• Title/Summary/Keyword: SPATIAL IMAGE

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Performance Prediction for Plenoptic Microscopy Under Numerical Aperture Unmatching Conditions (수치 구경 불일치 플렌옵틱 현미경 성능 예측 방안 연구)

  • Ha Neul Yeon;Chan Lee;Seok Gi Han;Jun Ho Lee
    • Korean Journal of Optics and Photonics
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    • v.35 no.1
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    • pp.9-17
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    • 2024
  • A plenoptic optical system for microscopy comprises an objective lens, tube lens, microlens array (MLA), and an image sensor. Numerical aperture (NA) matching between the tube lens and MLA is used for optimal performance. This paper extends performance predictions from NA matching to unmatching cases and introduces a computational technique for plenoptic configurations using optical analysis software. Validation by fabricating and experimenting with two sample systems at 10× and 20× magnifications resulted in predicted spatial resolutions of 12.5 ㎛ and 6.2 ㎛ and depth of field (DOF) values of 530 ㎛ and 88 ㎛, respectively. The simulation showed resolutions of 11.5 ㎛ and 5.8 ㎛, with DOF values of 510 ㎛ and 70 ㎛, while experiments confirmed predictions with resolutions of 11.1 ㎛ and 5.8 ㎛ and DOF values of 470 ㎛ and 70 ㎛. Both formula-based prediction and simulations yielded similar results to experiments that were suitable for system design. However, regarding DOF values, simulations were closer to experimental values in accuracy, recommending reliance on simulation-based predictions before fabrication.

Detection of video editing points using facial keypoints (얼굴 특징점을 활용한 영상 편집점 탐지)

  • Joshep Na;Jinho Kim;Jonghyuk Park
    • Journal of Intelligence and Information Systems
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    • v.29 no.4
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    • pp.15-30
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    • 2023
  • Recently, various services using artificial intelligence(AI) are emerging in the media field as well However, most of the video editing, which involves finding an editing point and attaching the video, is carried out in a passive manner, requiring a lot of time and human resources. Therefore, this study proposes a methodology that can detect the edit points of video according to whether person in video are spoken by using Video Swin Transformer. First, facial keypoints are detected through face alignment. To this end, the proposed structure first detects facial keypoints through face alignment. Through this process, the temporal and spatial changes of the face are reflected from the input video data. And, through the Video Swin Transformer-based model proposed in this study, the behavior of the person in the video is classified. Specifically, after combining the feature map generated through Video Swin Transformer from video data and the facial keypoints detected through Face Alignment, utterance is classified through convolution layers. In conclusion, the performance of the image editing point detection model using facial keypoints proposed in this paper improved from 87.46% to 89.17% compared to the model without facial keypoints.

A Conjoint Analysis on the Preference Analysis of the Han River Skyline Focus on the Apgujeong Apartment District in the Han River Embankments, Seoul (컨조인트 분석(Conjoint analysis)을 이용한 한강 변 스카이라인 형태 선호도 분석 연구 - 한강 변 압구정 아파트지구를 중심으로 -)

  • Kang, Song-Hee;Jang, Chang-Hee;Lee, Jae-Seung
    • Journal of Cadastre & Land InformatiX
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    • v.53 no.2
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    • pp.79-92
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    • 2023
  • With a growing interest in the Han River Skyline, which greatly influences Seoul's image, careful consideration of the skyline form has become crucial in the redevelopment plans for apartment complexes along the Han River. The Seoul Metropolitan City government has lifted the height limitations for apartments along the Hang River to cultivate a vibrant skyline. However, traditional skyline analysis often overlooks specific attributes, limiting the provision of precise guidelines for Seoul's unique skyline plans. Despite advancements in Digital Twin technology, only some tools effectively manage urban skylines with preferred shapes. Hence, this study aims to make a substantial contribution to the advancement of a Digital Twin 3D modeling program capable of effectively managing urban skylines. This is achieved through the utilisation of Conjoint Analysis, which assesses the importance of each attribute in determining the preferred skyline shape. Focusing on Apgujeong apartment complexes along the Han River currently undergoing redevelopment or planned for redevelopment, the study analyses the preferred skyline shape to propose standards for the Digital Twin 3D modeling program development. It also suggests that Conjoint Analysis can be beneficial in this process.

Detecting high-resolution usage status of individual parcel of land using object detecting deep learning technique (객체 탐지 딥러닝 기법을 활용한 필지별 조사 방안 연구)

  • Jeon, Jeong-Bae
    • Journal of Cadastre & Land InformatiX
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    • v.54 no.1
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    • pp.19-32
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    • 2024
  • This study examined the feasibility of image-based surveys by detecting objects in facilities and agricultural land using the YOLO algorithm based on drone images and comparing them with the land category by law. As a result of detecting objects through the YOLO algorithm, buildings showed a performance of detecting objects corresponding to 96.3% of the buildings provided in the existing digital map. In addition, the YOLO algorithm developed in this study detected 136 additional buildings that were not located in the digital map. Plastic greenhouses detected a total of 297 objects, but the detection rate was low for some plastic greenhouses for fruit trees. Also, agricultural land had the lowest detection rate. This result is because agricultural land has a larger area and irregular shape than buildings, so the accuracy is lower than buildings due to the inconsistency of training data. Therefore, segmentation detection, rather than box-shaped detection, is likely to be more effective for agricultural fields. Comparing the detected objects with the land category by law, it was analyzed that some buildings exist in agricultural and forest areas where it is difficult to locate buildings. It seems that it is necessary to link with administrative information to understand that these buildings are used illegally. Therefore, at the current level, it is possible to objectively determine the existence of buildings in fields where it is difficult to locate buildings.

Susceptibility-Weighted Imaging as a Distinctive Imaging Technique for Providing Complementary Information for Precise Diagnosis of Neurologic Disorder (신경계 질환에 관한 정확한 진단을 위해 다양한 보완 정보를 제공하는 독특한 영상 기법으로서의 자기화율 강조 영상)

  • Byeong-Uk Jeon;In Kyu Yu;Tae Kun Kim;Ha Youn Kim;Seungbae Hwang
    • Journal of the Korean Society of Radiology
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    • v.82 no.1
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    • pp.99-115
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    • 2021
  • Various sequences have been developed for MRI to aid in the radiologic diagnosis. Among the various MR sequences, susceptibility-weighted imaging (SWI) is a high-spatial-resolution, three-dimensional gradient-echo MR sequence, which is very sensitive in detecting deoxyhemoglobin, ferritin, hemosiderin, and bone minerals through local magnetic field distortion. In this regard, SWI has been used for the diagnosis and treatment of various neurologic disorders, and the improved image quality has enabled to acquire more useful information for radiologists. Here, we explain the principle of various signals on SWI arising in neurological disorders and provide a retrospective review of many cases of clinically or pathologically proven disease or components with distinctive imaging features of various neurological diseases. Additionally, we outline a short and condensed overview of principles of SWI in relation to neurological disorders and describe various cases with characteristic imaging features on SWI. There are many different types diseases involving the brain parenchyma, and they have distinct SWI features. SWI is an effective imaging tool that provides complementary information for the diagnosis of various diseases.

Development of Inquiry Activity Materials for Visualizing Typhoon Track using GK-2A Satellite Images (천리안 위성 2A호 영상을 활용한 태풍 경로 시각화 탐구활동 수업자료 개발)

  • Chae-Young Lim;Kyung-Ae Park
    • Journal of the Korean earth science society
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    • v.45 no.1
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    • pp.48-71
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    • 2024
  • Typhoons are representative oceanic and atmospheric phenomena that cause interactions within the Earth's system with diverse influences. In recent decades, the typhoons have tended to strengthen due to rapidly changing climate. The 2022 revised science curriculum emphasizes the importance of teaching-learning activities using advanced science and technology to cultivate digital literacy as a citizen of the future society. Therefore, it is necessary to solve the temporal and spatial limitations of textbook illustrations and to develop effective instructional materials using global-scale big data covered in the field of earth science. In this study, according to the procedure of the PDIE (Preparation, Development, Implementation, Evaluation) model, the inquiry activity data was developed to visualize the track of the typhoon using the image data of GK-2A. In the preparatory stage, the 2015 and 2022 revised curriculum and the contents of the inquiry activities of the current textbooks were analyzed. In the development stage, inquiry activities were organized into a series of processes that can collect, process, visualize, and analyze observational data, and a GUI (Graphic User Interface)-based visualization program that can derive results with a simple operation was created. In the implementation and evaluation stage, classes were conducted with students, and classes using code and GUI programs were conducted respectively to compare the characteristics of each activity and confirm its applicability in the school field. The class materials presented in this study enable exploratory activities using actual observation data without professional programming knowledge which is expected to contribute to students' understanding and digital literacy in the field of earth science.

Application of Geo-Segment Anything Model (SAM) Scheme to Water Body Segmentation: An Experiment Study Using CAS500-1 Images (수체 추출을 위한 Geo-SAM 기법의 응용: 국토위성영상 적용 실험)

  • Hayoung Lee;Kwangseob Kim;Kiwon Lee
    • Korean Journal of Remote Sensing
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    • v.40 no.4
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    • pp.343-350
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    • 2024
  • Since the release of Meta's Segment Anything Model (SAM), a large-scale vision transformer generation model with rapid image segmentation capabilities, several studies have been conducted to apply this technology in various fields. In this study, we aimed to investigate the applicability of SAM for water bodies detection and extraction using the QGIS Geo-SAM plugin, which enables the use of SAM with satellite imagery. The experimental data consisted of Compact Advanced Satellite 500 (CAS500)-1 images. The results obtained by applying SAM to these data were compared with manually digitized water objects, Open Street Map (OSM), and water body data from the National Geographic Information Institute (NGII)-based hydrological digital map. The mean Intersection over Union (mIoU) calculated for all features extracted using SAM and these three-comparison data were 0.7490, 0.5905, and 0.4921, respectively. For features commonly appeared or extracted in all datasets, the results were 0.9189, 0.8779, and 0.7715, respectively. Based on analysis of the spatial consistency between SAM results and other comparison data, SAM showed limitations in detecting small-scale or poorly defined streams but provided meaningful segmentation results for water body classification.

Investigation of the Signal Characteristics of a Small Gamma Camera System Using NaI(Tl)-Position Sensitive Photomultiplier Tube (NaI(Tl) 섬광결정과 위치민감형 광전자증배관을 이용한 소형 감마카메라의 신호 특성 고찰)

  • Choi, Yong;Kim, Jong-Ho;Kim, Joon-Young;Im, Ki-Chun;Kim, Sang-Eun;Choe, Yearn-Seong;Lee, Kyung-Han;Joo, Koan-Sik;Kim, Byung-Tae
    • The Korean Journal of Nuclear Medicine
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    • v.34 no.1
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    • pp.82-93
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    • 2000
  • Purpose: We characterized the signals obtained from the components of a small gamma camera using Nal(Tl)-position sensitive photomultiplier tube (PSPMT) and optimized the parameters employed in the modules of the system. Materials and Methods: The small gamma camera system consists of a Nal(Tl) crystal ($60{\times}60{\times}6mm^3$) coupled with a Hamamatsu R3941 PSPMT, a resister chain circuit, preamplifiers, nuclear instrument modules (NIMs), an analog to digital converter and a personal computer for control and display. The PSPMT was read out using a resistive charge division circuit which multiplexes the 34 cross wire anode channels into 4 signals (X+, X-, Y+, Y -). Those signals were individually amplified by four preamplifiers and then, shaped and amplified by amplifiers. The signals were discriminated and digitized via triggering signal and used to localize the position of an event by applying the Anger logic. The gamma camera control and image display was performed by a program implemented using a graphic software. Results: The characteristics of signal and the parameters employed in each module of the system were presented. The intrinsic sensitivity of the system was approximately $8{\times}10^3$ counts/sec/${\mu}Ci$. The intrinsic energy resolution of the system was 18% FWHM at 140 keV. The spatial resolution obtained using a line-slit mask and $^{99m}Tc$ point source were, respectively, 2.2 and 2.3 mm FWHM in X and Y directions. Breast phantom containing $2{\sim}7mm$ diameter spheres was successfully imaged with a parallel hole collimator. The image displayed accurate size and activity distribution over the imaging field of view Conclusion: We proposed a simple method for development of a small gamma camera and presented the characteristics of the signals from the system and the optimized parameters used in the modules of the small gamma camera.

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Evaluation of MR Based Respiratory Motion Correction Technique in Liver PET/MRI Study (Liver PET/MRI 검사 시 MR 기반 호흡 움직임 보정 방법의 유용성 평가)

  • Do, Yong Ho;Lee, Hong Jae;Kim, Jin Eui;Noh, Gyeong Woon
    • The Korean Journal of Nuclear Medicine Technology
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    • v.22 no.1
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    • pp.15-22
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    • 2018
  • Purpose Respiratory motion during PET/MRI acquisition may result in image blurring and error in measurement for volume and quantification of lesion. The aim of this study was to evaluate changes of quantitative accuracy, tumor size and image quality by applying MR based respiratory motion correction technique (MBRMCT) using integrated PET/MR scanner. Materials and Methods Data of 30 patients (aged $62.5{\pm}10.2y$) underwent $^{18}F-FDG$ liver PET/MR (Biograph mMR 3.0T, Siemens) study were collected. PET listmode data for 7 minutes was simultaneously acquired with maximum average gate (MAG), minimum time gate (MTG) and non gate (NG) T1 weighted MR images. Gated PET reconstruction was performed using mu-maps generated from MAG and MTG by setting 35% of efficiency window. Maximum SUV ($SUV_{max}$), peak SUV ($SUV_{peak}$), tumor size and full width at half maximum (FWHM) in the z-axis direction of MAG, MTG and NG PET images were evaluated. Results Compared to NG, mean $SUV_{max}$ and $SUV_{peak}$ were increased in MAG 13.15%(p<0.0001), 8.66%(p<0.0001), MTG 13.27%(p<0.0001), 8.80%(p<0.0001) and mean tumor size and FWHM were decreased in MAG 14.47%(p<0.0001), 15.49%(p=0.0004), MTG 14.89%(p<0.0001), 15.79%(p=0.0003) respectively. Mean $SUV_{max}$ and $SUV_{peak}$ of MTG were increased by 0.07%(p=0.8802), 0.13%(p=0.7766). Mean tumor size and FWHM of MTG were decreased by 0.49%(p=0.2786), 0.36%(p=0.2488) compared to MAG. There was no statistically significant difference between MAG and MTG which increase total scan time for about 7 and 2 minutes. Conclusion SUV, accuracy of tumor size and spatial resolution were improved in both of MAG and MTG by applying MBRMCT without installing additional hardware in liver PET/MR study. More accurate information can be provided with the increase of 2 minutes scan time if applying MTG of MBRMCT to various abdominal PET/MR studies affected by respiratory motion.

Development of an Automatic 3D Coregistration Technique of Brain PET and MR Images (뇌 PET과 MR 영상의 자동화된 3차원적 합성기법 개발)

  • Lee, Jae-Sung;Kwark, Cheol-Eun;Lee, Dong-Soo;Chung, June-Key;Lee, Myung-Chul;Park, Kwang-Suk
    • The Korean Journal of Nuclear Medicine
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    • v.32 no.5
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    • pp.414-424
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    • 1998
  • Purpose: Cross-modality coregistration of positron emission tomography (PET) and magnetic resonance imaging (MR) could enhance the clinical information. In this study we propose a refined technique to improve the robustness of registration, and to implement more realistic visualization of the coregistered images. Materials and Methods: Using the sinogram of PET emission scan, we extracted the robust head boundary and used boundary-enhanced PET to coregister PET with MR. The pixels having 10% of maximum pixel value were considered as the boundary of sinogram. Boundary pixel values were exchanged with maximum value of sinogram. One hundred eighty boundary points were extracted at intervals of about 2 degree using simple threshold method from each slice of MR images. Best affined transformation between the two point sets was performed using least square fitting which should minimize the sum of Euclidean distance between the point sets. We reduced calculation time using pre-defined distance map. Finally we developed an automatic coregistration program using this boundary detection and surface matching technique. We designed a new weighted normalization technique to display the coregistered PET and MR images simultaneously. Results: Using our newly developed method, robust extraction of head boundary was possible and spatial registration was successfully performed. Mean displacement error was less than 2.0 mm. In visualization of coregistered images using weighted normalization method, structures shown in MR image could be realistically represented. Conclusion: Our refined technique could practically enhance the performance of automated three dimensional coregistration.

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