Jun Ki Lee

Hanyang University, Sŏul, Seoul, South Korea

Are you Jun Ki Lee?

Claim your profile

Publications (5)25.52 Total impact

  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Although studies of obsessive-compulsive disorder (OCD) over the last 20 years have suggested abnormalities in frontal-subcortical circuitry, evidences of structural abnormalities in those areas are still imperfect and contradictory. With recent advances in neuroimaging technology, it is now possible to study cortical thickness based on cortical surfaces, which offers a direct quantitative index of cortical mass. Using the constrained Laplacian-based automated segmentation with proximities (CLASP) algorithm, we measured cortical thickness of 55 patients with OCD (33 men and 22 women) and 52 age- and sex-matched healthy volunteers (32 men and 20 women). We found multiple regions of cortical thinning in OCD patients compared to the normal control group. Patients with OCD had thinner left inferior frontal, left middle frontal, left precentral, left superior temporal, left parahippocampal, left orbitofrontal, and left lingual cortices. Most thinned regions were located in the left ventral cortex system, providing a new perspective that this ventral cortical system may be involved in the pathophysiology of OCD.
    Human Brain Mapping 12/2007; 28(11):1128-35. · 6.92 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Visual assessment of structural MRI is, by definition, normal in patients with juvenile myoclonic epilepsy (JME), a major subsyndrome of idiopathic generalized epilepsy (IGE). However, recent quantitative MRI studies have shown structural abnormalities in cortical and thalamic grey matter (GM) in JME. Voxel-based morphometry (VBM) is a fully automated, unbiased, operator-independent MRI analysis technique that detects regionally specific differences in brain tissue composition on a voxel-wise comparison between groups of subjects. Using VBM, we examined structural differences in cortical and subcortical GM volume (GMV) between 25 JME patients (15 women, mean age=22.7+/-5.1 years) and age- and sex-matched 44 control subjects (27 women, mean age=23.1+/-4.3 years). We also performed a correlation analysis to delineate a possible relationship between the GMV increases or reductions and the increasing duration of epilepsy. Group comparison showed GMV increases in the superior mesiofrontal region bilaterally and GMV reductions in the thalamus bilaterally in JME patients (P<0.05, corrected for multiple comparisons using false discovery rate). Correlation analysis revealed that bilateral thalamic GMV had negative correlations with the duration of epilepsy (P<0.05, corrected for multiple comparisons after small volume corrections; P<0.05, Pearson correlation test). Our findings of GMV increases in the superior mesiofrontal regions and progressive thalamic atrophy could further support the pathophysiological concept of the functional abnormalities in thalamocortical circuit in JME.
    NeuroImage 11/2007; 37(4):1132-7. · 6.13 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Cortical surface reconstruction is important for functional brain mapping and morphometric analysis of the brain cortex. Several methods have been developed for the faithful reconstruction of surface models which represent the true cortical surface in both geometry and topology. However, there has been no explicit comparison study among those methods because each method has its own procedures, file formats, coordinate systems, and use of the reconstructed surface. There has also been no explicit evaluation method except visual inspection to validate the whole-cortical surface models quantitatively. In this study, we presented a novel phantom-based validation method of the cortical surface reconstruction algorithm and quantitatively cross-validated the three most prominent cortical surface reconstruction algorithms which are used in Freesurfer, BrainVISA, and CLASP, respectively. The validation included geometrical accuracy and mesh characteristics such as Euler number, fractal dimension (FD), total surface area, and local density of points. CLASP showed the best geometric/topologic accuracy and mesh characteristics such as FD and total surface area compared to Freesurfer and BrainVISA. In the validation of local density of points, Freesurfer and BrainVISA showed more even distribution of points on the cortical surface compared to CLASP.
    NeuroImage 07/2006; 31(2):572-84. · 6.13 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Accurate reconstruction of the inner and outer cortical surfaces of the human cerebrum is a critical objective for a wide variety of neuroimaging analysis purposes, including visualization, morphometry, and brain mapping. The Anatomic Segmentation using Proximity (ASP) algorithm, previously developed by our group, provides a topology-preserving cortical surface deformation method that has been extensively used for the aforementioned purposes. However, constraints in the algorithm to ensure topology preservation occasionally produce incorrect thickness measurements due to a restriction in the range of allowable distances between the gray and white matter surfaces. This problem is particularly prominent in pediatric brain images with tightly folded gyri. This paper presents a novel method for improving the conventional ASP algorithm by making use of partial volume information through probabilistic classification in order to allow for topology preservation across a less restricted range of cortical thickness values. The new algorithm also corrects the classification of the insular cortex by masking out subcortical tissues. For 70 pediatric brains, validation experiments for the modified algorithm, Constrained Laplacian ASP (CLASP), were performed by three methods: (i) volume matching between surface-masked gray matter (GM) and conventional tissue-classified GM, (ii) surface matching between simulated and CLASP-extracted surfaces, and (iii) repeatability of the surface reconstruction among 16 MRI scans of the same subject. In the volume-based evaluation, the volume enclosed by the CLASP WM and GM surfaces matched the classified GM volume 13% more accurately than using conventional ASP. In the surface-based evaluation, using synthesized thick cortex, the average difference between simulated and extracted surfaces was 4.6 +/- 1.4 mm for conventional ASP and 0.5 +/- 0.4 mm for CLASP. In a repeatability study, CLASP produced a 30% lower RMS error for the GM surface and a 8% lower RMS error for the WM surface compared with ASP.
    NeuroImage 09/2005; 27(1):210-21. · 6.13 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Registration of functional PET and MR images is a necessary step for combining functional information from PET images with anatomical information in MR images. But, the methods published are non-automatic or rigid body transformation. In this paper, we present a method that mapping PET image onto the MR image with automatic non-rigid transformation. The method is largely composed of two parts. First part is the segmentation and extracting the features of both MR and PET by using FCM and morphological methods. And, second part is the non-rigid mapping of PET image onto the PET template and MR image onto MR template. The templates are made from 20 PET images and 20 MR images each other. And, the MR template is registered with PET template. In non-rigid mapping, we use Bayesian framework in which statistical information on the imaging process is combined with prior information on expected template deformations to make inferences about the parameters of the deformation field. The method newly defines intensity similarity between the deforming scan and the target brain. Intensity similarity combined with prior information is used to generate deformation field. We applied our algorithm to PET and T1-weighted MR images from many patients. The registered images were validated by physicians. And we got the satisfactory results.
    Proceedings of SPIE - The International Society for Optical Engineering 07/2001; · 0.20 Impact Factor