area under the receiver operating characteristic curve values of 0.96 (0.89) and 0.98 (0.92) compared with HC and PD, respectively. The mean curvature of the PSP showed SN deformation along the side closer to the red nucleus. We demonstrated the automated volumetric measurement of iron-rich regions in the SN using deep learning can quantify the SN atrophy in PSP compared with PD and HC.
Keyword (Author)
convolutional neural networkprogressive supranuclear palsyquantitative analysissegmentationsubstantia nigra


Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.