가열장치를 구비한 부착형 탄소발열체 X선 촬영대 고안

송종남,김응곤 한국방사선학회 2015 한국방사선학회 논문지 Vol.9 No.3

본 연구의 목적은 기존에 사용 중인 X선 발생장치의 촬영대를 따뜻하게 가열하면서도 X선 감약이 적은 탄소나노튜 브(carbon nano tube, CNT) 발열체를 사용하여 가열장치를 구비한 X선 발생장치용 부착형 촬영대의 고안 및 설계를 하고자 한다. 고안된 제품의 구성은 부착형 탄소발열체 촬영대로서 기존 X선 촬영대, 탄소나노튜브 면상발열체, 전극 선, 난연 처방된 보호필름과 바닥필름으로 구성되어 있다. 본 고안 제품의 특징과 장점은 냉기(冷氣)를 느끼는 촬영대 에서 환의를 착용하고 검사를 받는 환자에게 온화한 느낌과 안전감을 제공하고 심적인 불안감을 해소하여 검사에 도움 을 줄 수 있기 때문에 임상 적용을 적극 권장하는 바이다. The purpose of this study is to warm up the conventional X-ray table by inventing and design for X-ray table with an attached heating device using less unloaded X-ray, CNT (carbon nano tube) heating element. Configuration of the product design for adhesive carbon heating element X-ray is composed of a conventional X-ray table, carbon nano tube planar heating element, an electrode line, flame resisting protective film, and the bottom film. Characteristics and advantages of this invented product is to provide gentle feeling, the sense of security, and eliminating anxiety to the patient wearing a patient gown and feel the cool air while receiving the test. Thus we are strongly recommend to use this device in the clinical situation.

CT 영상을 이용한 대퇴체부 휨의 3차원적 곡률 분석

송종남,김응곤 한국방사선학회 2015 한국방사선학회 논문지 Vol.9 No.3

본 연구의 목적은 기존에 사용 중인 X선 발생장치의 촬영대를 따뜻하게 가열하면서도 X선 감약이 적은 탄소나노튜 브(carbon nano tube, CNT) 발열체를 사용하여 가열장치를 구비한 X선 발생장치용 부착형 촬영대의 고안 및 설계를 하고자 한다. 고안된 제품의 구성은 부착형 탄소발열체 촬영대로서 기존 X선 촬영대, 탄소나노튜브 면상발열체, 전극 선, 난연 처방된 보호필름과 바닥필름으로 구성되어 있다. 본 고안 제품의 특징과 장점은 냉기(冷氣)를 느끼는 촬영대 에서 환의를 착용하고 검사를 받는 환자에게 온화한 느낌과 안전감을 제공하고 심적인 불안감을 해소하여 검사에 도움 을 줄 수 있기 때문에 임상 적용을 적극 권장하는 바이다. The purpose of this study is to warm up the conventional X-ray table by inventing and design for X-ray table with an attached heating device using less unloaded X-ray, CNT (carbon nano tube) heating element. Configuration of the product design for adhesive carbon heating element X-ray is composed of a conventional X-ray table, carbon nano tube planar heating element, an electrode line, flame resisting protective film, and the bottom film. Characteristics and advantages of this invented product is to provide gentle feeling, the sense of security, and eliminating anxiety to the patient wearing a patient gown and feel the cool air while receiving the test. Thus we are strongly recommend to use this device in the clinical situation.

단순 방사선 영상 검사를 통한 추나의학적 진단 방법 - 척추.골반변위 명명체계를 중심으로 -

이진현,김창곤,조동찬,문수정,박태용,고연석,남항우,이정한,Lee, Jin-Hyun,Kim, Chang-Gon,Jo, Dong-Chan,Moon, Su-Jeong,Park, Tae-Young,Ko, Youn-Suk,Nam, Hang-Woo,Lee, Jung-Han 척추신경추나의학회 2014 척추신경추나의학회지 Vol.9 No.1

Objective : The purpose of this study is to offer a new approach to diagnostic X-ray in perspective of Chuna manual medicine for clinical application. Methods : Characteristics of each malposition in X-ray were analyzed comprehensively, based on the listing system. By verifying these results, find out the methods of X-ray diagnosis according to the each malposition. Results : 1. Vertebral malposition can be explained by alignment and relative position of vertebral body in the X-ray. To obtain more accurate estimation of subluxation, features of other structures should be considered, such as spinous process, intervertebral foramen and disc space. 2. Pelvic malposition can be determined by relative location of anterior superior iliac spine (ASIS) and posterior superior iliac spine (PSIS) in the X-ray. Also other pelvic parameters should be utilized to make a diagnosis of sacral malposition. Conclusions : Diagnostic X-ray should be applied to many clinicians for reasonable Chuna manual medicine application. And further studies are needed to use the diagnostic X-ray in the perspective of Chuna manual medicine.

A Tuberculosis Detection Method Using Attention and Sparse R-CNN

Xuebin Xu,Jiada Zhang,Xiaorui Cheng,Longbin Lu,Yuqing Zhao,Zongyu Xu,Zhuangzhuang Gu 한국인터넷정보학회 2022 KSII Transactions on Internet and Information Syst Vol.16 No.7

To achieve accurate detection of tuberculosis (TB) areas in chest radiographs, we design a chest X-ray TB area detection algorithm. The algorithm consists of two stages: the chest X-ray TB classification network (CXTCNet) and the chest X-ray TB area detection network (CXTDNet). CXTCNet is used to judge the presence or absence of TB areas in chest X-ray images, thereby excluding the influence of other lung diseases on the detection of TB areas. It can reduce false positives in the detection network and improve the accuracy of detection results. In CXTCNet, we propose a channel attention mechanism (CAM) module and combine it with DenseNet. This module enables the network to learn more spatial and channel features information about chest X-ray images, thereby improving network performance. CXTDNet is a design based on a sparse object detection algorithm (Sparse R-CNN). A group of fixed learnable proposal boxes and learnable proposal features are using for classification and location. The predictions of the algorithm are output directly without non-maximal suppression post-processing. Furthermore, we use CLAHE to reduce image noise and improve image quality for data preprocessing. Experiments on dataset TBX11K show that the accuracy of the proposed CXTCNet is up to 99.10%, which is better than most current TB classification algorithms. Finally, our proposed chest X-ray TB detection algorithm could achieve AP of 45.35% and AP50 of 74.20%. We also establish a chest X-ray TB dataset with 304 sheets. And experiments on this dataset showed that the accuracy of the diagnosis was comparable to that of radiologists. We hope that our proposed algorithm and established dataset will advance the field of TB detection.

학습률 적용에 따른 흉부영상 폐렴 유무 분류 비교평가

김지율,예수영 한국방사선학회 2022 한국방사선학회 논문지 Vol.16 No.5

This study tried to suggest the most efficient learning rate for accurate and efficient automatic diagnosis of medical images for chest X-ray pneumonia images using deep learning. After setting the learning rates to 0.1, 0.01, 0.001, and 0.0001 in the Inception V3 deep learning model, respectively, deep learning modeling was performed three times. And the average accuracy and loss function value of verification modeling, and the metric of test modeling were set as performance evaluation indicators, and the performance was compared and evaluated with the average value of three times of the results obtained as a result of performing deep learning modeling. As a result of performance evaluation for deep learning verification modeling performance evaluation and test modeling metric, modeling with a learning rate of 0.001 showed the highest accuracy and excellent performance. For this reason, in this paper, it is recommended to apply a learning rate of 0.001 when classifying the presence or absence of pneumonia on chest X-ray images using a deep learning model. In addition, it was judged that when deep learning modeling through the application of the learning rate presented in this paper could play an auxiliary role in the classification of the presence or absence of pneumonia on chest X-ray images. In the future, if the study of classification for diagnosis and classification of pneumonia using deep learning continues, the contents of this thesis research can be used as basic data, and furthermore, it is expected that it will be helpful in selecting an efficient learning rate in classifying medical images using artificial intelligence. 본 연구는 딥러닝을 이용한 흉부 X선 폐렴 영상에 대하여 정확하고 효율적인 의료영상의 자동진단을 위해서 가장 효율적인 학습률을 제시하고자 하였다. Inception V3 딥러닝 모델에 학습률을 0.1, 0.01, 0.001, 0.0001로 각각 설정한 후 3회 딥러닝 모델링을 수행하였다. 그리고 검증 모델링의 평균 정확도 및 손실 함수 값, Test 모델링의 Metric을 성능평가 지표로 설정하여 딥러닝 모델링의 수행 결과로 획득한 결과값의 3회 평균값으로 성능을 비교 평가하였다. 딥러닝 검증 모델링 성능평가 및 Test 모델링 Metric에 대한 성능평가의 결과, 학습률 0.001을 적용한 모델링이 가장 높은 정확도와 우수한 성능을 나타내었다. 이러한 이유로 본 논문에서는 딥러닝 모델을 이용한 흉부 X선 영상에 대한 폐렴 유무 분류 시 학습률을 0.001로 적용할 것을 권고한다. 그리고 본 논문에서 제시하는 학습률의 적용을 통한 딥러닝 모델링 시 흉부 X선 영상에 대한 폐렴 유무 분류에 대한 인력의 보조적인 역할을 수행할 수 있을 거라고 판단하였다. 향후 딥러닝을 이용한 폐렴 유무 진단 분류 연구가 계속해서 진행될 시, 본 논문의 논문 연구 내용은 기초자료로 활용될 수 있다고 여겨지며 나아가 인공지능을 활용한 의료영상 분류에 있어 효율적인 학습률 선택에 도움이 될 것으로 기대된다.

자동화 시각 진단용 X-선 요척골 영상 추출 알고리즘

최종호(Jong-Ho Choi) 한국정보기술학회 2013 한국정보기술학회논문지 Vol.11 No.11

The wrist disease diagnosis using conventional X-ray images has been widely used for the diagnosis relating to the fracture, triangular fibrocartilage complex(TFCC), and bone mineral density in radius-ulna. The automated visual diagnosis algorithm of wrist disease has been variously proposed in the field of medical images. However, the algorithm that can extract the radius-ulna regions from X-ray images has not been proposed yet. The automated diagnosis algorithm has to be applied after the manual region-extraction by the experts. In this paper, we propose the algorithm that can automatically extract the radius-ulna regions from X-ray images. Through the experiments using clinical X-ray images, we demonstrate the efficiency of the proposed radius-ulna extraction algorithm. This proposed algorithm has an advantage that can be applied to various medical imaging systems of orthopedics.

화상인식과 X선 영상에의 응용에 관한 연구

Song, Chae-Uk,Yea, Byeong-Deok 한국정보통신학회 2001 한국정보통신학회논문지 Vol.5 No.4

본 연구는 디지털 화상처리기술의 대표적인 응용분야로서 주목받고 있는 X선 사진을 대상으로 한 계산기 지원진단에 관한 연구의 일종으로서, 폐의 중요한 질환중 하나인 폐기종의 진단을 지원하는 계산기 시스템에 관한 연구이다. 구체적인 내용으로서는 흉부X선 사진으로부터 말초혈관을 자동추출하고, 추출된 혈관을 토대로 여러가지의 특징량을 구하여, 최종적으로 폐기종의 병세진행도를 정량평가하는 시스템에 관한 연구이다. 혈관 도형을 추출하여 병의 진행 정도를 정량적으로 평가하기 위해 본 연구에서 제안한 평가방법을 10장의 X선 사진에 설정된 189개의 관심영역에 적용하여, 의사의 평가치와 본 연구의 제안방법에 의한 평가치를 비교·검토함으로써 그 유효성을 검증하였다. In this study, we propose a method for quantifying the degree of advance of pulmonary emphysema by using chest X-ray images. With this method, we devise two schemes for this purpose. One is for detecting blood vessels by using a deformable model with the tree-like structure and using an evaluation function specialized by knowledge about blood vessels appeared in chest X-ray images, and the other is for quantifying the degree of advance by using several features, which were extracted from blood vessels, and the equation of quantitative evaluation. In order to evaluate the performance, we applied the proposed method to 189 ROIs(Regions of Interest) of ten chest X-ray images and compared the values by the proposed method with those by a medical doctor.

추나치료에 적용된 골반변위 진단법에 대한 체계적 문헌고찰

이준석 ( Jun-seok Lee ),박경원 ( Kyeong-won Park ),김현태 ( Hyun-tae Kim ),박선영 ( Sun-young Park ),신병철 ( Byung-cheul Shin ) 한방재활의학과학회 2022 한방재활의학과학회지 Vol.32 No.2

Objectives This systematic review aimed to analyze research about pelvic deviation diagnosis for Chuna manual therapy (CMT) and to review the diagnosis methods, indices, and results of diagnosis. Methods Ten electronic databases were systematically searched up to January 4th 2022. Clinical studies and reviews containing pelvic deviation diagnosis for CMT or using CMT as a treatment of pelvic deviation were selected and evaluated. CMT diagnosis in clinical studies and reviews were isolated and analyzed by 2 independent reviewers. Results Thirteen clinical studies and three reviews were included in the evaluation. X-ray analysis and manual testing were the two main methods used in CMT diagnosis of pelvic deviation. For manual testing in clinical studies, leg length insufficiency testing was the most frequently used measurement index and the most common diagnostic results were anterior and posterior rotation. In the X-ray analysis, Obturator foramen and femur head line were the most frequently used measurement index and the most common diagnostic results were anterior rotation and posterior rotation. Conclusions The systematic review found that manual testing and X-ray analysis were mainly used for the diagnosis of pelvic deviation in CMT among clincial and review articles. As there was little research about diagnosing pelvic deviation in CMT and any existing research presented only low standards of evidence, further research should be updated with using a more standardized approach. (J Korean Med Rehabil 2022; 32(2):83-94)

골밀도 검사의 실제: Dual-Energy X-ray Absorptiometry (DXA) 중심으로

김은희 ( Eun Heui Kim ),김인주 ( In Joo Kim ),전윤경 ( Yun Kyung Jeon ) 대한내과학회 2019 대한내과학회지 Vol.94 No.3

Dual-energy X-ray absorptiometry (DXA) is a widely used technology used to diagnosis osteoporosis and monitor changes in bone mineral density (BMD). The present paper reviews the clinical application of DXA in evaluating osteoporosis, including indications for BMD testing, interpretation of DXA results, diagnosis of osteoporosis, and serial BMD follow up. As the clinical utility of DXA depends on the quality of the scan acquisition, the precision assessment of DXA is also discussed. (Korean J Med 2019;94:268-272)

Pleural Effusion Diagnosis using Local Interpretable Model-agnostic Explanations and Convolutional Neural Network

Hai Thanh Nguyen,Cham Ngoc Thi Nguyen,Thao Minh Nguyen Phan,Tinh Cong Dao 대한전자공학회 2021 IEIE Transactions on Smart Processing & Computing Vol.10 No.2

The application of Artificial Intelligence (AI) in medicine has been a leading concern worldwide. Artificial intelligence-based systems not only support storing a large amount of data but also assist doctors in making a diagnosis. In addition, deep learning has obtained numerous achievements that greatly supported the development of image-based diagnostic methods. On the other hand, deep learning models still work as a black box that makes interpreting the output a challenge. Diagnosis based on images is currently a trend that plays a key role in clinical treatment by discovering abnormal regions for disease diagnosis. This paper proposes a computer-aid diagnosis system to support a pleural effusion diagnosis based on Chest X-ray (CXR) images. This study investigated several shallow convolutional neural network architectures that classify CXR images as well as the technique for processing imbalanced data using oversampling technology. The best model in the experiments was chosen to generate explanations using the Local Interpretable Model-agnostic Explanations (LIME) to support providing signals for pleural effusion diagnosis. The proposed method is expected to provide more informative CXR images of the pleural effusion diagnosis process.