• Journal of information and communication convergence engineering
• /
• v.6 no.4
• /
• pp.425-429
• /
• 2008

We investigated algorithm to detect and characterize interstitial lung abnormalities seen at chest radiographs. This method includes a process of 4 directional Laplaction-Gaussian filtering, and a process of linear opacity judgment. Two regions of interest (ROIs) were selected in each right lung of patients, and these ROIs were processed by our computer-analyzing system. For quantitative analysis of interstitial opacities, the radiographic index, which is the percentage of opacity areas in a ROI, was obtained and evaluated in the images. From or result, abnormal lungs were well differentiated from normal lungs. In our algorithm, the processing results were not only given as the numeric data named "radiographic index" but also confirmed with radiologists observation on CRT. The approach, by which the interstitial abnormalities themselves are extracted, is good enough because the results can be confirmed by the observations of radiologists. In conclusion, our system is useful for the detection and characterization of interstitial lung abnormalities.

• Pediatric Gastroenterology, Hepatology & Nutrition
• /
• v.8 no.2
• /
• pp.243-246
• /
• 2005

Pleural effusion represents a rare complication of acute hepatitis A infection. Twelve year-old girl was admitted with complaints of general weakness, nausea and icteric sclerae. She also complained of right chest pain. Right decubitus view of chest radiograph showed pleural fluid accumulation. Laboratory findings were as follows: AST/ALT 1692/1970 IU/L, total/direct bilirubin 4.48/3.66 mg/dL and HA IgM Ab (+). On the seventh day of hospitalization, her general condition was much improved and chest radiography showed resolved pleural effusion.

• Proceedings of the IEEK Conference
• /
• 2002.06d
• /
• pp.335-338
• /
• 2002

This paper proposes some technical approaches for automatic detection of pulmonary nodules in chest X-ray images. We applied threshold technique for the lung field segmentation and extended the lung field by using morphological methods. A template matching technique was employed for automatic detecting nodules in lung area. Genetic algorithm(GA) was used in template matching(TM) to select a matched image from various reference patterns(simulated typical nodules). We eliminated the false-positive candidates by using histograms and contrasts. We used standard databases published by Japanese Society of Radiological Technology (JSRT) for correct results. Also we employ two-dimensional Gaussian distribution for some reference images because the shadow of lung nodules in radiogram generally shows the distributions. Nodules of about 89% were correctly detected by our scheme. The simulation results show that it is an effective method to indicate lesions on chest radiograms.

• Tuberculosis and Respiratory Diseases
• /
• v.78 no.4
• /
• pp.356-359
• /
• 2015

Pneumothorax is an extremely rare complication of non-tuberculous mycobacterial infection. A 52-year-old man presenting with difficulty breathing and chest pain was admitted to our hospital. A right-sided pneumothorax was observed on chest radiography and chest computed tomography showed multiple cavitating and non-cavitating nodules with consolidation in the upper to middle lung zones bilaterally. Serial sputum cultures were positive for Mycobacterium kansasii, and he was diagnosed with pulmonary M. kansasii disease complicated by tension pneumothorax. After initiation of treatment including decortications and pleurodesis, the patient made a full recovery. We herein describe this patient's course in detail and review the current relevant literature.

• Journal of radiological science and technology
• /
• v.4 no.1
• /
• pp.23-30
• /
• 1981

In chest x-ray radiography, intensifying screen is used to the exposed dose of patients. Recently, newer materials-rere earth elements-are used in intensifying screen. Authors studied the aspects of chest x-ray radiogram and obtained the results that rare earth element intensifying screen did not harm in detail and could reduce the exposed dose of patient by 1/24 and below.

• Korean Journal of Radiology
• /
• v.21 no.5
• /
• pp.511-525
• /
• 2020

Chest X-ray radiography and computed tomography, the two mainstay modalities in thoracic radiology, are under active investigation with deep learning technology, which has shown promising performance in various tasks, including detection, classification, segmentation, and image synthesis, outperforming conventional methods and suggesting its potential for clinical implementation. However, the implementation of deep learning in daily clinical practice is in its infancy and facing several challenges, such as its limited ability to explain the output results, uncertain benefits regarding patient outcomes, and incomplete integration in daily workflow. In this review article, we will introduce the potential clinical applications of deep learning technology in thoracic radiology and discuss several challenges for its implementation in daily clinical practice.

• Korean Journal of Radiology
• /
• v.24 no.6
• /
• pp.541-552
• /
• 2023

Objective: Detection of pneumoperitoneum using abdominal radiography, particularly in the supine position, is often challenging. This study aimed to develop and externally validate a deep learning model for the detection of pneumoperitoneum using supine and erect abdominal radiography. Materials and Methods: A model that can utilize "pneumoperitoneum" and "non-pneumoperitoneum" classes was developed through knowledge distillation. To train the proposed model with limited training data and weak labels, it was trained using a recently proposed semi-supervised learning method called distillation for self-supervised and self-train learning (DISTL), which leverages the Vision Transformer. The proposed model was first pre-trained with chest radiographs to utilize common knowledge between modalities, fine-tuned, and self-trained on labeled and unlabeled abdominal radiographs. The proposed model was trained using data from supine and erect abdominal radiographs. In total, 191212 chest radiographs (CheXpert data) were used for pre-training, and 5518 labeled and 16671 unlabeled abdominal radiographs were used for fine-tuning and self-supervised learning, respectively. The proposed model was internally validated on 389 abdominal radiographs and externally validated on 475 and 798 abdominal radiographs from the two institutions. We evaluated the performance in diagnosing pneumoperitoneum using the area under the receiver operating characteristic curve (AUC) and compared it with that of radiologists. Results: In the internal validation, the proposed model had an AUC, sensitivity, and specificity of 0.881, 85.4%, and 73.3% and 0.968, 91.1, and 95.0 for supine and erect positions, respectively. In the external validation at the two institutions, the AUCs were 0.835 and 0.852 for the supine position and 0.909 and 0.944 for the erect position. In the reader study, the readers' performances improved with the assistance of the proposed model. Conclusion: The proposed model trained with the DISTL method can accurately detect pneumoperitoneum on abdominal radiography in both the supine and erect positions.

• Korean Journal of Radiology
• /
• v.24 no.9
• /
• pp.890-902
• /
• 2023

Objective: The clinical impact of artificial intelligence-based computer-aided detection (AI-CAD) beyond diagnostic accuracy remains uncertain. We aimed to investigate the influence of the clinical implementation of AI-CAD for chest radiograph (CR) interpretation in daily practice on the rate of referral for chest computed tomography (CT). Materials and Methods: AI-CAD was implemented in clinical practice at the Seoul National University Hospital. CRs obtained from patients who visited the pulmonology outpatient clinics before (January-December 2019) and after (January-December 2020) implementation were included in this study. After implementation, the referring pulmonologist requested CRs with or without AI-CAD analysis. We conducted multivariable logistic regression analyses to evaluate the associations between using AI-CAD and the following study outcomes: the rate of chest CT referral, defined as request and actual acquisition of chest CT within 30 days after CR acquisition, and the CT referral rates separately for subsequent positive and negative CT results. Multivariable analyses included various covariates such as patient age and sex, time of CR acquisition (before versus after AI-CAD implementation), referring pulmonologist, nature of the CR examination (baseline versus follow-up examination), and radiology reports presence at the time of the pulmonology visit. Results: A total of 28546 CRs from 14565 patients (mean age: 67 years; 7130 males) and 25888 CRs from 12929 patients (mean age: 67 years; 6435 males) before and after AI-CAD implementation were included. The use of AI-CAD was independently associated with increased chest CT referrals (odds ratio [OR], 1.33; P = 0.008) and referrals with subsequent negative chest CT results (OR, 1.46; P = 0.005). Meanwhile, referrals with positive chest CT results were not significantly associated with AI-CAD use (OR, 1.08; P = 0.647). Conclusion: The use of AI-CAD for CR interpretation in pulmonology outpatients was independently associated with an increased frequency of overall referrals for chest CT scans and referrals with subsequent negative results.

• Journal of radiological science and technology
• /
• v.16 no.1
• /
• pp.57-65
• /
• 1993

Asymetric system have been introduced in these years by KODAK company nam of Insight system for the purpose of improve the chest image. We have had a problem of chest radiology that it is very difficult to visualize the lung field and modiastinal region at one shot. That's why we are the RT using the technique of high voltage hard quality radiography in chest radiography. Also it is known the c-type wide latitude film can lift up the density of mediastinal structures. Authors investigated the photographic characteristics and physical structure of Insight system. Method 1. Investigated the structure of Emulsion layer. Calculated the particle size of Insight system using SEM(Scanning Electron Microscope). 2. Photographic characteristics has been compared the Insight system with the ortho KM/MG combination in $60{\sim}120kV$ range. Results 1. The particle size of backside film were investigated about 2 times larger that of front side film. 2. The front and backscreen's thickness ratio was detected 1 : 3.87, that the backscreen's thickness was thicker than frontscreen. 3. At the view point of photographic characteristics the frontside of insight system make up the contrast, backside make up the density at low exposure lesion.

• The Journal of Churna Manual Medicine for Spine and Nerves
• /
• v.10 no.2
• /
• pp.27-35
• /
• 2015

Objectives: The purpose of this study is to discriminate the cough-induced rib fracture with chest pain occurred after chuna therapy. Methods: A 68-year-old female patient who is suffering from left chest wall pain with chronic cough was treated by Korean medical treatment and chuna therapy from November 11th 2014 to November 15th 2014. The improvement of the patient's pain was measured by 100 mm Visual Analog Scale (VAS). For diagnosis the rib fracture, we conducted the radiography, computed tomography (CT), and bone scan. Results: After treatment, pain intensity was decreased and the rib fracture was negative in radiography and CT. But, in bone scan, the 5th-8th rib fractures in left side were detected. Conclusions: When the patient with chest pain visit the hospital after chuna therapy, a doctor keep in mind the possibility of coughinduced rib fracture.