• Title/Summary/Keyword: Separating image

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Detection of Smoking Behavior in Images Using Deep Learning Technology (딥러닝 기술을 이용한 영상에서 흡연행위 검출)

  • Dong Jun Kim;Yu Jin Choi;Kyung Min Park;Ji Hyun Park;Jae-Moon Lee;Kitae Hwang;In Hwan Jung
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.23 no.4
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    • pp.107-113
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    • 2023
  • This paper proposes a method for detecting smoking behavior in images using artificial intelligence technology. Since smoking is not a static phenomenon but an action, the object detection technology was combined with the posture estimation technology that can detect the action. A smoker detection learning model was developed to detect smokers in images, and the characteristics of smoking behaviors were applied to posture estimation technology to detect smoking behaviors in images. YOLOv8 was used for object detection, and OpenPose was used for posture estimation. In addition, when smokers and non-smokers are included in the image, a method of separating only people was applied. The proposed method was implemented using Google Colab NVIDEA Tesla T4 GPU in Python, and it was found that the smoking behavior was perfectly detected in the given video as a result of the test.

Deep Learning Algorithm Training and Performance Analysis for Corridor Monitoring (회랑 감시를 위한 딥러닝 알고리즘 학습 및 성능분석)

  • Woo-Jin Jung;Seok-Min Hong;Won-Hyuck Choi
    • Journal of Advanced Navigation Technology
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    • v.27 no.6
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    • pp.776-781
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    • 2023
  • K-UAM will be commercialized through maturity after 2035. Since the Urban Air Mobility (UAM) corridor will be used vertically separating the existing helicopter corridor, the corridor usage is expected to increase. Therefore, a system for monitoring corridors is also needed. In recent years, object detection algorithms have developed significantly. Object detection algorithms are largely divided into one-stage model and two-stage model. In real-time detection, the two-stage model is not suitable for being too slow. One-stage models also had problems with accuracy, but they have improved performance through version upgrades. Among them, YOLO-V5 improved small image object detection performance through Mosaic. Therefore, YOLO-V5 is the most suitable algorithm for systems that require real-time monitoring of wide corridors. Therefore, this paper trains YOLO-V5 and analyzes whether it is ultimately suitable for corridor monitoring.K-uam will be commercialized through maturity after 2035.

Contrast Enhancement Using a Density based Sub-histogram Equalization Technique (밀도기반의 분할된 히스토그램 평활화를 통한 대비 향상 기법)

  • Yoon, Hyun-Sup;Han, Young-Joon;Hahn, Hern-Soo
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.46 no.1
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    • pp.10-21
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    • 2009
  • In order to enhance the contrast in the regions where the pixels have similar intensities, this paper presents a new histogram equalization scheme. Conventional global equalization schemes over-equalizes those regions so that too bright or dark pixels are resulted and local equalization schemes produce unexpected discontinuities at the boundaries of the blocks. The proposed algorithm segments the original histogram into sub-histograms with reference to brightness level and equalizes each sub-histogram with the limited extents of equalization considering its mean and variance. The final image is determined as the weighted sum of the equalized images obtained by using the sub-histogram equalizations. By limiting the maximum and minimum ranges of equalization operations on individual sub-histograms, the over-equalization effect is eliminated. Also the result image does not miss feature information in low density histogram region since the remaining these area is applied separating equalization. This paper includes how to determine the segmentation points in the histogram. The proposed algorithm has been tested with more than 100 images having various contrast in the images and the results are compared to the conventional approaches to show its superiority.

Segmentation Method of Overlapped nuclei in FISH Image (FISH 세포영상에서의 군집세포 분할 기법)

  • Jeong, Mi-Ra;Ko, Byoung-Chul;Nam, Jae-Yeal
    • The KIPS Transactions:PartB
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    • v.16B no.2
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    • pp.131-140
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    • 2009
  • This paper presents a new algorithm to the segmentation of the FISH images. First, for segmentation of the cell nuclei from background, a threshold is estimated by using the gaussian mixture model and maximizing the likelihood function of gray value of cell images. After nuclei segmentation, overlapped nuclei and isolated nuclei need to be classified for exact nuclei analysis. For nuclei classification, this paper extracted the morphological features of the nuclei such as compactness, smoothness and moments from training data. Three probability density functions are generated from these features and they are applied to the proposed Bayesian networks as evidences. After nuclei classification, segmenting of overlapped nuclei into isolated nuclei is necessary. This paper first performs intensity gradient transform and watershed algorithm to segment overlapped nuclei. Then proposed stepwise merging strategy is applied to merge several fragments in major nucleus. The experimental results using FISH images show that our system can indeed improve segmentation performance compared to previous researches, since we performed nuclei classification before separating overlapped nuclei.

Material Discrimination Using X-Ray and Neutron

  • Jaehyun Lee;Jinhyung Park;Jae Yeon Park;Moonsik Chae;Jungho Mun;Jong Hyun Jung
    • Journal of Radiation Protection and Research
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    • v.48 no.4
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    • pp.167-174
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    • 2023
  • Background: A nondestructive test is commonly used to inspect the surface defects and internal structure of an object without any physical damage. X-rays generated from an electron accelerator or a tube are one of the methods used for nondestructive testing. The high penetration of X-rays through materials with low atomic numbers makes it difficult to discriminate between these materials using X-ray imaging. The interaction characteristics of neutrons with materials can supplement the limitations of X-ray imaging in material discrimination. Materials and Methods: The radiation image acquisition process for air-cargo security inspection equipment using X-rays and neutrons was simulated using a GEometry ANd Tracking (Geant4) simulation toolkit. Radiation images of phantoms composed of 13 materials were obtained, and the R-value, representing the attenuation ratio of neutrons and gamma rays in a material, was calculated from these images. Results and Discussion: The R-values were calculated from the simulated X-ray and neutron images for each phantom and compared with those obtained in the experiments. The R-values obtained from the experiments were higher than those obtained from the simulations. The difference can be due to the following two causes. The first reason is that there are various facilities or equipment in the experimental environment that scatter neutrons, unlike the simulation. The other is the difference in the neutron signal processing. In the simulation, the neutron signal is the sum of the number of neutrons entering the detector. However, in the experiment, the neutron signal was obtained by superimposing the intensities of the neutron signals. Neutron detectors also detect gamma rays, and the neutron signal cannot be clearly distinguished in the process of separating the two types of radiation. Despite these differences, the two results showed similar trends and the viability of using simulation-based radiation images, particularly in the field of security screening. With further research, the simulation-based radiation images can replace ones from experiments and be used in the related fields. Conclusion: The Korea Atomic Energy Research Institute has developed air-cargo security inspection equipment using neutrons and X-rays. Using this equipment, radiation images and R-values for various materials were obtained. The equipment was reconstructed, and the R-values were obtained for 13 materials using the Geant4 simulation toolkit. The R-values calculated by experiment and simulation show similar trends. Therefore, we confirmed the feasibility of using the simulation-based radiation image.

Research of Protocols for Optimization of Exposure Dose in Abdominopelvic CT - (복부-골반 CT검사 시 피폭선량 최적화에 관한 프로토콜 연구)

  • Hong, Dong-Hee
    • Journal of radiological science and technology
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    • v.40 no.2
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    • pp.245-251
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    • 2017
  • This study measured the exposure dose during abdominal-pelvic CT exam which occupies 70% of CT exam and tried to propose a protocol for optimized exposure dose in abdomen and pelvis without affecting the imagery interpretation. The study scanned abdomen-pelvis using the current clinical scan method, the 120 kVp, auto exposure control(AEC), as 1 phase. As for the newly proposed 2 phase scan method, the study divided into 1 phase abdomen exam and 2 phase pelvis exam and each conducted tube voltage 120 kVp, AEC for abdomen exam, and fixed tube current method in 120 kVp, 100, 150, 200, 250, 300, 350, 400 mA for pelvis exam. The exposure dose value was compared using $CTDI_{VOL}$, DLP value measured during scan, and average value of CT attenuation coefficient, noise, SNR from each scan image were obtained to evaluate the image. As for the result, scanning of 2 phase showed significant difference compared to 1 phase. In $CTDI_{VOL}$ value, the 2 phase showed 26% decrease in abdomen, 1.8~59.5% decrease in pelvis for 100~250 mA, 12.7%~30% increase in pelvis for 300~400 mA. Also, DLP value showed 53% decrease in abdomen and 41~81% decrease in pelvis when scanned by 2 phase compared to 1 phase, but it was not statistically significant. As for the SNR, when scanning 2 phase close to heart, scanning 1 phase close to pelvis, scanning and scanning 1 phase at upper and lower abdomen, it was higher when scanning 2 phase for 200~250 mA. Also, the CT number and noise was overall similar, but the noise was high close to pelvis. However, when scanning 2 phase for 250 mA close to pelvis, the noise value came out similar to 1 phase, and did not show statistically significant difference. It seems when separating pelvis to scan in 250 mA rather than 400 mA in 1 phase as before, it is expected to have reduced effect of exposure dose without difference in the quality of image. Thus, for patients who often get abdominal-pelvic CT exam, fertile women or children, this study proposes 2 phase exam for smaller exposure dose with same image quality.

(Image Analysis of Electrophoresis Gels by using Region Growing with Multiple Peaks) (다중 피크의 영역 성장 기법에 의한 전기영동 젤의 영상 분석)

  • 김영원;전병환
    • Journal of KIISE:Software and Applications
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    • v.30 no.5_6
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    • pp.444-453
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    • 2003
  • Recently, a great interest of bio-technology(BT) is concentrated and the image analysis technique for electrophoresis gels is highly requested to analyze genetic information or to look for some new bio-activation materials. For this purpose, the location and quantity of each band in a lane should be measured. In most of existing techniques, the approach of peak searching in a profile of a lane is used. But this peak is improper as the representative of a band, because its location does not correspond to that of the brightest pixel or the center of gravity. Also, it is improper to measure band quantity in most of these approaches because various enhancement processes are commonly applied to original images to extract peaks easily. In this paper, we adopt an approach to measure accumulated brightness as a band quantity in each band region, which Is extracted by not using any process of changing relative brightness, and the gravity center of the region is calculated as a band location. Actually, we first extract lanes with an entropy-based threshold calculated on a gel-image histogram. And then, three other methods are proposed and applied to extract bands. In the MER method, peaks and valleys are searched on a vertical search line by which each lane is bisected. And the minimum enclosing rectangle of each band is set between successive two valleys. On the other hand, in the RG-1 method, each band is extracted by using region growing with a peak as a seed, separating overlapped neighbor bands. In the RG-2 method, peaks and valleys are searched on two vertical lines by which each lane is trisected, and the left and right peaks nay be paired up if they seem to belong to the same band, and then each band region is grown up with a peak or both peaks if exist. To compare above three methods, we have measured the location and amount of bands. As a result, the average errors in band location of MER, RG-1, and RG-2 were 6%, 3%, and 1%, respectively, when the lane length is normalized to a unit value. And the average errors in band amount were 8%, 5%, and 2%, respectively, when the sum of band amount is normalized to a unit value. In conclusion, RG-2 was shown to be more reliable in the accuracy of measuring the location and amount of bands.

Deep Learning Approaches for Accurate Weed Area Assessment in Maize Fields (딥러닝 기반 옥수수 포장의 잡초 면적 평가)

  • Hyeok-jin Bak;Dongwon Kwon;Wan-Gyu Sang;Ho-young Ban;Sungyul Chang;Jae-Kyeong Baek;Yun-Ho Lee;Woo-jin Im;Myung-chul Seo;Jung-Il Cho
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.25 no.1
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    • pp.17-27
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    • 2023
  • Weeds are one of the factors that reduce crop yield through nutrient and photosynthetic competition. Quantification of weed density are an important part of making accurate decisions for precision weeding. In this study, we tried to quantify the density of weeds in images of maize fields taken by unmanned aerial vehicle (UAV). UAV image data collection took place in maize fields from May 17 to June 4, 2021, when maize was in its early growth stage. UAV images were labeled with pixels from maize and those without and the cropped to be used as the input data of the semantic segmentation network for the maize detection model. We trained a model to separate maize from background using the deep learning segmentation networks DeepLabV3+, U-Net, Linknet, and FPN. All four models showed pixel accuracy of 0.97, and the mIOU score was 0.76 and 0.74 in DeepLabV3+ and U-Net, higher than 0.69 for Linknet and FPN. Weed density was calculated as the difference between the green area classified as ExGR (Excess green-Excess red) and the maize area predicted by the model. Each image evaluated for weed density was recombined to quantify and visualize the distribution and density of weeds in a wide range of maize fields. We propose a method to quantify weed density for accurate weeding by effectively separating weeds, maize, and background from UAV images of maize fields.

Establishment of a Hepatocellular Carcinoma Cell Line Expressing Dual Reporter Genes: Sodium Iodide Symporter (NIS) and Enhanced Green Fluorescence Protein (EGFP) (나트륨 옥소 공동수송체 유전자와 녹색 형광 유전자의 이중 리포터 유전자를 발현하는 간암세포주 확립)

  • Kwak, Won-Jung;Koo, Bon-Chul;Kwon, Mo-Sun;Lee, Yong-Jin;Lee, Hwa-Young;Yoo, Jeong-Soo;Kim, Te-Oan;Chun, Kwon-Soo;Cheon, Gi-Jeong;Lee, Sang-Woo;Ahn, Byeong-Cheol;Lee, Jae-Tae
    • Nuclear Medicine and Molecular Imaging
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    • v.41 no.3
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    • pp.226-233
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    • 2007
  • Purpose: Dual reporter gene imaging has several advantages for more sophisticated molecular imaging studies such as gene therapy monitoring. Herein, we have constructed hepatoma cell line expressing dual reporter genes of sodium iodide symporter (NIS) and enhanced green fluorescence protein (EGFP), and the functionalities of the genes were evaluated in vivo by nuclear and optical imaging. Materials and Methods: A pRetro-PN vector was constructed after separating NIS gene from pcDNA-NIS. RSV-EGFP-WPRE fragment separated from pLNRGW was cloned into pRetro-PN vector. The final vector expressing dual reporter genes was named pRetro-PNRGW. A human hepatoma (HepG2) cells were transfected by the retrovirus containing NIS and EGFP gene (HepG2-NE). Expression of NIS gene was confirmed by RT-PCR, radioiodine uptake and efflux studies. Expression of EGFP was confirmed by RT-PCR and fluorescence microscope. The HepG2 and HepG2-NE cells were implanted in shoulder and hindlimb of nude mice, then fluorescence image, gamma camera image and I-124 microPET image were undertaken. Results: The HepG2-NE cell was successfully constructed. RT-PCR showed NIS and EGFP mRNA expression. About 50% of cells showed fluorescence. The iodine uptake of NIS-expressed cells was about 9 times higher than control. In efflux study, $T_{1/2}$ of HepG2-NE cells was 9 min. HepG2-NE xenograft showed high signal-to-background fluorescent spots and higher iodine-uptake compared to those of HepG2 xenograft. Conclusion: A hepatoma cell line expressing NIS and EGFP dual reporter genes was successfully constructed and could be used as a potential either by therapeutic gene or imaging reporter gene.

USABILITY EVALUATION OF PLANNING MRI ACQUISITION WHEN CT/MRI FUSION OF COMPUTERIZED TREATMENT PLAN (전산화 치료계획의 CT/MRI 영상 융합 시 PLANNING MRI영상 획득의 유용성 평가)

  • Park, Do-Geun;Choe, Byeong-Gi;Kim, Jin-Man;Lee, Dong-Hun;Song, Gi-Won;Park, Yeong-Hwan
    • The Journal of Korean Society for Radiation Therapy
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    • v.26 no.1
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    • pp.127-135
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    • 2014
  • Purpose : By taking advantage of each imaging modality, the use of fused CT/MRI image has increased in prostate cancer radiation therapy. However, fusion uncertainty may cause partial target miss or normal organ overdose. In order to complement such limitation, our hospital acquired MRI image (Planning MRI) by setting up patients with the same fixing tool and posture as CT simulation. This study aims to evaluate the usefulness of the Planning MRI through comparing and analyzing the diagnostic MRI image and Planning MRI image. Materials and Methods : This study targeted 10 patients who had been diagnosed with prostate cancer and prescribed nonhormone and definitive RT 70 Gy/28 fx from August 2011 to July 2013. Each patient had both CT and MRI simulations. The MRI images were acquired within one half hour after the CT simulation. The acquired CT/MRI images were fused primarily based on bony structure matching. This study measured the volume of prostate in the images of Planning MRI and diagnostic MRI. The diameters at the craniocaudal, anteroposterior and left-to-right directions from the center of prostate were measured in order to compare changes in the shape of prostate. Results : As a result of comparing the volume of prostate in the images of Planning MRI and diagnostic MRI, they were found to be $25.01cm^3$(range $15.84-34.75cm^3$) and $25.05cm^3$(range $15.28-35.88cm^3$) on average respectively. The diagnostic MRI had an increase of 0.12 % as compared with the Planning MRI. On the planning MRI, there was an increase in the volume by $7.46cm^3$(29 %) at the transition zone directions, and there was a decrease in the volume by $8.52cm^3$(34 %) in the peripheral zone direction. As a result of measuring the diameters at the craniocaudal, anteroposterior and left-to-right directions in the prostate, the Planning MRI was found to have on average 3.82cm, 2.38cm and 4.59cm respectively and the diagnostic MRI was found to have on average 3.37cm, 2.76cm and 4.51cm respectively. All three prostate diameters changed and the change was significant in the Planning MRI. On average, the anteroposterior prostate diameter decrease by 0.38cm(13 %). The mean right-to-left and craniocaudal diameter increased by 0.08cm(1.6 %) and 0.45cm(13 %), respectively. Conclusion : Based on the results of this study, it was found that the total volumes of prostate in the Planning MRI and the diagnostic MRI were not significantly different. However, there was a change in the shape and partial volume of prostate due to the insertion of prostate balloon tube to the rectum. Thus, if the Planning MRI images were used when conducting the fusion of CT/MRI images, it would be possible to include the target in the CTV without a loss as much as the increased volume in the transition zone. Also, it would be possible to reduce the radiation dose delivered to the rectum through separating more clearly the reduction of peripheral zone volume. Therefore, the author of this study believes that acquisition of Planning MRI image should be made to ensure target delineation and localization accuracy.