• Current Optics and Photonics
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• 제7권6호
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• pp.655-664
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• 2023

Ghost imaging (GI) technology is developing rapidly, but there are inevitably some limitations such as the influence of atmospheric turbulence. In this paper, we study a ghost imaging system in atmospheric turbulence and use a gamma-gamma (GG) model to simulate the medium to strong range of turbulence distribution. With a compressed sensing (CS) algorithm and generative adversarial network (GAN), the image can be restored well. We analyze the performance of correlation imaging, the influence of atmospheric turbulence and the restoration algorithm's effects. The restored image's peak signal-to-noise ratio (PSNR) and structural similarity index map (SSIM) increased to 21.9 dB and 0.67 dB, respectively. This proves that deep learning (DL) methods can restore a distorted image well, and it has specific significance for computational imaging in noisy and fuzzy environments.

• Nuclear Engineering and Technology
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• 제54권6호
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• pp.2204-2212
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• 2022

Recently, the demand for alpha imaging detectors for quantifying the distributions of alpha particles has increased in various fields. This study aims to reconstruct a high-resolution image from an alpha imaging detector by applying a super-spatial resolution method combined with the maximum-likelihood expectation maximization (MLEM) algorithm. To perform the super-spatial resolution method, several images are acquired while slightly moving the detector to predefined positions. Then, a forward model for imaging is established by the system matrix containing the mechanical shifts, subsampling, and measured point-spread function of the imaging system. Using the measured images and system matrix, the MLEM algorithm is implemented, which converges towards a high-resolution image. We evaluated the performance of the proposed method through the Monte Carlo simulations and phantom experiments. The results showed that the super-spatial resolution method was successfully applied to the alpha imaging detector. The spatial resolution of the resultant image was improved by approximately 12% using four images. Overall, the study's outcomes demonstrate the feasibility of the super-spatial resolution method for the alpha imaging detector. Possible applications of the proposed method include high-resolution imaging for alpha particles of in vitro sliced tissue and pre-clinical biologic assessments for targeted alpha therapy.

• Medical Lasers
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• 제10권3호
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• pp.123-131
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• 2021

Optical imaging modalities with properties of real-time, non-invasive, in vivo, and high resolution for image-guided surgery have been widely studied. In this review, we introduce two optical imaging systems, that could be the core of image-guided surgery and introduce the system configuration, implementation, and operation methods. First, we introduce the optical coherence tomography (OCT) system implemented by our research group. This system is implemented based on a swept-source, and the system has an axial resolution of 11 ㎛ and a lateral resolution of 22 ㎛. Second, we introduce a fluorescence imaging system. The fluorescence imaging system was implemented based on the absorption and fluorescence wavelength of indocyanine green (ICG), with a light-emitting diode (LED) light source. To confirm the performance of the two imaging systems, human malignant melanoma cells were injected into BALB/c nude mice to create a xenograft model and using this, OCT images of cancer and pathological slide images were compared. In addition, in a mouse model, an intravenous injection of indocyanine green was used with a fluorescence imaging system to detect real-time images moving along blood vessels and to detect sentinel lymph nodes, which could be very important for cancer staging. Finally, polarization-sensitive OCT to find the boundaries of cancer in real-time and real-time image-guided surgery using a developed contrast agent and fluorescence imaging system were introduced.

• 한국의학물리학회지:의학물리
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• 제20권2호
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• pp.51-61
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• 2009

컴프턴 카메라는 컴프턴 산란현상의 기하학적 해석을 통해 감마선원의 3차원적 위치분포를 고정된 위치에서 찾아내는 신개념의 감마선 영상장치이다. 기존의 감마선 영상장치에서는 필수적으로 사용되는 기계적 집속기를 사용하지 않기 때문에 높은 영상 감도를 제공할 수 있으며, 다중 추적자 기능을 제공한다는 장점이 있어 차세대 감마선 영상장치로서 주목을 받고 있다. 본 연구에서는 Geant4 몬테칼로 전산모사 툴키트를 이용하여 사용자 친화형의 컴프턴 카메라 시뮬레이터를 개발하였다. 시뮬레이터의 정확성을 검증하기 위하여 한양대학교에서 개발 중인 이중 산란형 컴프턴 카메라의 실험 결과와 비교하였다. 영상 해상도의 경우 선원의 에너지가 높아짐에 따라 해상도가 향상되는 동일한 경향을 보였으나, 시뮬레이터 결과에서 약 1 mm 정도 우수하게 평가되었다. 영상 감도의 경우 실험에서 2~3배 정도 높게 평가되었다. 이러한 결과들은 우연 동시반응에 기인한 것으로, 실험에서 획득한 유효반응들은 전산모사와는 달리 우연한 동시계수에의한 데이터가 상당수 포함되어 있기 때문에 영상 해상도는 상대적으로 저조하고, 영상 감도는 높게 나타난 것으로 판단된다. 개발된 시뮬레이터를 이용하여 새로운 구조의 컴프턴 카메라에 대한 성능을 평가하였다. 단일 산란형 컴프턴 카메라의 경우 산란부를 다층 구조로 개발할 때 4대의 산란부 검출기를 사용하는 것이 최상의 성능을 보이는 것으로 평가되었고, 그 이상 사용할 경우 성능이 오히려 저하됨을 확인하였다.

• 비파괴검사학회지
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• 제20권6호
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• pp.521-537
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• 2000

초음파 영상은 의료진단을 위한 영상기기 중 가장 널리 쓰이고 있는 방법으로 전자공학에 있어서 DSP 및 VLSI 분야의 기술발전에 힘입어 보다 효율적이고 복잡한 기법들의 적용이 가능하여져 90년대에 이르러 시스템의 성능이 매우 빠르게 발달되었다. 본 논문은 의료진단용 초음파 영상장치에서 사용되는 주요 디지털 신호처리 기법과 시스템 구현 기술에 대하여 기술하였다. 구체적으로는 일반적인 초음파 영상장치의 구조 및 신호처리 기법을 소개하고, 90년대에 개발된 디지털 초음파 영상장치의 기술적인 내용을 그 기술 동향과 전망과 함께 다루었다. 특히 초음파 영상의 화질을 결정하는 가장 중요한 요소인 해상도를 증대하기 위한 모든 초음파 집속 기법을 표현할 수 있는 통합 합성 구경 모형을 제시하고, 이론적인 해석을 통하여 초음파 영상을 위한 어레이 신호처리 기법들을 구분하고 각 방법들에 대한 특성을 조사하였나. 본 논문에서 소개된 신호처리 기법들은 초음파를 이용한 비파괴 검사 분야에 유용하게 적용될 수 있는 것 들이다.

• Current Optics and Photonics
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• 제2권6호
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• pp.568-575
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• 2018

Various techniques to measure the three-dimensional (3D) surface profile of a 3D micro- or nanostructure have been proposed. However, it is difficult to apply such techniques directly to industrial uses because most of them are relatively slow, unreliable, and expensive. The HiLo optical imaging technique, which was recently introduced in the field of fluorescence imaging, is a promising wide-field imaging technique capable of high-speed imaging with a simple optical configuration. It has not been used in measuring a 3D surface profile although confocal microscopy originally developed for fluorescence imaging has been adapted to the field of 3D optical measurement for a long time. In this paper, to the best of our knowledge, the HiLo optical imaging technique for measuring a 3D surface profile is proposed for the first time. Its optical configuration and algorithm for a precisely detecting surface position are designed, optimized, and implemented. Optical performance for several 3D microscale structures is evaluated, and it is confirmed that the capability of measuring a 3D surface profile with HiLo optical imaging technique is comparable to that with confocal microscopy.

• Investigative Magnetic Resonance Imaging
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• 제25권4호
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• pp.300-312
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• 2021

Compressed sensing (CS) has been investigated in magnetic resonance (MR) parametric mapping to reduce scan time. However, the relatively long reconstruction time restricts its widespread applications in the clinic. Recently, deep learning-based methods have shown great potential in accelerating reconstruction time and improving imaging quality in fast MR imaging, although their adaptation to parametric mapping is still in an early stage. In this paper, we proposed a novel deep learning-based framework DEMO for fast and robust MR parametric mapping. Different from current deep learning-based methods, DEMO trains the network in an unsupervised way, which is more practical given that it is difficult to acquire large fully sampled training data of parametric-weighted images. Specifically, a CS-based loss function is used in DEMO to avoid the necessity of using fully sampled k-space data as the label, thus making it an unsupervised learning approach. DEMO reconstructs parametric weighted images and generates a parametric map simultaneously by unrolling an interaction approach in conventional fast MR parametric mapping, which enables multi-tasking learning. Experimental results showed promising performance of the proposed DEMO framework in quantitative MR T1ρ mapping.

• Investigative Magnetic Resonance Imaging
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• 제23권3호
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• pp.241-250
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• 2019

Purpose: The purpose of this study was to determine the relation between quantitative magnetic resonance imaging biomarkers, and clinical performances in chronic phase of carbon monoxide intoxication. Materials and Methods: Eighteen magnetic resonance scans and cognitive evaluations were performed, on patients with carbon monoxide intoxication in chronic phase. Apparent diffusion coefficient (ADC) ratios of affected versus unaffected centrum semiovale, and corpus callosum were obtained. Signal intensity (SI) ratios between affected centrum semiovale, and normal pons in T2-FLAIR (fluid-attenuated inversion recovery) images were obtained. The Mini-Mental State Exam, and clinical outcome scores were assessed. Correlation coefficients were calculated, between MRI and clinical markers. Patients were further classified into poor-outcome and good-outcome groups based on clinical performance, and imaging parameters were compared. T2-SI ratio of centrum semiovale was compared, with that of 18 sex-matched and age-matched controls. Results: T2-SI ratio of centrum semiovale was significantly higher in the poor-outcome group, than that in the good-outcome group and was strongly inversely correlated, with results from the Mini-Mental State Exam. ADC ratios of centrum semiovale were significantly lower in the poor outcome group than in the good outcome group, and were moderately correlated with the Mini-Mental State Exam score. Conclusion: A higher T2-SI and a lower ratio of ADC values in the centrum semiovale, may indicate presence of more severe white matter injury and clinical impairment. T2-SI ratio and ADC values in the centrum semiovale, are useful quantitative imaging biomarkers for correlation with clinical performance in individuals with carbon monoxide intoxication.

• International Journal of Control, Automation, and Systems
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• 제6권6호
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• pp.828-835
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• 2008

We present a novel method for eye location by means of a two-level classifier scheme. Locating the eye by machine-inspection of an image or video is an important problem for Computer Vision and is of particular value to applications in biomedical imaging. Our method aims to overcome the significant challenge of an eye-location that is able to maintain high accuracy by disregarding highly variable changes in the environment. A first level of computational analysis processes this image context. This is followed by object detection by means of a two-class discrimination classifier(second algorithmic level).We have tested our eye location system using FERET and BioID database. We compare the performance of two-level classifier with that of non-level classifier, and found it's better performance.

• 제어로봇시스템학회논문지
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• 제20권8호
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• pp.842-848
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• 2014

In this paper, an improved method RMBE (Resizable Model Based target size Estimator) is presented for SDIIR (Strap Down Imaging Infrared) seekers. At the target engaging scenario, the IIR target measurement is separated by various parts. In this case, target object changing is important to accurate target intercept. Therefore, we need robust target size estimator. Our proposed method resize estimated target size with MC-1 (Markov Chain I) for accurate target size estimation. The performance of proposed method is tested at IIR target tracking of target intercept scenario. The experiment results show that the proposed RMBE has improved performance than MBE.