• Title/Summary/Keyword: NIR detection

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Synthesis of dimeric fluorescent TSPO ligand for detection of glioma

  • Tien Tan Bui;Hee-Kwon Kim
    • Journal of Radiopharmaceuticals and Molecular Probes
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    • v.7 no.1
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    • pp.56-65
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    • 2021
  • TSPO, an 18-kDa translocator protein, is a peripheral-type benzodiazepine receptor that has been associated to a variety of biological activities such as apoptosis, steroidogenesis, and cell proliferation. Because TSPO overexpression has been found in various forms of cancer, it has recently become one of the most appealing biological targets for cancer therapies and detection. In order to create new optical imaging agents for improved diagnostics, we synthesized a novel dimeric fluorescent TSPO ligand based on PRB28 structure and SCy5.5. Following the preparation of the novel TSPO ligand, in vivo and ex vivo imaging tests were performed to examine the tumor uptake characteristics of the fluorescent TSPO ligand in a glioma animal model, and it was found that novel TSPO ligand was accumulated in glioma. These results suggested that novel dimeric fluorescent TSPO ligand will be applied to detect glioma.

Gaze Detection by Wearable Eye-Tracking and NIR LED-Based Head-Tracking Device Based on SVR

  • Cho, Chul Woo;Lee, Ji Woo;Shin, Kwang Yong;Lee, Eui Chul;Park, Kang Ryoung;Lee, Heekyung;Cha, Jihun
    • ETRI Journal
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    • v.34 no.4
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    • pp.542-552
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    • 2012
  • In this paper, a gaze estimation method is proposed for use with a large-sized display at a distance. Our research has the following four novelties: this is the first study on gaze-tracking for large-sized displays and large Z (viewing) distances; our gaze-tracking accuracy is not affected by head movements since the proposed method tracks the head by using a near infrared camera and an infrared light-emitting diode; the threshold for local binarization of the pupil area is adaptively determined by using a p-tile method based on circular edge detection irrespective of the eyelid or eyelash shadows; and accurate gaze position is calculated by using two support vector regressions without complicated calibrations for the camera, display, and user's eyes, in which the gaze positions and head movements are used as feature values. The root mean square error of gaze detection is calculated as $0.79^{\circ}$ for a 30-inch screen.

Assessment of the Completeness of Lymph Node Dissection Using Near-infrared Imaging with Indocyanine Green in Laparoscopic Gastrectomy for Gastric Cancer

  • Kim, Tae-Han;Kong, Seong-Ho;Park, Ji-Ho;Son, Yong-Gil;Huh, Yeon-Ju;Suh, Yun-Suhk;Lee, Hyuk-Joon;Yang, Han-Kwang
    • Journal of Gastric Cancer
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    • v.18 no.2
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    • pp.161-171
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    • 2018
  • Purpose: This study assessed the feasibility of near-infrared (NIR) imaging with indocyanine green (ICG) in investigating the completeness of laparoscopic lymph node (LN) dissection for gastric cancer. Materials and Methods: Patients scheduled for laparoscopic gastrectomy for treating gastric cancer were enrolled in the study. After intraoperative submucosal ICG injection (0.05 mg/mL), LN dissection was performed under conventional laparoscopic light. After dissection, the LN stations of interest were examined under the NIR mode to locate any extra ICG-stained (E) tissues, which were excised and sent for pathologic confirmation. This technique was tested in 2 steps: infra-pyloric LN dissection (step 1) and review of all stations after proper radical node dissection (step 2). Results: In step 1, 15 patients who underwent laparoscopic pylorus-preserving gastrectomy (LPPG) and 15 patients who underwent laparoscopic distal gastrectomy (LDG) were examined. Seven and 2 E-tissues were obtained during LPPG and LDG, respectively. From the retrieved E-tissues, 1 and 0 tissue obtained during LPPG and LDG, respectively, was confirmed as LN. In step 2, 20 patients were enrolled (13 D1+ dissection and 7 D2 dissection). Six E-tissues were retrieved from 5 patients, and 1 tissue was confirmed as LN in the pathologic review. Overall, 15 E-tissues were detected and removed, and 2 tissues were confirmed as LNs in the pathologic review. Both nodes were from LN station #6, with 1 case each in the LDG and LPPG groups. Conclusions: NIR imaging may provide additional node detection during laparoscopic LN dissection for gastric cancer, especially in the infra-pyloric area.

A Study on the Implementation and Development of Image Processing Algorithms for Vibes Detection Equipment (정맥 검출 장비 구현 및 영상처리 알고리즘 개발에 대한 연구)

  • Jin-Hyoung, Jeong;Jae-Hyun, Jo;Jee-Hun, Jang;Sang-Sik, Lee
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.15 no.6
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    • pp.463-470
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    • 2022
  • Intravenous injection is widely used for patient treatment, including injection drugs, fluids, parenteral nutrition, and blood products, and is the most frequently performed invasive treatment for inpatients, including blood collection, peripheral catheter insertion, and other IV therapy, and more than 1 billion cases per year. Intravenous injection is one of the difficult procedures performed only by experienced nurses who have been trained in intravenous injection, and failure can lead to thrombosis and hematoma or nerve damage to the vein. Nurses who frequently perform intravenous injections may also make mistakes because it is not easy to detect veins due to factors such as obesity, skin color, and age. Accordingly, studies on auxiliary equipment capable of visualizing the venous structure of the back of the hand or arm have been published to reduce mistakes during intravenous injection. This paper is about the development of venous detection equipment that visualizes venous structure during intravenous injection, and the optimal combination was selected by comparing the brightness of acquired images according to the combination of near-infrared (NIR) LED and Filter with different wavelength bands. In addition, an image processing algorithm was derived to threshehold and making blood vessel part to green through grayscale conversion, histogram equilzation, and sharpening filters for clarity of vein images obtained through the implemented venous detection experimental module.

MEAT SPECIATION USING A HIERARCHICAL APPROACH AND LOGISTIC REGRESSION

  • Arnalds, Thosteinn;Fearn, Tom;Downey, Gerard
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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    • 2001.06a
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    • pp.1245-1245
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    • 2001
  • Food adulteration is a serious consumer fraud and a matter of concern to food processors and regulatory agencies. A range of analytical methods have been investigated to facilitate the detection of adulterated or mis-labelled foods & food ingredients but most of these require sophisticated equipment, highly-qualified staff and are time-consuming. Regulatory authorities and the food industry require a screening technique which will facilitate fast and relatively inexpensive monitoring of food products with a high level of accuracy. Near infrared spectroscopy has been investigated for its potential in a number of authenticity issues including meat speciation (McElhinney, Downey & Fearn (1999) JNIRS, 7(3), 145-154; Downey, McElhinney & Fearn (2000). Appl. Spectrosc. 54(6), 894-899). This report describes further analysis of these spectral sets using a hierarchical approach and binary decisions solved using logistic regression. The sample set comprised 230 homogenized meat samples i. e. chicken (55), turkey (54), pork (55), beef (32) and lamb (34) purchased locally as whole cuts of meat over a 10-12 week period. NIR reflectance spectra were recorded over the wavelength range 400-2498nm at 2nm intervals on a NIR Systems 6500 scanning monochromator. The problem was defined as a series of binary decisions i. e. is the meat red or white\ulcorner is the red meat beef or lamb\ulcorner, is the white meat pork or poultry\ulcorner etc. Each of these decisions was made using an individual binary logistic model based on scores derived from principal component or partial least squares (PLS1 and PLS2) analysis. The results obtained were equal to or better than previous reports using factorial discriminant analysis, K-nearest neighbours and PLS2 regression. This new approach using a combination of exploratory and logistic analyses also appears to have advantages of transparency and the use of inherent structure in the spectral data. Additionally, it allows for the use of different data transforms and multivariate regression techniques at each decision step.

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NEAR INFRARED REFLECTANCE SPECTROSCOPY AS A TOOL TO PREDICT QUALITATIVE AND QUANTITATIVE MEAT AND BONE MEAL PRESENCE IN COMPOUND FEEDS

  • Fernandez, Maria;Martinez, Adela;Modrono, Sagrario;De La Roza, Begona
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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    • 2001.06a
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    • pp.1269-1269
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    • 2001
  • The Bovine Spongiform Encephalopathy (BSE) is one of the more important problems that have affected the economy of european cattles and the Public Safety. Their transmission is mainly through digestive system, and the compound feeds made with animal proteins are one source of infection for healthy cows. Nowadays the official method for meat and bone meal (MBM) detection in compound feeds is a microscopy technique. However, this methodology is subjective, and that alter the fact to make one exhaustive quantitative analysis and one differentiation between mammalian and poultry bones. In addition, the separation of the differents fractions in a sample by density before the analysis, requires the use of organochlorates products as $CCl_4$, which produce serious damages in the atmosphere ozone content. NIR methodology is another possible way to confirm and identifying animal ingredients in compound feeds, Its capabilities for quantitative and qualitative analysis of foods and feeds has been enought demonstrated. The objective of this work was to use NIR as a tool to make an qualitative and quantitative analysis and a prediction of the meat and bone meal presence in compound feeds from North Spain cattle farms. Using a global population of compound feeds, on make three different groups depending of MBM percentage presence (0, 0-100, 100), to build and validate one calibration equation to determine MBM content and make one discriminant analysis between these three groups. The preliminary dates obtained with another differents samples of known composition showed promising results.

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MEAT SPECIATION USING A HIERARCHICAL APPROACH AND LOGISTIC REGRESSION

  • Arnalds, Thosteinn;Fearn, Tom;Downey, Gerard
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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    • 2001.06a
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    • pp.1152-1152
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    • 2001
  • Food adulteration is a serious consumer fraud and a matter of concern to food processors and regulatory agencies. A range of analytical methods have been investigated to facilitate the detection of adulterated or mis-labelled foods & food ingredients but most of these require sophisticated equipment, highly-qualified staff and are time-consuming. Regulatory authorities and the food industry require a screening technique which will facilitate fast and relatively inexpensive monitoring of food products with a high level of accuracy. Near infrared spectroscopy has been investigated for its potential in a number of authenticity issues including meat speciation (McElhinney, Downey & Fearn (1999) JNIRS, 7(3), 145 154; Downey, McElhinney & Fearn (2000). Appl. Spectrosc. 54(6), 894-899). This report describes further analysis of these spectral sets using a hierarchical approach and binary decisions solved using logistic regression. The sample set comprised 230 homogenized meat samples i. e. chicken (55), turkey (54), pork (55), beef (32) and lamb (34) purchased locally as whole cuts of meat over a 10-12 week period. NIR reflectance spectra were recorded over the wavelength range 400-2498nm at 2nm intervals on a NIR Systems 6500 scanning monochromator. The problem was defined as a series of binary decisions i. e. is the meat red or white\ulcorner is the red meat beef or lamb\ulcorner, is the white meat pork or poultry\ulcorner etc. Each of these decisions was made using an individual binary logistic model based on scores derived from principal component or partial least squares (PLS1 and PLS2) analysis. The results obtained were equal to or better than previous reports using factorial discriminant analysis, K-nearest neighbours and PLS2 regression. This new approach using a combination of exploratory and logistic analyses also appears to have advantages of transparency and the use of inherent structure in the spectral data. Additionally, it allows for the use of different data transforms and multivariate regression techniques at each decision step.

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Near-Infrared Spectroscopy and Modeling of Luminous Blue Variables

  • Kim, Hyun-Jeong;Koo, Bon-Chul;Park, Yong-Sun
    • The Bulletin of The Korean Astronomical Society
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    • v.36 no.2
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    • pp.152.1-152.1
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    • 2011
  • We report preliminary results of long-slit near-infrared (NIR) spectroscopy of Luminous Blue Variables (LBVs) with moderate resolution of R ~ 2400. We obtained Jshort (1.04-1.26 micron) and Ks (2.02-2.31 micron) band spectra of 4 LBVs and 3 LBV candidates in Southern hemisphere using IRIS2, infrared imager and spectrograph, mounted on the 4-m Anglo-Australian Telescope. All targets are fairly bright in NIR so that we can obtain high signal-to-noise ratio for clear line detection and modeling. They are also widely distributed in the HR diagram so that we can compare the spectral properties of LBVs in different temperature and luminosity ranges. Among them, we present the results of two well-known LBVs AG Car and HR Car. Their spectra show similar properties with hydrogen, He I, and metallic lines such as Fe II and Mg II, most of them in emission. We discuss, in particular, the He I 1.083 micron lines formed in stellar wind because these two LBVs show large variation in their He I line intensities, compared to previous studies. Since the He I 1.083 line is known to be anticorrelated with the photometric variation of LBVs, strong line intensities with P-Cygni profiles in both stars indicate that they are now near the visual minimum phase. We model the obtained spectra using non-LTE atmosphere code CMFGEN of Hillier (1998) to derive stellar parameters such as wind velocity and mass loss rate, and discuss the long-term variability of stellar parameters of these LBVs. deduced from our otometric solution.

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Optical sensing techniques for simultaneous detection of nanoparticles and microorganisms in water (수질내 초미립자와 미생물의 동시 검출을 위한 광학센서기술)

  • Sohn, Ok-Jae;Hyung, Gi-Woo;Kim, Byung-Seb;Rhee, Jong-Il
    • Journal of Sensor Science and Technology
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    • v.17 no.3
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    • pp.157-161
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    • 2008
  • An optical sensor was developed to detect nanoparticles, turbid materials and microorganisms in water simultaneously. Three different light sources like UV-LED, NIR-LED and laser diode have been employed to develop the optical sensor based on the scattering light and fluorescence light. The sensor system has high selectivity and sensitivity, that it can be used to monitor the quality of drinking water.

Vegetation Change Detection using Change Vector Analysis (CVA 변화탐지 기법을 이용한 식생 변화 탐지)

  • 김혜진;김선수;김용일
    • Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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    • 2004.03a
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    • pp.295-300
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    • 2004
  • 변화탐지를 위하여 기존에 사용하던 화소차 혹은 화소비 변화탐지 기법은 단밴드의 영상을 사용하므로 다중분광 자료를 활용하기 어렵고 변화지역의 유형을 추출하는데 적절하지 못하다는 단점이 있다. 후분류 변화탐지 기법은 다중분팡 영상의 활용이 가능하고 변화지역의 변화 유형을 파악할 수 있지만 변화탐지 성과가 분류 결과의 정확도에 의해 크게 영향을 받는다. 이에 반해 CVA(Change Vector Analysis) 변화탐지는 여러 밴드의 다중분광 영상을 이용하여 변화지역을 탐지할 뿐 아니라 피복 변화의 경향을 파악할 수 있어 보다 효율적인 기법으로 평가받고 있다. 기본적인 CVA 변화탐지는 일반적으로 다중분광 영상의 red 밴드와 infrared 밴드의 영상을 조합하여 변화탐지를 수행하여 식생 및 인공물의 변화를 탐지한다. 본 연구에서는 단순한 red/NIR 밴드간의 조합 외에 식생의 특성을 계수로 변환하는 PDA(Pattern Decomposition Analysis) 변환 및 Tasseled Cap 변환 결과를 이용한 CVA 변화탐지를 수행하고 각 결과의 정확도를 비교하여 보다 효율적인 식생 변화탐지 기법을 제안하고자 하였다.

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