• Current Optics and Photonics
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• 제5권5호
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• pp.554-561
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• 2021

Indocyanine green (ICG) is a cyanine dye that has been used in medical diagnostics based on fluorescence imaging, and in medical therapy based on the photothermal effect. It is important to systematically understand the photothermal effect and fluorescence characteristics of ICG simultaneously. By varying a number of conditions such as laser power density, laser irradiation wavelength, concentration of ICG solution, and exposure time of laser irradiation, the intensity properties of fluorescence and the temperature change induced by the photothermal effect are measured simultaneously using a charge-coupled-device camera and a thermal-imaging camera. The optimal conditions for maximizing the photothermal effect are determined, while maintaining a relatively long lifetime and high efficiency of the fluorescence for fluorescence imaging. When the concentration of ICG is approximately 50 ㎍/ml and the laser power density exceeds 1.5 W/cm², the fluorescence lifetime is the longest and the temperature induced by the photothermal effect rapidly increases, exceeding the critical temperature sufficient to damage human cells and tissues. The findings provide useful insight into the realization of effective photothermal therapy, while also specifying the site to be treated and enabling real-time treatment monitoring.

• 전자통신동향분석
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• 제36권5호
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• pp.1-8
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• 2021

Over the last three decades, the development of Ti:sapphire femtosecond lasers has led to advancements in scientific and industrial fields. In particular, these advanced lasers show great potential for applications with bio-imaging and medical surgery, such as two-photon microscopy, nonlinear Raman microscopy, optical coherence tomography, and ophthalmic surgery. Herein, we present a detailed description of the theoretical and experimental physics of Kerr-lens mode-locked femtosecond Ti:sapphire lasers and its two-photon microscopy.

• 한국멀티미디어학회논문지
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• 제19권8호
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• pp.1236-1247
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• 2016

Recently, the level set has become a popular method in many research fields. The main reason is that it can be modified into many variants. One such case is our proposed method. We describe a contrast-enhancement method to segment the hippocampal region from the background. However, the hippocampus region has quite similar intensities to the neighboring pixel intensities. In addition, to handle the inhomogeneous intensities of the hippocampus, we used a bias correction before hippocampal segmentation. Thus, we developed a contrast-enhanced bias-corrected distance-regularized level set (CBDLS) to segment the hippocampus in magnetic resonance imaging (MRI). It shows better performance than the distance-regularized level set evolution (DLS) and bias-corrected distance-regularized level set (BDLS) methods in 33 MRI images of one normal patient. Segmentation after contrast enhancement and bias correction can be done more accurately than segmentation while not using a bias-correction method and without contrast enhancement.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2009년도 9th International Meeting on Information Display
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• pp.1354-1356
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• 2009

In this paper, we explained characteristics of integral imaging microscope using point light source. To display the bio-medical information, which is captured as a form of the elemental images, using autostereoscopic displays, the characteristics analysis of three-dimensional information is required. For integral imaging microscope using point light source array, the elemental image capturing configuration has to satisfy a specific condition. We explain the condition to capture the elemental images and show the experimental results.

• 대한의생명과학회지
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• 제25권1호
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• pp.7-14
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• 2019

Alzheimer's disease (AD) is highly prevalent in dementia, with no specifically effective treatment having yet been discovered. Amyloid plaques are one of the key hallmarks of AD. Transgenic mouse models exhibiting Alzheimer's disease-like pathology have been widely used to study the pathophysiology of Alzheimer's disease. In this study, we showed an age-dependent correlation between cognitive function, pathological findings, and [F-18] Florbetaben (FBB) PET images. Nineteen transgenic mice (12 with AD, 7 with controls) were used for this study. We observed an increase in ${\beta}$-Amyloid deposition ($A{\beta}$) in brain tissue and [F-18] FBB amyloid PET imaging in the AD group. The [F-18] FBB data showed a mildly negative trend with cognitive function. Pathological findings were negatively correlated with cognitive functions. These finding suggests that amyloid beta deposition can be well-monitored with [F-18] FBB PET and a decline in cognitive function is related to the increase in amyloid plaque burden.

• Current Optics and Photonics
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• 제6권1호
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• pp.92-103
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• 2022

The development of midinfrared (mid-IR) quantum cascade lasers (QCLs) has enabled rapid high-contrast measurement of the mid-IR spectra of biological tissues. Several studies have compared the differences between the mid-IR spectra of colon cancer and noncancerous colon tissues. Most mid-IR spectrum classification studies have been proposed as machine-learning-based algorithms, but this results in deviations depending on the initial data and threshold values. We aim to develop a process for classifying colon cancer and noncancerous colon tissues through a deep-learning-based convolutional-neural-network (CNN) model. First, we image the midinfrared spectrum for the CNN model, an image-based deep-learning (DL) algorithm. Then, it is trained with the CNN algorithm and the classification ratio is evaluated using the test data. When the tissue microarray (TMA) and routine pathological slide are tested, the ML-based support-vector-machine (SVM) model produces biased results, whereas we confirm that the CNN model classifies colon cancer and noncancerous colon tissues. These results demonstrate that the CNN model using midinfrared-spectrum images is effective at classifying colon cancer tissue and noncancerous colon tissue, and not only submillimeter-sized TMA but also routine colon cancer tissue samples a few tens of millimeters in size.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2006년도 하계종합학술대회
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• pp.391-392
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• 2006

In x-ray imaging system, twokinds of noises are involved. First, the charge generated from the radiation interaction with the detector during exposure is modeled by Poisson process. Second, the signal is then added by readout electronics noise, which is modeled by Gaussian distribution. In this paper, we applied Wiener filter and Wavelet to remove noise from medical X-ray image, the result shows that wavelet yield better segmentation results than the wiener filter.

• 전기학회논문지
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• 제66권1호
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• pp.107-113
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• 2017

Unlike regular images, there is no ground truth for bio surface images. Result of biosurface imaging is not only significantly affected by the environment and the condition of the bio surface, it requires more detailed expression than regular images. Therefore, unlike algorithms tested on regular images, studies on bio surface images requires a highly precise optimization process. We aim to optimize the graph cut algorithm, known to be the most outstanding among the stereo visions, by considering baseline, lambda, and disparity range. Optimal results were in the range of 1~10 for lambda. The disparity ranged from -30 to -50, indicating an optimal value in a slightly higher range. Furthermore, we verified the tested optimization data using SIFT.

• IEIE Transactions on Smart Processing and Computing
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• 제4권5호
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• pp.311-317
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• 2015

The aim of this study is to develop a 3D registration algorithm for positron emission tomography/computed tomography (PET/CT) and magnetic resonance (MR) images acquired from independent PET/CT and MR imaging systems. Combined PET/CT images provide anatomic and functional information, and MR images have high resolution for soft tissue. With the registration technique, the strengths of each modality image can be combined to achieve higher performance in diagnosis and radiotherapy planning. The proposed method consists of two stages: normalized mutual information (NMI)-based global matching and independent component analysis (ICA)-based refinement. In global matching, the field of view of the CT and MR images are adjusted to the same size in the preprocessing step. Then, the target image is geometrically transformed, and the similarities between the two images are measured with NMI. The optimization step updates the transformation parameters to efficiently find the best matched parameter set. In the refinement stage, ICA planes from the windowed image slices are extracted and the similarity between the images is measured to determine the transformation parameters of the control points. B-spline. based freeform deformation is performed for the geometric transformation. The results show good agreement between PET/CT and MR images.

• Bulletin of the Korean Chemical Society
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• 제31권8호
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• pp.2371-2374
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• 2010