• 제목/요약/키워드: chest X-ray imaging

검색결과 92건 처리시간 0.02초

호흡기 질환에서 단순흉부 X-선 진단 (Plain Chest X-ray Diagnosis of Respiratory Disease)

  • 김상진
    • Tuberculosis and Respiratory Diseases
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    • 제40권4호
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    • pp.353-356
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    • 1993
  • Advent of new imaging modalities such as computed tomography, magnetic resonance imaging and ultrasound contributed greately to the specific imaging diagnosis. However plain chest X-ray is still most prequently used for imaging diagnosis of respiratory disease in clinical pratic and it is important to make a good quality of X-ray film and good interpretation. The optimal chest X-ray should be taken with full inspiration without rotation and motion and the exposure is at the level of barely demonstrable thoracic vertebral disc space. It is recommended that higk KVP technique for detection of lesions which is overlaped by mediastinum, heart and rib cage. It is better to examine chest X-ray film start at some distance(6-8 feet) and closer to the film later on and the reader should not read a film in fatigue condition. The reading room should be quiet and relately dark illumination. It is important, to make a good X-ray film and good interpretation to reduce the observer error.

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영상의학과 이동검사 영역의 공간선량 분포에 대한 측정 및 분석 (The Measurement and Analysis by Free Space Scatter Dose Distribution of Diagnostic Radiology Mobile Examination Area)

  • 김성규;손상혁
    • 대한디지털의료영상학회논문지
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    • 제11권1호
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    • pp.5-13
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    • 2009
  • There are several reasons to take X-ray in case of inpatients. Some of them who cannot ambulate or have any risk if move are taken portable X-ray at their wards. Usually, in this case, many other people-patients unneeded X-ray test, family, hospital workers etc-are indirectly exposed to X-ray by scatter ray. For that reason I try to be aware of free space scatter dose accurately and make the point at issue of portable X-ray better in this study. kVp dose meter is used for efficiency management of portable X-ray equipment. Mobile X-ray equipment, ionization chamber, electrometer, solid water phantom are used for measuring of free space scatter dose. First of all the same surroundings condition is made as taken real portable X-ray, inquired amount of X-ray both chest AP and abdomen AP most frequently examined and measured scatter ray distribution of two tests individually changing distance. In the result of measuring horizontal distribution with condition of chest AP it is found that the mAs is decreased as law of distance reverse square but no showed mAs change according to direction. Vertical distribution showed the mAs slightly higher than horizontal distribution but it isnt found out statistical characteristic. In abdomen AP, compare with chest AP, free space scatter dose is as higher as five-hundred times and horizontal, vertical distribution are quite similar to chest AP in result. In portable X-ray test, in order to reduce the secondary exposure by free space scatter dose first, cut down unnecessary portable order the second, set up the specific area at individual ward for the test the third, when moving to a ward for the X-ray test prepare a portable shielding screen. The last, expose about 2m apart from patients if unable to do above three ways.

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Restoration of Chest X-ray by Kalman Filter

  • Kim, Jin-Woo
    • Journal of information and communication convergence engineering
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    • 제8권5호
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    • pp.581-585
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    • 2010
  • A grid was sandwiched between two cascaded imaging plates. Using a fan-beam X-ray tube and a single exposure scheme, the two imaging plates, respectively, recorded grid-less and grid type information of the object. Referring to the mathematical model of the Grid-less and grid technique, it was explained that the collected components whereas that of imaging plates with grid was of high together with large scattered components whereas that of imaging plate with grid was of low and suppressed scattered components. Based on this assumption and using a Gaussian convolution kernel representing the effect of scattering, the related data of the imaging plates were simulated by computer. These observed data were then employed in the developed post-processing estimation and restoration (kalman-filter) algorithms and accordingly, the quality of the resultant image was effectively improved.

흉부 X-선 영상을 이용한 14 가지 흉부 질환 분류를 위한 Ensemble Knowledge Distillation (Ensemble Knowledge Distillation for Classification of 14 Thorax Diseases using Chest X-ray Images)

  • 호티키우칸;전영훈;곽정환
    • 한국컴퓨터정보학회:학술대회논문집
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    • 한국컴퓨터정보학회 2021년도 제64차 하계학술대회논문집 29권2호
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    • pp.313-315
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    • 2021
  • Timely and accurate diagnosis of lung diseases using Chest X-ray images has been gained much attention from the computer vision and medical imaging communities. Although previous studies have presented the capability of deep convolutional neural networks by achieving competitive binary classification results, their models were seemingly unreliable to effectively distinguish multiple disease groups using a large number of x-ray images. In this paper, we aim to build an advanced approach, so-called Ensemble Knowledge Distillation (EKD), to significantly boost the classification accuracies, compared to traditional KD methods by distilling knowledge from a cumbersome teacher model into an ensemble of lightweight student models with parallel branches trained with ground truth labels. Therefore, learning features at different branches of the student models could enable the network to learn diverse patterns and improve the qualify of final predictions through an ensemble learning solution. Although we observed that experiments on the well-established ChestX-ray14 dataset showed the classification improvements of traditional KD compared to the base transfer learning approach, the EKD performance would be expected to potentially enhance classification accuracy and model generalization, especially in situations of the imbalanced dataset and the interdependency of 14 weakly annotated thorax diseases.

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인공 지능을 이용한 흉부 엑스레이 이미지에서의 이물질 검출 (Detecting Foreign Objects in Chest X-Ray Images using Artificial Intelligence)

  • 한창화
    • 한국방사선학회논문지
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    • 제17권6호
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    • pp.873-879
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    • 2023
  • 본 연구는 인공지능(AI)을 사용하여 흉부 엑스레이 이미지에서 이물질을 탐지하는 방법을 탐구하였다. 의료영상학, 특히 흉부 엑스레이는 폐렴이나 폐암과 같은 질병을 진단하는 데 매우 중요한 역할을 한다. 영상의학 검사가 증가함에 따라 AI는 효율적이고 빠른 진단을 위한 중요한 도구가 되었다. 하지만 이미지에는 단추나 브래지어 와이어와 같은 일상적인 장신구를 포함한 이물질이 포함될 수 있어 정확한 판독을 방해할 수 있다. 본 연구에서는 이러한 이물질을 정확하게 식별하는 AI 알고리즘을 개발하였고, 미국 국립보건원 흉부 엑스레이 데이터셋을 가공하여 YOLOv8 모델을 기반으로 처리하였다. 그 결과 정확도, 정밀도, 리콜, F1-score가 모두 0.91에 가까울 정도로 높은 탐지 성능을 보였다. 이번 연구는 AI의 뛰어난 성능에도 불구하고 이미지 내 이물질로 인해 판독 결과가 왜곡될 수 있는 문제점을 해결함으로써 영상의학 분야에서 AI의 혁신적인 역할과 함께, 임상 구현에 필수적인 정확성에 기반하여 신뢰성을 강조하였다.

Fuzzy Logic Systems을 이용한 X-선 영상의 진단평가 (Diagonstic Evaluation of X-Ray Imaging using Fuzzy Logic Systems)

  • 이용구
    • 전자공학회논문지 IE
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    • 제46권3호
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    • pp.62-67
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    • 2009
  • 본 논문에서는 퍼지논리시스템을 이용하여 ROC 곡선을 설계하였다. ROC 곡선은 진단평가를 위하여 이용되고, ROC 곡선을 평가하는 진단자는 초보 진단자를 선정하였다. 학습을 통한 ROC 곡선에 관한 진단능력을 평가하기 위하여 흉부 X-선 사진이 사용되었다. 진단을 위해 잡음과 신호(병변)을 갖는 X-선 필름을 사용하였다. 남성과 여성 간의 진단능력의 차이에 관하여 나타난 결과는 여성보다 남성이 우세한 것으로 나타났으나 그 차이는 작은 것으로 나타났다.

이동형 X선 장치 차폐도구 제작을 통한 표면선량 분포 측정 (Measurement of Skin Dose Distribution for the Mobile X-ray Unit Collimator Shielding Device)

  • 홍선숙;김득용
    • 대한디지털의료영상학회논문지
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    • 제12권1호
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    • pp.5-8
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    • 2010
  • Opened a court in February 10, 2006, a rule of safety management of the diagnosis radiation system was promulgated for safety of the radiation worker, patients and patients' family members. The purpose of this rule is to minimize the risk of being exposed to radiation during the process of handling X-ray. For this reason, we manufactured shielding device of mobile X-ray unit collimator for diminution of skin dose. Shielding device is made to a thickness of Pb 0.375mm. For portable chest radiography, we measured skin dose 50cm from center ray to 200cm at intervals of 20cm by Unfors Xi detector. As a result, a rule of safety management of the diagnosis radiation system has been strengthened. But there are exceptions, such as ER, OR, ICU to this rule. So shielding device could contribute to protect unnecessary radiation exposure and improve nation's health.

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엑스선촬영 각도를 측정할 수 있는 장치 개발과 흉부 X선 영상촬영에서의 적용 (Development of portable digital radiography system with device for sensing X-ray source-detector angle and its application in chest imaging)

  • 김태훈;허동운;류종현;정창원;전홍영;김규겸;홍지민;장미연;김대원;윤권하
    • 한국컴퓨터정보학회:학술대회논문집
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    • 한국컴퓨터정보학회 2017년도 제55차 동계학술대회논문집 25권1호
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    • pp.235-238
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    • 2017
  • This study was to develop a portable digital radiography (PDR) system with a function measuring the X-ray source-with-detector angle (SDA) and to evaluate the imaging performance for the diagnosis of chest imaging. The SDA device consisted of an Arduino, an accelerometer and gyro sensor, and a Bluetooth module. According to different angle degrees, five anatomical landmarks on chest images were assessed using a 5-point scale. Mean signal-to-noise ratio and contrast-to-noise ratio were 182.47 and 141.43. Spatial resolution (10% MTF) and entrance surface dose were 3.17 lp/mm ($157{\mu}m$) and 0.266mGy. The angle values of SDA device were not significant difference as compared to those of the digital angle meter. In chest imaging, SNR and CNR values were not significantly different according to different angle degrees (repeated-measures ANOVA, p>0.05). The visibility scores of the border of heart, 5th rib and scapula showed significant differences according to different angles (rmANOVA, p<0.05), whereas the scores of the clavicle and 1st rib were not significant. It is noticeable that the increase in SDA degree was consistent with the increase of visibility score. Our PDR with SDA device would be useful to be applicable to clinical radiography setting according to the standard radiography guideline at various fields.

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A Deep Learning Approach for Covid-19 Detection in Chest X-Rays

  • Sk. Shalauddin Kabir;Syed Galib;Hazrat Ali;Fee Faysal Ahmed;Mohammad Farhad Bulbul
    • International Journal of Computer Science & Network Security
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    • 제24권3호
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    • pp.125-134
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    • 2024
  • The novel coronavirus 2019 is called COVID-19 has outspread swiftly worldwide. An early diagnosis is more important to control its quick spread. Medical imaging mechanics, chest calculated tomography or chest X-ray, are playing a vital character in the identification and testing of COVID-19 in this present epidemic. Chest X-ray is cost effective method for Covid-19 detection however the manual process of x-ray analysis is time consuming given that the number of infected individuals keep growing rapidly. For this reason, it is very important to develop an automated COVID-19 detection process to control this pandemic. In this study, we address the task of automatic detection of Covid-19 by using a popular deep learning model namely the VGG19 model. We used 1300 healthy and 1300 confirmed COVID-19 chest X-ray images in this experiment. We performed three experiments by freezing different blocks and layers of VGG19 and finally, we used a machine learning classifier SVM for detecting COVID-19. In every experiment, we used a five-fold cross-validation method to train and validated the model and finally achieved 98.1% overall classification accuracy. Experimental results show that our proposed method using the deep learning-based VGG19 model can be used as a tool to aid radiologists and play a crucial role in the timely diagnosis of Covid-19.

웨이브렛 변환과 자동적인 임계치 설정에 의한 미세 석회화 검출 (Microcalcification Extraction by Wavelet Transform and Automatic Thresholding)

  • 원철호;서용수;조진호
    • 한국멀티미디어학회논문지
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    • 제8권4호
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    • pp.482-491
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    • 2005
  • 본 논문에서는 디지털 X선 유방 촬영 시스템에서 획득된 영상으로부터 웨이브릿 변환과 자동적인 임계치 설정기법을 이용하여 미세 석회화 영역을 추출하였다. 디지털 X선 영상 장비는 임상 진단 분야에서는 필수적인 진단 장비이며, 흉부 촬영, 골절상 및 치아 교정 등의 다양한 분야에 사용되고 있다. 특히 디지털 X선 유방 촬영술은 유방암 진단의 가장 좋은 방법으로 알려져 있으며 최근 국내에서 디지털 X선 기기를 개발하기 위한 많은 연구들이 진행되고 있다. 본 논문에서는 디지털 X선 유방 촬영 영상으로부터 초기 단계의 유방암 진단을 위해 필수적인 미세 석회화를 검출하는 알고리즘을 제안하여 이를 효과적으로 검출하였으며 진단 방사선학적 진단에 도움을 줄 수 있음을 보였다.

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