Biomedical subjects

In-Young Kim

Publications and source records attributed to In-Young Kim.

4 recordsLinked to original sources

PubMed2003

Evaluation of automated and semi-automated skull-stripping algorithms using similarity index and segmentation error.

The skull-stripping in the MR brain image appears to be a key issue in neuroimage analysis. In this paper, we evaluated the accuracy and efficiency of both automated and semi-automated skull-stripping methods. The evaluation was performed on both simulated and real data with the ground truth in skull-stripping. Although automated method showed better efficient results, it should require additional intervention. In contrast to that, semi-automated method showed better accurate results, but it was time consuming and prone to operator bias. Therefore, it might be practical that the semi-automated method was used as the post-processing of the automated one.

Algorithms↗

PubMed2003

A PC-based high-quality and interactive virtual endoscopy navigating system using 3D texture based volume rendering.

As an alternative method to optical endoscopy, visual quality and interactivity are crucial for virtual endoscopy. One solution is to use the 3D texture map based volume rendering method that offers high rendering speed without reducing visual quality. However, it is difficult to apply the method to virtual endoscopy. First, 3D texture mapping requires a high-end graphic workstation. Second, texture memory limits reduce the frame-rate. Third, lack of shading reduces visual quality significantly. As 3D texture mapping has become available on personal computers recently, we developed an interactive navigation system using 3D texture mapping on a personal computer. We divided the volume data into small cubes and tested whether the cubes had meaningful data. Only the cubes that passed the test were loaded into the texture memory and rendered. With the amount of data to be rendered minimized, rendering speed increased remarkably. We also improved visual quality by implementing full Phong shading based on the iso-surface shading method without sacrificing interactivity. With the developed navigation system, 256 x 256 x 256 sized brain MRA data was interactively explored with good image quality.

Anatomy, Cross-Sectional↗

PubMed2002

Metastatic spinal cord compression of testicular yolk sac tumor.

INTRODUCTION: Pediatric testicular tumors are rare. Spinal metastasis of testicular yolk sac tumor (YST) is extremely rare, with only one reported case. CASE REPORT: We report a rare case of metastatic spinal cord compression of testicular YST in a 14-month-old boy who presented with progressive paraparesis and neurological bladder dysfunction. Two months prior to admission, he underwent a left radical orchiectomy for YST of the testis. Magnetic resonance imaging revealed severe spinal cord compression by the ventral epidural mass from T-9 to T-11 and at S-3. Emergency surgical resection was performed for tissue diagnosis and spinal decompression. Histopathological features of the epidural mass indicated metastasis of the testicular YST. CONCLUSION: Although spinal involvement with metastatic YST is rare, it must be considered in children with testicular YST exhibiting evidence of pain or weakness, and surgical decompression followed by adjuvant chemotherapy should not be delayed.

Decompression, Surgical↗

PubMed2002

Intensity based affine registration including feature similarity for spatial normalization.

This paper presents a new spatial normalization with affine transformation. The quantitative comparison of brain architecture across different subjects requires a common coordinate system. For the analysis of a specific brain area, it is required to normalize and compare a region of interest and global brain. Intensity based registration method matches the global brain well. But a region of interest may not be locally normalized compared to feature based method. The method of this paper uses feature similarities of local region as well as intensity similarities. The lateral ventricle and the central gray nuclei of brain including the corpus callosum, which is used for features in Schizophrenia detection, is appropriately normalized. In the results section, our method reduces the difference of feature area such as corpus callosum (7.7%, 2.4%) and lateral ventricle (8.2%, 13.5%) compared with mutual information and Talairach methods.

Algorithms↗