• Journal of radiological science and technology
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• v.40 no.2
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• pp.197-203
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• 2017

The purpose of this study was to measure signal to noise ratio (SNR) according to change of equalization from region of interest (ROI) of heart shadow in chest image. We examined images of chest image of 87 patients in a University-affiliated hospital, Seoul, Korea. Chest images of each patient were calculated by using ImageJ. We have analysis socio-demographical variables, SNR according to images, 95% confidence according to SNR of difference in a mean of SNR. Differences of SNR among change of equalization were tested by SPSS Statistics21 ANOVA test for there was statistical significance 95%(p < 0.05). In SNR results, with the quality of distributions in the order of original chest image, original chest image heart shadow and equalization chest image, equalization chest image heart shadow(p < 0.001). In conclusion, this study would be that quantitative evaluation of heart shadow on chest image can be used as an adjunct to the histogram equalization chest image.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.7
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• pp.1573-1582
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• 2011

Risk of lung cancer among lung-related diseases has gradually increased during last decades. The chest digital radiography is the primary diagnosis method for lung cancer. Diagnosing lung cancer using this method requires doctors of ripe experience. Despite their experience there are often wrong diagnoses, which decrease early diagnosis and survival rates of patients. The aim of this study was intended to establish the base on the Computer Aided Diagnosis (CAD) by analyzing Image Recognition Algorithm using Principle component Analysis (PCA) and diagnosing patient's chest X-ray image. The database obtained through this approach enables a doctor to significantly reduce misdiagnosis during the early diagnosis stage, if he or she utilizes it as the preliminary reading step. Case studies were carried out using normal organ, and organs suffering from bronchogenic carcinoma and granuloma. A normal image and unique disease images were extracted after PCA analysis, and their cross-recognition efficiency were compared each other. The result revealed that the recognition rate was much high between normal and disease images, but relatively low between two disease images. In order to increase the recognition efficiency among chest diseases the related algorithms have to be developed continuously in the future study, and such effort will establish the resolute base for CAD.

• Journal of the Korean Society of Radiology
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• v.82 no.4
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• pp.1000-1004
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• 2021

Percutaneous transthoracic needle biopsy (PTNB) is a minimally-invasive procedure that is an indispensable tool for evaluating pulmonary lesions. Though extremely rare, tumor seeding of the pleura and chest wall can occur as a complication. Given that the breast is located anterior to the thorax, needle tracking through the breast is inevitable when PTNB is performed using the anterior approach. We describe tumor seeding of metastatic pulmonary ameloblastoma in the pectoralis muscle layer of the breast along the needle track of PTNB in a 51-year-old female presenting with a palpable lump in the right breast.

• Journal of the Korean Society of Radiology
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• v.81 no.6
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• pp.1334-1347
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• 2020

Coronavirus disease (COVID-19) has threatened public health as a global pandemic. Chest CT and radiography are crucial in managing COVID-19 in addition to reverse transcription-polymerase chain reaction, which is the gold standard for COVID-19 diagnosis. This is a review of the current status of the use of chest CT and radiography in COVID-19 diagnosis and management and anㄷ introduction of early representative studies on the application of artificial intelligence to chest CT and radiography. The authors also share their experiences to provide insights into the future value of artificial intelligence.

• Journal of the Korean Society of Radiology
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• v.12 no.4
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• pp.519-524
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• 2018

Chest examinations and mass chest examinations using the CR(computed radiography) System are frequently used clinically. a factor that degrades image quality in the acquisition process is the use of unused IPs long times. this paper addresses the estimation of winer filter and improved wiener filter to restoration of Chest CR images Experimental results show that the proposed method can reduce noise. in low noise variation image wiener method was excellent than improved method and the result was the opposite at high noise varience. the application of algorithms to chest CR images effectively eliminates noise. the classic Wiener filter was better than the improved method. Multiple patients examined during the process without any erase IP(image plate) process, The proposed algorithm determines that the images can be restored to a good quality and will help to read the images.

• Journal of radiological science and technology
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• v.28 no.4
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• pp.273-277
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• 2005

The rapid development in digital acquisition technology in radiography has not been accompanied by information regarding optimum radiolographic technique for use with an amorphus silicon flat panel detector. The purpose of our study was to compared image quality and radiation dose of an amorphus silicon flat panel detectors for digital chest radiography. All examinations were performed by using an amorphus silicon flat panel detector. Chest radiographs of an chest phantom were obtained with peak kilovoltage values of $60{\sim}150kVp$. Published data on the effect of x-ray beam energy on image quality and patient dose when using an amorphus silicon flat panel detector. It is important that radiographers are aware of optimum kVp selection for an amorphus silicon flat panel detector system, particularly for the commonly performed chest examination.

• 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.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.903-906
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• 2021

인공지능 기술 발전으로, 의료영상 분야에서도 딥러닝 기반 질병 진단 연구가 활발히 진행되고 있다. 딥러닝 모델 개발 시, 학습 데이터 품질은 모델의 성능과 신뢰성에 매우 큰 영향을 미친다. 그러나 의료 분야의 경우 도메인 지식에 대한 진입 장벽이 높아 개발자가 학습에 사용되는 의료영상 데이터의 품질을 평가하기 어렵다. 이로 인해, 많은 의료영상 분야에서는 각 분야의 특성(질병의 종류, 관찰 아나토미 등)에 따른 영상 품질 평가 방법을 제시해왔다. 그러나 기존의 방법은 특정 질병에 초점이 맞춰져, 일반화된 품질 평가 기준을 제시하고 있지 않다. 따라서 본 논문에서는 대부분의 흉부 질환을 진단하기 위한 흉부 X선 영상의 품질을 평가할 수 있는 기준을 제안한다. 우선, 흉부 X선 영상을 대상으로 관찰된 영역인 심장, 횡격막, 견갑골, 폐 등을 분할하여, 3D 히스토그램을 기반으로 각 영역별 통계적인 정밀 품질 평가 기준을 제안한다. 본 연구에서는 JSRT, Chest 14의 오픈 데이터셋을 활용하여 적용 실험을 수행하였으며, 민감도는 97.6%, 특이도는 92.8%의 우수한 성능을 확인하였다.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.9 no.1
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• pp.61-66
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• 2015

Chest X-ray images is the most common and widely used in clinical findings for a wide range of anatomical information about the prognosis of the disease in patients with cardiopulmonary rehabilitation. Many analysis algorithm was developed by a number of studies regarding the region segmentation and image analysis, there are specific differences due to the complexity and diversity of the image. In this paper, a diagnosis support system of the chest X-ray image based on image processing and analysis methods to detect the cardiopulmonary disease. The threshold value and morphological method was applied to segment the pulmonary region in a chest X-ray image. Anatomical measurements and texture analysis was performed on the segmented regions. The effectiveness of the proposed method is shown through experiments and comparison with diagnosis results by clinical experts to show that the proposed method can be used for decision support system.

• Journal of the Korean Society of Radiology
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• v.82 no.3
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• pp.562-574
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• 2021

MRI has the advantages of having excellent soft-tissue contrast and providing functional information without any harmful ionizing radiation. Although previous technical limitations restricted the use of chest MRI, recent technological advances and expansion of insurance coverage are increasing the demand for chest MRI. Recognizing the need for guidelines on appropriate use of chest MRI in Korean clinical settings, the Korean Society of Radiology has composed a development committee, working committee, and advisory committee to develop Korean chest MRI justification guidelines. Five key questions were selected and recommendations have been made with the evidence-based clinical imaging guideline adaptation methodology. Recommendations are as follows. Chest MRI can be considered in the following circumstances: for patients with incidentally found anterior mediastinal masses to exclude non-neoplastic conditions, for pneumoconiosis patients with lung masses to differentiate progressive massive fibrosis from lung cancer, and when invasion of the chest wall, vertebrae, diaphragm, or major vessels by malignant pleural mesothelioma or non-small cell lung cancer is suspected. Chest MRI without contrast enhancement or with minimal dose low-risk contrast media can be considered for pregnant women with suspected pulmonary embolism. Lastly, chest MRI is recommended for patients with pancoast tumors planned for radical surgery.