• Title/Summary/Keyword: Back-Projection

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Development of Image Reconstruction Algorithm for Chest Digital Tomosynthesis System (CDT) and Evaluation of Dose and Image Quality (흉부 디지털 단층영상합성 시스템의 영상 재구성 알고리즘 개발 및 선량과 화질 평가)

  • Kim, Min Kyoung;Kwak, Hyeng Ju;Kim, Jong Hun;Choe, Won-Ho;Ha, Yun Kyung;Lee, So Jung;Kim, Dae Ho;Lee, Yong-Gu;Lee, Youngjin
    • Journal of the Institute of Electronics and Information Engineers
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    • v.53 no.9
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    • pp.143-147
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    • 2016
  • Recently, digital tomosynthesis system (DTS) has been developed to reduce overlap using conventional X-ray and to overcome high patient dose problem using computed tomography (CT). The purpose of this study was to develop image reconstruction algorithm and to evaluate image characteristics and dose with chest digital tomosynthesis (CDT) system. Image reconstruction was used for filtered back-projection (FBP) methods and system geometry was constructed ${\pm}10^{\circ}$, ${\pm}15^{\circ}$, ${\pm}20^{\circ}$, and ${\pm}30^{\circ}$ angular range for acquiring phantom images. Image characteristics carried out root mean square error (RMSE) and signal difference-to-noise ratio (SDNR), and dose is evaluated effective dose with ${\pm}20^{\circ}$ angular range. According to the results, the phantom image with slice thickness filter has superb RMSE and SDNR, and effective dose was 0.166 mSv. In conclusion, we demonstrated usefulness of developed CDT image reconstruction algorithm and we constructed CDT basic output data with measuring effective dose.

Development of Unmatched System Model for Iterative Image Reconstruction for Pinhole Collimator of Imaging Systems in Nuclear Medicine (핀홀콜리메이터를 사용한 핵의학영상기기의 순환적 영상 재구성을 위한 비동일 시스템 모델 개발)

  • Bae, Jae-Keon;Bae, Seung-Bin;Lee, Ki-Sung;Kim, Yong-Kwon;Joung, Jin-Hun
    • Journal of radiological science and technology
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    • v.35 no.4
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    • pp.353-360
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    • 2012
  • Diverse designs of collimator have been applied to Single Photon Emission Computed Tomography (SPECT) according to the purpose of acquisition; thus, it is necessary to reflect geometric characteristic of each collimator for successive image reconstruction. This study carry out reconstruction algorithm for imaging system in nuclear medicine with pinhole collimator. Especially, we study to solve sampling problem which caused in the system model of pinhole collimator. System model for a maximum likelihood expectation maximization (MLEM) was developed based on the geometry of the collimator. The projector and back-projector were separately implemented based on the ray-driven and voxel-driven methods, respectively, to overcome sparse sampling problem. We perform phantom study for pinhole collimator by using geant4 application for tomographic emission(GATE) simulation tool. The reconstructed images show promising results. Designed iterative reconstruction algorithm with unmatched system model effective to remove sampling problem artefact. Proposed algorithm can be used not only for pinhole collimator but also for various collimator system of imaging system in nuclear medicine.

Soccer Game Analysis I : Extraction of Soccer Players' ground traces using Image Mosaic (축구 경기 분석 I : 영상 모자익을 통한 축구 선수의 운동장 궤적 추출)

  • Kim, Tae-One;Hong, Ki-Sang
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.36S no.1
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    • pp.51-59
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    • 1999
  • In this paper we propose the technique for tracking players and a ball and for obtaining players' ground traces using image mosaic in general soccer sequences. Here, general soccer sequences mean the case that there is no extreme zoom-in or zoom-out of TV camera. Obtaining player's ground traces requires that the following three main problems be solved. There main problems: (1) ground field extraction (2) player and ball tracking and team indentification (3) player positioning. The region of ground field is extracted on the basis of color information. Players are tracked by template matching and Kalman filtering. Occlusion reasoning between overlapped players in done by color histogram back-projection. To find the location of a player, a ground model is constructed and transformation between the input images and the field model is computed using four or more feature points. But, when feature points extracted are insufficient, image-based mosaic technique is applied. By this image-to-model transformation, the traces of players on the ground model can be determined. We tested our method on real TV soccer sequence and the experimental results are given.

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Effects of Advanced Modeled Iterative Reconstruction on Coronary Artery Calcium (CAC) Scores (ADMIRE가 관상동맥 칼슘(CAC) 점수에 미치는 영향)

  • Lee, Sang-Heon;Lee, Hyo-Young
    • Journal of the Korean Society of Radiology
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    • v.15 no.5
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    • pp.603-612
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    • 2021
  • The effect of Advanced Modeled Iterative Reconstruction (ADMIRE) on the coronary artery calcium (CAC) score of computed tomography was evaluated. Coronary artery calcium images (348 calcium, 6 groups, total of 2088 calcium) were acquired by 128-slice dual-source CT of 89 patients.Volume score and Agatston score were measured from images reconstructed with filtered back projection (FBP) and ADMIRE (1-5). The difference between FBP and ADMIRE Strength (1-5) was confirmed through the Kruskal-Wallis test, and the post-hoc analysis was performed using the Mann-Whitney U test based on FBP. Both volume score and Agatston score showed statistically significant differences between FBP and ADMIRE (1-5) (P=0.015, P=0.0.38). As a result of post hoc analysis, the volume score decreased to 9.5% in ADMIRE 4 (Z=-2.359, P=0.018) and 13.2% in ADMIRE 5 (Z=-3.113, P=0.002) based on FBP. Agatston score decreased to 10.4% in ADMIRE 4 (Z=-2.051, P=0.040) and 14.0% in ADMIRE 5 (Z=-2.718, P=0.007) based on FBP. High ADMIRE strength affected the volume score and Agatston score due to the decrease in calcium area. In addition, the change in the Density factor due to the decrease in Maximum HU may affect the calculation of the Agatston score.

Evaluation of Image Quality and Radiation Dose for Filtered Back-Projection and Iterative Reconstruction Algorithm in Abdominal Computed Tomography Protocol (복부 CT 프로토콜에서 필터 보정 역투영법과 반복적 재구성기법에 따른 화질 및 선량에 관한 연구)

  • Oh, Jeong-Min;Seo, Hyeon-Ji;Kim, Yung-Kyoon;Han, Dong-Kyoon
    • Journal of the Korean Society of Radiology
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    • v.15 no.7
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    • pp.1065-1072
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    • 2021
  • In Computed Tomography, abdominal examination showed the highest proportion of use, and effort of reducing the radiation dose is required. Recently introduced Iterative Reconstruction(IR) is repetitive reconstruction technique of Computed Tomography. SIEMENS' IR, ADMIRE and GE's IR, ASIR-V, were used in this examination. Noise, % Contrast, and High contrast resolution were measured by using ACR phantom for image quality evaluation. In addition, CTDIvol and DLP displayed in the CT device were used for dose evaluation. When FBP and IR were compared, stage 2 to stage 5 of ADMIRE and 10, 30, 50, 70, and 90% of ASIR-V were applied, noise could be reduced from a minimum of 0.46 to a maximum of 2.38 in ADMIRE compared to FBP, and noise from a minimum of 0.51 to a maximum of 2.5 in ASIR-V compared to FBP. Also, % Contrast and High contrast resolution of FBP and IR were no statistical difference. When IR was used for abdominal CT examination, the radiation dose of ADMIRE is reduced by 25.39% compared to the radiation dose of FBP. Also, the radiation dose of ASIR-V is reduced by 16.61% compared to the radiation dose of FBP. In conclusion, it is believed that if IR is applied during abdominal CT examination, the radiation dose can be reduced without deteriorating the image quality.

Development of Cloud-Based Medical Image Labeling System and It's Quantitative Analysis of Sarcopenia (클라우드기반 의료영상 라벨링 시스템 개발 및 근감소증 정량 분석)

  • Lee, Chung-Sub;Lim, Dong-Wook;Kim, Ji-Eon;Noh, Si-Hyeong;Yu, Yeong-Ju;Kim, Tae-Hoon;Yoon, Kwon-Ha;Jeong, Chang-Won
    • KIPS Transactions on Computer and Communication Systems
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    • v.11 no.7
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    • pp.233-240
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    • 2022
  • Most of the recent AI researches has focused on developing AI models. However, recently, artificial intelligence research has gradually changed from model-centric to data-centric, and the importance of learning data is getting a lot of attention based on this trend. However, it takes a lot of time and effort because the preparation of learning data takes up a significant part of the entire process, and the generation of labeling data also differs depending on the purpose of development. Therefore, it is need to develop a tool with various labeling functions to solve the existing unmetneeds. In this paper, we describe a labeling system for creating precise and fast labeling data of medical images. To implement this, a semi-automatic method using Back Projection, Grabcut techniques and an automatic method predicted through a machine learning model were implemented. We not only showed the advantage of running time for the generation of labeling data of the proposed system, but also showed superiority through comparative evaluation of accuracy. In addition, by analyzing the image data set of about 1,000 patients, meaningful diagnostic indexes were presented for men and women in the diagnosis of sarcopenia.

Characterization of Deep Learning-Based and Hybrid Iterative Reconstruction for Image Quality Optimization at Computer Tomography Angiography (전산화단층촬영조영술에서 화질 최적화를 위한 딥러닝 기반 및 하이브리드 반복 재구성의 특성분석)

  • Pil-Hyun, Jeon;Chang-Lae, Lee
    • Journal of the Korean Society of Radiology
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    • v.17 no.1
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    • pp.1-9
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    • 2023
  • For optimal image quality of computer tomography angiography (CTA), different iodine concentrations and scan parameters were applied to quantitatively evaluate the image quality characteristics of filtered back projection (FBP), hybrid-iterative reconstruction (hybrid-IR), and deep learning reconstruction (DLR). A 320-row-detector CT scanner scanned a phantom with various iodine concentrations (1.2, 2.9, 4.9, 6.9, 10.4, 14.3, 18.4, and 25.9 mg/mL) located at the edge of a cylindrical water phantom with a diameter of 19 cm. Data obtained using each reconstruction technique was analyzed through noise, coefficient of variation (COV), and root mean square error (RMSE). As the iodine concentration increased, the CT number value increased, but the noise change did not show any special characteristics. COV decreased with increasing iodine concentration for FBP, adaptive iterative dose reduction (AIDR) 3D, and advanced intelligent clear-IQ engine (AiCE) at various tube voltages and tube currents. In addition, when the iodine concentration was low, there was a slight difference in COV between the reconstitution techniques, but there was little difference as the iodine concentration increased. AiCE showed the characteristic that RMSE decreased as the iodine concentration increased but rather increased after a specific concentration (4.9 mg/mL). Therefore, the user will have to consider the characteristics of scan parameters such as tube current and tube voltage as well as iodine concentration according to the reconstruction technique for optimal CTA image acquisition.

Improvement in Image Quality and Visibility of Coronary Arteries, Stents, and Valve Structures on CT Angiography by Deep Learning Reconstruction

  • Chuluunbaatar Otgonbaatar;Jae-Kyun Ryu;Jaemin Shin;Ji Young Woo;Jung Wook Seo;Hackjoon Shim;Dae Hyun Hwang
    • Korean Journal of Radiology
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    • v.23 no.11
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    • pp.1044-1054
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    • 2022
  • Objective: This study aimed to investigate whether a deep learning reconstruction (DLR) method improves the image quality, stent evaluation, and visibility of the valve apparatus in coronary computed tomography angiography (CCTA) when compared with filtered back projection (FBP) and hybrid iterative reconstruction (IR) methods. Materials and Methods: CCTA images of 51 patients (mean age ± standard deviation [SD], 63.9 ± 9.8 years, 36 male) who underwent examination at a single institution were reconstructed using DLR, FBP, and hybrid IR methods and reviewed. CT attenuation, image noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and stent evaluation, including 10%-90% edge rise slope (ERS) and 10%-90% edge rise distance (ERD), were measured. Quantitative data are summarized as the mean ± SD. The subjective visual scores (1 for worst -5 for best) of the images were obtained for the following: overall image quality, image noise, and appearance of stent, vessel, and aortic and tricuspid valve apparatus (annulus, leaflets, papillary muscles, and chordae tendineae). These parameters were compared between the DLR, FBP, and hybrid IR methods. Results: DLR provided higher Hounsfield unit (HU) values in the aorta and similar attenuation in the fat and muscle compared with FBP and hybrid IR. The image noise in HU was significantly lower in DLR (12.6 ± 2.2) than in hybrid IR (24.2 ± 3.0) and FBP (54.2 ± 9.5) (p < 0.001). The SNR and CNR were significantly higher in the DLR group than in the FBP and hybrid IR groups (p < 0.001). In the coronary stent, the mean value of ERS was significantly higher in DLR (1260.4 ± 242.5 HU/mm) than that of FBP (801.9 ± 170.7 HU/mm) and hybrid IR (641.9 ± 112.0 HU/mm). The mean value of ERD was measured as 0.8 ± 0.1 mm for DLR while it was 1.1 ± 0.2 mm for FBP and 1.1 ± 0.2 mm for hybrid IR. The subjective visual scores were higher in the DLR than in the images reconstructed with FBP and hybrid IR. Conclusion: DLR reconstruction provided better images than FBP and hybrid IR reconstruction.

Study on the Repeatability and Reproductivity of a Moire Body Shape Analyser (모아레를 이용한 체형분석의 반복성 재현성에 관한 연구)

  • Lee, Dong-Yup;Park, Young-Bae;Oh, Hwan-Sub
    • The Journal of the Society of Korean Medicine Diagnostics
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    • v.10 no.2
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    • pp.121-131
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    • 2006
  • Background : As each human has a look in the face of oneself, he or she has a look of him or herself in the shape of the body also. And for the shape of the body which gives a big clue in diagnosis in musculoskeletal disorders. Therefor many means are used and developed for diagnosis through body shape or posture analysis for musculoskeletal disorders. X-ray, CT, MRI has been used for diagnosis through image in this way to tell about the inside of the human body. On the other side, moire topography was used for information about the exterior of the human body, but yet only minimal information such as the number of contour lines in each side was available. Therefor there were a few studies to use moire topography or other methods to get information about the surface of the human body in numeric values. The instrument used in this study which is a laser projection moire, is another trial to get numeric data about the surface of the human body. The instrument is composed of laser projector and a computer software to recompose and analyse the image data into depth, height, angle and length. Objectives : The study was focused on whether the instrument is reliable for clinic use, and to seek the proper environment and posture for the examination, and among the data the software provides, which items are more reliable and useful. Methods : For reproductivity and repeatability, 4 testers tested 2 persons. And to how if the body shape changes according to the posture and which posture gives the most reliable data, the test was performed in 6 different positions. Results : Result, the instrument showed sufficient repeatability and reproductivity for clinical use. And among the items the software provides, the length of the back, the angle of the back in the sagittal and coronal plane showed reliable results. And there was difference in the results according to the posture, and Therefor, in following studies using this instrument or similar type of posture analysing instruments, the length of the back, the angle of the back in the sagittal and coronal plane could be reliable item to use.

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Estimation of Human Height and Position using a Single Camera (단일 카메라를 이용한 보행자의 높이 및 위치 추정 기법)

  • Lee, Seok-Han;Choi, Jong-Soo
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.45 no.3
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    • pp.20-31
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    • 2008
  • In this paper, we propose a single view-based technique for the estimation of human height and position. Conventional techniques for the estimation of 3D geometric information are based on the estimation of geometric cues such as vanishing point and vanishing line. The proposed technique, however, back-projects the image of moving object directly, and estimates the position and the height of the object in 3D space where its coordinate system is designated by a marker. Then, geometric errors are corrected by using geometric constraints provided by the marker. Unlike most of the conventional techniques, the proposed method offers a framework for simultaneous acquisition of height and position of an individual resident in the image. The accuracy and the robustness of our technique is verified on the experimental results of several real video sequences from outdoor environments.