• Proceedings of the Korean Information Science Society Conference
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• 2002.10d
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• pp.553-555
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• 2002

컴퓨터지원진단(Computer Aided Diagnosis; CAD) 시스템은 방사선 의사들이 흉부 X-ray 영상에서 결절을 탐지하는데 있어 실제적으로 발생할 수 있는 오진율을 줄이고, 폐 결절이 존재하는 폐야에서 결절의 존재 유무를 판단하여 검출을 표시함으로써 진단율을 개선시킬 수 있도록 하였다. 본 논문은 흉부 X-ray 영상에서의 폐 결절을 추출하는데 유전자 알고리즘(Genetic Algorithm)을 이용한 템플릿 매칭(Template Matching) 방법을 제안한다. 제안한 방법은 흉부 X-ray 영상에 존재하는 결절과 레퍼런스 이미지를 매칭시켜 적합도를 계산한 후, 그 값을 통하여 수치가 낮은 개체를 선택하여 높은 개체와 교차시킨다. 그리고 레퍼런스 이미지는 결절이 존재하는 환자 X-ray 영상에서 샘플 노듈을 추출한 후 가우시안 분포를 갖는 512개의 레퍼런스 이미지를 생성하였다. 본 논문에서 사용된 영상은 결절 50개, 비결절 30개와 흉부 X-ray 영상에서 육안으로 판별이 가능한 결절 영상을 20개를 포함하여 총 100개 영상을 사용하였다. 실험 결과 83%의 결절을 자동 추출 하였으며, 가장 적절한 레퍼런스 이미지를 발견하고 이를 흉부영상에 매칭시켜 정확한 결절의 위치를 확인하였다.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.6
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• pp.243-250
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• 2023

Chest X-ray is radiological examination for xeamining the lungs and haert, and is particularly widely used for diagnosing lung disease. Since the quality of these chest X-rays can affect the doctor's diagnosis, the process of evaluating the quality must necessarily go through. This process can involve the subjectivity of radiologists and is manual, so it takes a lot of time and csot. Therefore, in this paper, based on the chest X-ray quality assessment guidelines used in clinical settings, we propose a tool that automates the five quality assessments of artificial shadow, coverage, patient posture, inspiratory level, and permeability. The proposed tool reduces the time and cost required for quality judgment, and can be further utilized in the pre-processing process of selecting high-quality learning data for the development of a learning model for diagnosing chest lesions.

• Journal of the Korean Society of Radiology
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• v.6 no.6
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• pp.441-445
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• 2012

X-ray Chest P-A is very important and basic diagnosis examination for pregnant women. For a pregnancy period pregnant women should be treated very carefully not to be exposed to any radiation which might cause harmful damage to women and babies as well. Lead apron is one of the effective methods to protect pregnant women from the X-ray radiation. However, it is difficult to obtain the accurate position of pregnant women during X-ray Chest P-A since conventional lead apron method forces pregnant women to hold the apron by themselves only to make pregnant women very uncomfortable and hard to maintain accurate position during radiation. As a consequence, it is common to get low quality images of X-ray Chest P-A due to the overlap of apex of lung and scapular. In order to fix this problem, we made new design lead apron that allowed pregnant women to be more comfortable to maintain accurate position during X-ray Chest P-A position. Finally, with this new design lead apron, it was possible to get the best optimized images of X-ray Chest P-A of pregnant women by minimizing overlapping apex of lung and scapular.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.589-591
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• 2022

흉부 X-ray 영상은 폐 질환을 진단하는 기본적인 도구로써 널리 사용되고 있다. 정확한 진단을 위해 흉부 X-ray 영상의 품질을 평가하는 과정을 거쳐야 하는데, 이 과정은 주관적인 기준에 따라 수 작업으로 이루어지기 때문에 많은 시간과 비용이 소요된다. 따라서 본 논문에서는 임상 현장에서 사용되는 흉부 X-ray 영상 화질 평가 가이드라인을 기반으로 인공음영, 포함범위, 환자자세, 흡기정도, 그리고 투과 상태의 5가지 품질 평가를 자동화하는 도구를 제안한다. 제안하는 도구는 품질 판단에 소요되는 시간과 비용을 줄여주고, 더 나아가 흉부 병변 진단을 위한 학습 모델 개발의 양질의 학습 데이터를 선별하는 전처리 과정에 활용될 수 있다.

• Journal of Chest Surgery
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• v.31 no.7
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• pp.730-734
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• 1998

Background: It is important to know the location, number, size and shape of bullae before thoracotomy or VATS bullectomy. Chest X-ray and chest CT may be used but with some limitation. The purpose of this study was to compare the diagnostic value of thoracography with that of chest X-ray in preoperative detection of bullae. Meterial and Method: Thoracography was performed by injection of non-ionic water-soluble dye into pleural space in 22 primary spontaneous pneumothoraces, which underwent thoracotomy or VATS bullectomy. Chest X-ray and thoracography were compared through operative finding. Results: Sensitivity and accuracy of thoracography(75% and 72.7%) were higher than those of chest X-ray(30% and 36.4%). However, specificity of thoracography(50%) was lower than that of chest X-ray (100%). There were no complications during or after thoracography. Conclusion: Thoracography is a safer and more useful method for preoperative detection of bullae when compared with chest X-ray.

• Journal of radiological science and technology
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• v.46 no.4
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• pp.287-294
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• 2023

This study was conducted to ultimately reduce unnecessary radiation exposure by emphasizing the need and importance of correct positioning by examining the positioning relationship of anatomical structures in the human body and changes in X-ray images according to changes in patient positioning during the left lateral chest X-ray examination. This study investigated and analyzed previously published papers and books on the left lateral chest X-ray examination to find out the importance of positioning in the left lateral chest X-ray examination. To find out the importance of correct positioning in the left lateral chest X-ray, we compared three images of incorrectly positioned right thorax and left thorax rotated forward and the lower median surface of the body leaning against the image receptor. In the left lateral chest examination, a distorted image was obtained in which the shape of the anatomical structure observed in the image was changed according to the presence or absence of rotation of the patient and the inclination of the median visual surface. X-ray images with the most accurate and large amount of information were obtained from X-ray images with the correct positioning performed during left lateral chest X-ray examination. Therefore, It is believed that the left lateral chest X-ray examination will have beneficial effects such as providing accurate medical information, preventing misdiagnosis, reducing social costs, and ultimately reducing radiation exposure.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.37 no.1
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• pp.49-55
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• 2000

Recently, X-ray chest rediography is showing a tendency to take an image of digital radiography so as to diagnose the pathology of chest in a usual. When the radiologist observes the chest image derived from digital radiography system on the monitor, he feels difficult to find out the pathological pattern because the quality of chest radiography is unequal. It takes amount of time to adjust the proper image for diagnosis. Therefore, we propose the method of the chest image equalization using neural networks and provide the compared result with histogram equalization method.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.10
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• pp.97-107
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• 2015

The initial X-ray images obtained from a digital X-ray machine have a wide data range and uneven brightness level than normal images. In particular, in Chest X-ray images, it is necessary to improve naturally all of the parts such as ribs, spine, tissue, etc. These X-ray images can not be improved enough from conventional image quality enhancement algorithms because their characteristics are different from ordinary images'. This paper proposes to eliminate unnecessary background from an input image and expand the histogram range of the image. Then, we adjust the weight per frequency band of the image for improvement of contrast and sharpness. Finally, jointly taking the advantages of global contrast enhancement and local contrast enhancement methods we obtain an improved X-ray image suitable for effective diagnosis in comparison with the existing methods. Experimental results show quantitatively that the proposed algorithm provides better X-ray images in terms of the discrete entropy and saturation than the previous works.

• Journal of radiological science and technology
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• v.45 no.3
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• pp.249-254
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• 2022

The purpose of this study was to examine the importance of proper positioning in chest PA X-ray examination. As a study method, this author searched for and analyzed materials related to chest PA X-ray examination from theses and books that had been published previously to understand the importance of proper positioning in chest PA X-ray examination. Generally, one of the examinations frequently done in most of the hospitals is chest PA X-ray examination. Also, in any kinds of X-ray examination, proper positioning is the most fundamental and definite way to provide accurate information about the patient. Poor positioning in chest PA X-ray examination may jeopardize the diagnosis and treatment, increase social cost due to examination needed to be done additionally, and generate additional radiation exposure unnecessarily above all. In conclusion, it is expected that proper positioning in chest PA X-ray examination will exert positive effects such as the provision of accurate information about the patient, prevention of misdiagnosis, reduction in social cost, and lastly decrease in radiation exposure.

• Journal of the Korean Society of Radiology
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• v.14 no.1
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• pp.39-44
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• 2020

The purpose of this study was learning about chest X-ray image classification and accuracy research through Deep Learning using big data technology with Convolution Neural Network. Normal 1,583 and Pneumonia 4,289 were used in chest X-ray images. The data were classified as train (88.8%), validation (0.2%) and test (11%). Constructed as Convolution Layer, Max pooling layer size 2×2, Flatten layer, and Image Data Generator. The number of filters, filter size, drop out, epoch, batch size, and loss function values were set when the Convolution layer were 3 and 4 respectively. The test data verification results showed that the predicted accuracy was 94.67% when the number of filters was 64-128-128-128, filter size 3×3, drop out 0.25, epoch 5, batch size 15, and loss function RMSprop was 4. In this study, the classification of chest X-ray Normal and Pneumonia was predictable with high accuracy, and it is believed to be of great help not only to chest X-ray images but also to other medical images.