• 제목/요약/키워드: Image detector data

검색결과 205건 처리시간 0.026초

시준기의 특성으로 인한 SPECT 왜곡 화상의 보정 (Correction of Single Photon Emission CT Image Distorted by Collimator Characteristic)

  • 백승권
    • 융합신호처리학회논문지
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    • 제5권1호
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    • pp.18-24
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    • 2004
  • Single Photon Emission CT(SPECT)기술은 산업의 비접촉 계측 시스템 분야에 있어서 단층 영상을 얻는데 이용되고 있다. 재구성된 영상의 화질이 왜곡되는 문제점의 하나는 시준기 특성에 있다. 영상 왜곡은 시준기의 기하학적 구조에 원인이 있다. 본 논문은 시준기의 구조로 인한 영상 왜곡을 제거하는 보정법을 제시하고 기존의 보정법과 비교하였다. 보정법은 투영 데이터를 공간 주파수상에서 위치 의존적 왜곡 함수로 디콘볼루션 하여 영상 왜곡을 제거하였다. 본 논문에서 시준기의 각도, 검출기와 물체 중심의 거리에 대하여 시뮬레이션을 하고, 실험을 통하여 검증하였다. 실제산업에서의 응용을 고려하여 보정법의 유효성 및 한계를 검토하였다.

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꼭짓점 정보를 이용한 자동차 번호판 검출 (Vehicle Number Plate Detection using Corner Information)

  • 김진욱;박중조
    • 융합신호처리학회논문지
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    • 제13권4호
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    • pp.173-179
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    • 2012
  • 본 논문에서는 자동차 번호판을 검출하는 새로운 방법을 제시한다. 자동차 번호판은 사각형 모양이므로 우리의 방법은 기본적으로 입력 영상에서 사각형을 추출하는 방법이 된다. 번호판을 검출하기 위해, 먼저 입력영상의 콘트라스트를 향상시키고, 그 후 LSD(Line segment detector) 기법을 사용하여 영상내의 선을 검출하고, 이 선 정보로 부터 사각형들을 추출 한다. 이 사각형들은 번호판 후보들이 되고, 이로부터 번호판이 검출된다. 이중에서 본 연구가 제안하는 부분은 사각형 추출방법으로서, 이 방법은 3단계로 구성된다: (1) 먼저, LSD에 의해 얻어진 선으로부터 꼭짓점들을 추출한다; (2) 구해진 꼭짓점들을 사용하여 사각형의 대각선을 검출한다; (3) 그 후, 대각선 정보를 이용하여 사각형을 추출해 낸다. 최종적으로 번호판 특성과 사각형 내부 정보를 이용하여 이 사각형들로부터 번호판이 선택된다. 100장의 자동차 영상을 촬영하여 실험한 결과 94%의 검출율을 달성하였다.

선형모형과 표준편차에 기반한 잡음영상에 효과적인 에지 검출 방법 (An effective edge detection method for noise images based on linear model and standard deviation)

  • 박영호
    • 응용통계연구
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    • 제33권6호
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    • pp.813-821
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    • 2020
  • 최근 다양한 분야에서 사진, 동영상 등과 같이 비정형 데이터를 이용한 연구가 활발하게 진행되고 있다. 이 중에서도 영상을 활용하는 연구들은 영상에 포함된 정보를 사용하기 위하여 많은 영상처리 기법들을 사용하고 있다. 에지 검출은 영상에서 정보를 추출하기 위해 많은 영상처리 응용 프로그램에서 사용되는 기본 도구이다. 그러나 잡음이 포함된 영상은 에지와 잡음이 모두 고주파 성분을 가지고 있기 때문에 에지 검출을 수행하는 것은 매우 어렵다. 본 논문은 잡음이 감소된 에지를 추출하는 방법으로 선형모형과 표준편차를 이용하였다. 화소 블록에 포함된 화소들의 표준편차와 선형모형의 적합으로 얻어진 잔차에 대한 표준편차의 차이로 에지를 검출하였다. 에지 검출의 결과는 영상처리 분야에서 대표적으로 사용되는 소벨 에지 검출기의 결과와 비교하였다. 잡음이 포함되지 않은 영상은 소벨 에지 검출 결과와 제안한 에지 검출의 결과가 유사하게 나타나고, 제안한 방법이 다양한 수준의 잡음이 추가된 영상에서 잡음에 의한 에지가 적게 나타나는 것을 확인하였다.

ANALYSIS BY SYNTHESIS FOR ESTIMATION OF DOSE CALCULATION WITH gMOCREN AND GEANT4 IN MEDICAL IMAGE

  • Lee, Jeong-Ok;Kang, Jeong-Ku;Kim, Jhin-Kee;Kim, Bu-Gil;Jeong, Dong-Hyeok
    • Journal of Radiation Protection and Research
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    • 제37권3호
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    • pp.146-148
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    • 2012
  • The use of GEANT4 simulation toolkit has increased in the radiation medical field for the design of treatment system and the calibration or validation of treatment plans. Moreover, it is used especially on calculating dose simulation using medical data for radiation therapy. However, using internal visualization tool of GEANT4 detector constructions on expressing dose result has deficiencies because it cannot display isodose line. No one has attempted to use this code to a real patient's data. Therefore, to complement this problem, using the result of gMocren that is a three-dimensional volume-visualizing tool, we tried to display a simulated dose distribution and isodose line on medical image. In addition, we have compared cross-validation on the result of gMocren and GEANT4 simulation with commercial radiation treatment planning system. We have extracted the analyzed data of dose distribution, using real patient's medical image data with a program based on Monte Carlo simulation and visualization tool for radiation isodose mapping.

Exposure Index를 이용한 이동형 디지털 X선 장치의 흉부촬영 적정노출조건에 관한 연구 (A Study on the Proper Chest Exposure Conditions of Mobile Digital X-ray Unit by Exposure Index)

  • 김재인;이양섭;장동수;정민철;배승호;이관섭;하동윤
    • 대한디지털의료영상학회논문지
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    • 제13권3호
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    • pp.139-144
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    • 2011
  • The purpose of this report is recommending a standard indicator which reflects the radiation exposure that is incident on a detector after every exposure event and that reflects the noise levels present in the image data. The experiment was performed with mobile digital X-ray unit and used a acrylic phantom for exposure index measurement. Exposure modality was kVp, mAs, SID. After every exposure, make a data sheet for characteristic curve of detector response. The equipment performed Mobile digital X-ray unit provide the user with values ralated to the incident exposure(air kerma)to the digital detector. They are showed as a logarithmic function shaped. As a result, DEI means a relative measure of exposure to the detector, as compared to the expected exposure for a particular anatomical view. Radiographic technique is the combination of factors used to exposure an anatomical part to produce a high quality radiography and technique charts used most commonly by radiographers to produce consistently exposure level which patient dose can be kept acceptably low.

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자동노출제어장치를 이용한 요추 측면 방사선검사 시 환자 중심 위치 변화가 선량과 화질에 미치는 영향 (Effects of Dose and Image Quality according to Center Location in Lumbar Spine Lateral Radiography Using AEC Mode)

  • 정운찬;주영철
    • 대한방사선기술학회지:방사선기술과학
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    • 제44권2호
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    • pp.85-90
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    • 2021
  • The purpose of this study is to consider usefulness of using AEC mode and importance of patient center location in L-spine lateral radiography by comparing dose and image quality according to the change of patient center location with using AEC mode or not. In this study, guide wire is attached to the human body phantom's lumbar spine and the lead ruler is attached to the bottom of the wall detector to find out center location in detector. ESD, mAs, and EI were selected as dose factors, and image quality was compared through SNR. With the lumbar spine located center of the detector, dose factors and image quality were compared according to using AEC mode or not. Afterwards, phantom moved 4 cm and 8 cm back and forth and compared dose factors and image quality. The exposure parameters were 85 kVp, 320 mA, x-ray field size 10×17 inch, and the distance between the center X-ray and the detector was fixed at 100 cm. The center X-ray was perpendicular to the fourth lumbar spine and the only bottom AEC chamber was used. All data were analyzed by independent t-test and ANOVA. As a result of this study, with AEC when the center is matched, ESD was 1.31±0.01 mGy, without AEC was 2.12±0.01 mGy. SNR was shown to be 22.81±1.83, and 23.44±1.87 respectively. When the phantom's center moves 4 cm, 8 cm forward, and 4 cm, 8 cm backward, ESD were 1.09±0.004 mGy, 0.32±0.003 mGy, 1.19±0.017 mGy, 1.11±0.006 mGy respectively, SNR were 18.29±0.60 dB, 11.11±0.22 dB, 18.98±0.80 dB, 17.71±0.82 dB. Using AEC in L-spine lateral radiography reduced ESD by 38%, EI by 35%, and mAs by 38%, without any difference in SNR(p<0.05). When the phantom's center moves 4 cm, 8 cm forward, and 4 cm, 8 cm backward, ESD was decreasing each 16%, 75%, 9%, 15%, EI was decreasing each 14%, 77%, 15%, 20%, mAs was decreasing each 15% 75% 9%, 15%. SNR was decreasing each 19%, 51%, 17%, 22%.

Multi-Channel Data Acquisition System Design for Spiral CT Application

  • Yoo, Sun-Won;Kim, In-Su;Kim, Bong-Su;Yun Yi;Kwak, Sung-Woo;Cho, Kyu-Sung;Park, Jung-Byung
    • 한국의학물리학회:학술대회논문집
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    • 한국의학물리학회 2002년도 Proceedings
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    • pp.468-470
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    • 2002
  • We have designed X-ray detection system and multi-channel data acquisition system for Spiral CT application. X-ray detection system consists of scintillator and photodiode. Scintillator converts X-ray into visible light. Photodiode converts visible light into electrical signal. The multi-channel data acquisition system consists of analog, digital, master and backplane board. Analog board detects electrical signal and amplifies signal by 140dB. Digital board consists of MUX(Multiplex) which routes multi-channel analog signal to preamplifier, and ADC(Analog to Digital Converter) which converts analog signal into digital signal. Master board supplies the synchronized clock and transmits the digital data to image reconstructor. Backplane provides electrical power, analog output and clock signal. The system converts the projected X-ray signal over the detector array with large gain, samples the data in each channel sequentially, and the sampled data are transmitted to host computer in a given time frame. To meet the timing limitation, this system is very flexible since it is implemented by FPGA(Field Programmable Gate Array). This system must have a high-speed operation with low noise and high SNR(signal to noise ratio), wide dynamic range to get a high resolution image.

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Carpal Bone Segmentation Using Modified Multi-Seed Based Region Growing

  • Choi, Kyung-Min;Kim, Sung-Min;Kim, Young-Soo;Kim, In-Young;Kim, Sun-Il
    • 대한의용생체공학회:의공학회지
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    • 제28권3호
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    • pp.332-337
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    • 2007
  • In the early twenty-first century, minimally invasive surgery is the mainstay of various kinds of surgical fields. Surgeons gave percutaneously surgical treatment of the screw directly using a fluoroscopic view in the past. The latest date, they began to operate the fractured carpal bone surgery using Computerized Tomography (CT). Carpal bones composed of wrist joint consist of eight small bones which have hexahedron and sponge shape. Because of these shape, it is difficult to grasp the shape of carpal bones using only CT image data. Although several image segmentation studies have been conducted with carpal bone CT image data, more studies about carpal bone using CT data are still required. Especially, to apply the software implemented from the studies to clinical fIeld, the outcomes should be user friendly and very accurate. To satisfy those conditions, we propose modified multi-seed region growing segmentation method which uses simple threshold and the canny edge detector for finding edge information more accurately. This method is able to use very easily and gives us high accuracy and high speed for extracting the edge information of carpal bones. Especially, using multi-seed points, multi-bone objects of the carpal bone are extracted simultaneously.

Comparison of estimating vegetation index for outdoor free-range pig production using convolutional neural networks

  • Sang-Hyon OH;Hee-Mun Park;Jin-Hyun Park
    • Journal of Animal Science and Technology
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    • 제65권6호
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    • pp.1254-1269
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    • 2023
  • This study aims to predict the change in corn share according to the grazing of 20 gestational sows in a mature corn field by taking images with a camera-equipped unmanned air vehicle (UAV). Deep learning based on convolutional neural networks (CNNs) has been verified for its performance in various areas. It has also demonstrated high recognition accuracy and detection time in agricultural applications such as pest and disease diagnosis and prediction. A large amount of data is required to train CNNs effectively. Still, since UAVs capture only a limited number of images, we propose a data augmentation method that can effectively increase data. And most occupancy prediction predicts occupancy by designing a CNN-based object detector for an image and counting the number of recognized objects or calculating the number of pixels occupied by an object. These methods require complex occupancy rate calculations; the accuracy depends on whether the object features of interest are visible in the image. However, in this study, CNN is not approached as a corn object detection and classification problem but as a function approximation and regression problem so that the occupancy rate of corn objects in an image can be represented as the CNN output. The proposed method effectively estimates occupancy for a limited number of cornfield photos, shows excellent prediction accuracy, and confirms the potential and scalability of deep learning.

MDCT에서 Curved MPR을 이용한 효과적인 영상진단 (The Effective Image Diagnosis Using Curved MPR from MDCT)

  • 송종남;장영일
    • 대한디지털의료영상학회논문지
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    • 제12권2호
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    • pp.139-143
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    • 2010
  • Two-dimensional(2D) images like Multi Planar Reconstruction(MPR) Image or Maximum Intensity Projection(MIP) were used for the purpose of diagnosis, but MPR image's quality were limited due to its superior limit of Z-axis ability to produce permitted radiation exposure virtuous in the permitted time limit from the existing Spiral CT. However, in company with the development of the Multi Detector Computed Tomography(MDCT), we were able to get the Data with the equal amount of Voxel, also get varied reconstructions as in the aspect of our needs. This present study propose a reconstruction technique which is to extract a field using Region of interest(ROI) segmentation method for improvement of the quality of the medical image and after that reconstruct the concerned part using the four-directed symmetry method of the oval, than using the reconstructed data, reorganize the image by using the Curved MPR method. If current proposed method is used, it is highly effective because of its ability to accurately display the disease concerned part, which will reduce the decoding time and also effectively provide information based on the accuracy of the decode.

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