• The Korean Journal of Health Service Management
• /
• v.7 no.1
• /
• pp.107-118
• /
• 2013

The purpose of this study is to grasp the image of radiologists perceived by college students of radiology. The survey subjects of this study were selected college students with major in radiology with 3-year system who are attending universities where are located in Daegu and Gyeongbuk area. As for distribution and collection of questionnaire, the objective of research was explained from April 2, 2012 to April 30. 220 people's questionnaires were finally analyzed with a self-administrative method after being widely distributed. Statistical analysis was carried out frequency analysis, t-test, ANOVA, and correlation analysis. To examine factors of having influence upon the image of radiologists, the multiple regression analysis was carried out. As for survey subjects' general characteristics, gender was indicated to be 58.2% for men and 41.8% for women. School year accounted for 38.2% for freshman, 29.1% for sophomore, and 32.7% for junior. Age was the largest in under 21 years old with 43.6%. The next was in order of over 23 years old with 32.7% and 22 years old with 20%. As a result of research, the image of radiologists was being perceived positively. The radiologist was being recognized as a specialist who is sincere oneself and has strong responsibilities, does valuable and worthwhile work, and has the matured professional knowledge. However, the individual image of radiologists was a little negative. Accordingly, to promote the individual image of radiologists, a specific and positive strategy is needed for approaching people as the specialized job with autonomy and responsibility as well as radiologist oneself.

• Korean Journal of Radiology
• /
• v.22 no.6
• /
• pp.912-921
• /
• 2021

Objective: To compare the performance of the deep learning-based lesion detection algorithm (DLLD) in detecting liver metastasis with that of radiologists. Materials and Methods: This clinical retrospective study used 4386-slice computed tomography (CT) images and labels from a training cohort (502 patients with colorectal cancer [CRC] from November 2005 to December 2010) to train the DLLD for detecting liver metastasis, and used CT images of a validation cohort (40 patients with 99 liver metastatic lesions and 45 patients without liver metastasis from January 2011 to December 2011) for comparing the performance of the DLLD with that of readers (three abdominal radiologists and three radiology residents). For per-lesion binary classification, the sensitivity and false positives per patient were measured. Results: A total of 85 patients with CRC were included in the validation cohort. In the comparison based on per-lesion binary classification, the sensitivity of DLLD (81.82%, [81/99]) was comparable to that of abdominal radiologists (80.81%, p = 0.80) and radiology residents (79.46%, p = 0.57). However, the false positives per patient with DLLD (1.330) was higher than that of abdominal radiologists (0.357, p < 0.001) and radiology residents (0.667, p < 0.001). Conclusion: DLLD showed a sensitivity comparable to that of radiologists when detecting liver metastasis in patients initially diagnosed with CRC. However, the false positives of DLLD were higher than those of radiologists. Therefore, DLLD could serve as an assistant tool for detecting liver metastasis instead of a standalone diagnostic tool.

• Journal of Digital Contents Society
• /
• v.13 no.3
• /
• pp.421-429
• /
• 2012

Lately, the number of interventional radiology is increased by the extension of procedure in medical radiation, and radiation exposure may be appeared differently by interventional radiologists, it is caused increase of radiation dose for radiation worker, patient, and radiologists. This study has done a comparative analysis characteristic of radiation exposure for five radiologists who executed interventional cardiology for 303 patients in S university hospital of Gyeong-Buk from Nov. 1, 2011 to Jan. 31, 2011. The average exposure time of five radiologists was 697.95sec. The average of cumulative DAP(exp) for patients was $52,730mGycm^2$ and the average of total DAP for patients was $104,875.14mGycm^2$. The average of frames for image was 855.52 frames in acquired images, and the average of frames for images was 802.2 frames in exposure images. They were statistically significant differences (p<0.05). Exposure time, cumulative DAP(fluro), cumulative DAP(exp), total DAP, acquired image, and exposure image were high correlation except cumulative DAP(exp), and acquired runs in x-ray exposure characteristics of machine. Exposure time was a great influence on radiologist. It signified that the more exposure time lead to the more radiation dose for radiologist. Radiation dose is related to ability, experience, difficulty, and precision of procedures in interventional procedure. The number of angiography and exposure time is difficult to control by radiologists. Therefore, it is in need of reasonable system which was evaluated the real dose of medical teams in interventional proceedings. We think that self education and training are required to reduce radiation dose for radiologists and radiation workers.

• Imaging Science in Dentistry
• /
• v.51 no.2
• /
• pp.129-136
• /
• 2021

Purpose: This study investigated the effects of 1 year of training on imaging diagnosis, using static ultrasonography (US) salivary gland images of Sjögren syndrome patients. Materials and Methods: This study involved 3 inexperienced radiologists with different levels of experience, who received training 1 or 2 days a week under the supervision of experienced radiologists. The training program included collecting patient histories and performing physical and imaging examinations for various maxillofacial diseases. The 3 radiologists (observers A, B, and C) evaluated 400 static US images of salivary glands twice at a 1-year interval. To compare their performance, 2 experienced radiologists evaluated the same images. Diagnostic performance was compared between the 2 evaluations using the area under the receiver operating characteristic curve (AUC). Results: Observer A, who was participating in the training program for the second year, exhibited no significant difference in AUC between the first and second evaluations, with results consistently comparable to those of experienced radiologists. After 1 year of training, observer B showed significantly higher AUCs than before training. The diagnostic performance of observer B reached the level of experienced radiologists for parotid gland assessment, but differed for submandibular gland assessment. For observer C, who did not complete the training, there was no significant difference in the AUC between the first and second evaluations, both of which showed significant differences from those of the experienced radiologists. Conclusion: These preliminary results suggest that the training program effectively helped inexperienced radiologists reach the level of experienced radiologists for US examinations.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
• /
• v.29 no.1
• /
• pp.261-274
• /
• 1999

Objectives: The purpose of this study was to evaluate the optimal distance and angle of observers by modulation transfer functions(MTFs) and receiver operating characteristics(ROCs), Material and Methods: Digital periapical radiograms were taken from 43 patients who have dental diseases(19 patients : dental caries. 12 patients : periapical lesions, 12 patients : periodontal diseases). Segmental images(4×4cm) were evaluated by 4 MTFs and ROC analysis. Results: The optimal distance(magnification) using MTF by Mannos & Sakrison was 12.97. and those by Nill. Ngan and Rao were 8.39, 4.78. 5.84 respectively. The optimal distance obtained from 4 radiologists by ROC analysis was 32cm(Az value: 0.89). and it was 40cm(Az value: 0.78) from 4 non-radiologists. There were significant differences of Az values between 4 radiologists and 4 non-radiologists at 24. 32 and 40cm (P<0.05). No significant differences of optimal distances were observed using 4 MTFs among +20, +10, 0, -10, -20 degrees(P>0.05). The optimal angle obtained from 4 radiologists by ROC analysis was +20 degree(Az value: 0.91). and no significant differences of Az values were observed among +20, +10, 0, -10 and -20 degrees(P>0.05). The optimal angle obtained from 4 non-radiologists by ROC analysis was 0 degree(Az value : 0.81). and no significant differences of Az values were observed among +20, +10, 0, -10 and -20 degrees(P>0.05). And there was significant difference of Az value between 4 radiologists and 4 non-radiologists at +20 degree(P<0.05). but no significant differences of Az values were observed among +10, 0, -10 and -20 degrees(P>0.05).

• Journal of Biomedical Engineering Research
• /
• v.26 no.6
• /
• pp.407-412
• /
• 2005

Convenience is one of the most important factors in medical image segmentation. Convenience is defined by compiling opinions from radiologists, and can be described as controllable maximum automation on the condition of producing only accurate results. The components of convenience are inclusive automation and inclusive modification. Inclusive modification consists of verify-and-confirm, undo-redo, exchange of segmentation methods, and intelligent modification tools. Inclusive automation is composed of automatic selection of a method, automatic selection of a confident segment, and automated chores. The convenient segmentation tool has been developed to segment X-ray images for orthopedic surgery, and has received an excellent evaluation from radiologists.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.3
• /
• pp.678-700
• /
• 2023

Diagnosing breast diseases using ultrasound (US) images remains challenging because it is time-consuming and requires expert radiologist knowledge. As a result, the diagnostic performance is significantly biased. To assist radiologists in this process, computer-aided diagnosis (CAD) systems have been developed and used in practice. This type of system is used not only to assist radiologists in examining breast ultrasound images (BUS) but also to ensure the effectiveness of the diagnostic process. In this study, we propose a new approach for breast lesion localization and segmentation using a multi-scale pyramid of the ultrasound image of a breast organ and a convolutional semantic segmentation network. Unlike previous studies that used only a deep detection/segmentation neural network on a single breast ultrasound image, we propose to use multiple images generated from an input image at different scales for the localization and segmentation process. By combining the localization/segmentation results obtained from the input image at different scales, the system performance was enhanced compared with that of the previous studies. The experimental results with two public datasets confirmed the effectiveness of the proposed approach by producing superior localization/segmentation results compared with those obtained in previous studies.

• Journal of Korean Neurosurgical Society
• /
• v.63 no.3
• /
• pp.386-396
• /
• 2020

Objective : To generate synthetic spine magnetic resonance (MR) images from spine computed tomography (CT) using generative adversarial networks (GANs), as well as to determine the similarities between synthesized and real MR images. Methods : GANs were trained to transform spine CT image slices into spine magnetic resonance T2 weighted (MRT2) axial image slices by combining adversarial loss and voxel-wise loss. Experiments were performed using 280 pairs of lumbar spine CT scans and MRT2 images. The MRT2 images were then synthesized from 15 other spine CT scans. To evaluate whether the synthetic MR images were realistic, two radiologists, two spine surgeons, and two residents blindly classified the real and synthetic MRT2 images. Two experienced radiologists then evaluated the similarities between subdivisions of the real and synthetic MRT2 images. Quantitative analysis of the synthetic MRT2 images was performed using the mean absolute error (MAE) and peak signal-to-noise ratio (PSNR). Results : The mean overall similarity of the synthetic MRT2 images evaluated by radiologists was 80.2%. In the blind classification of the real MRT2 images, the failure rate ranged from 0% to 40%. The MAE value of each image ranged from 13.75 to 34.24 pixels (mean, 21.19 pixels), and the PSNR of each image ranged from 61.96 to 68.16 dB (mean, 64.92 dB). Conclusion : This was the first study to apply GANs to synthesize spine MR images from CT images. Despite the small dataset of 280 pairs, the synthetic MR images were relatively well implemented. Synthesis of medical images using GANs is a new paradigm of artificial intelligence application in medical imaging. We expect that synthesis of MR images from spine CT images using GANs will improve the diagnostic usefulness of CT. To better inform the clinical applications of this technique, further studies are needed involving a large dataset, a variety of pathologies, and other MR sequence of the lumbar spine.

• Imaging Science in Dentistry
• /
• v.44 no.1
• /
• pp.31-35
• /
• 2014

Purpose: This study was performed to investigate the effect of image enhancement of periapical radiographs according to the diagnostic task. Materials and Methods: Eighty digital intraoral radiographs were obtained from patients and classified into four groups according to the diagnostic tasks of dental caries, periodontal diseases, periapical lesions, and endodontic files. All images were enhanced differently by using five processing techniques. Three radiologists blindly compared the subjective image quality of the original images and the processed images using a 5-point scale. Results: There were significant differences between the image quality of the processed images and that of the original images (P< 0.01) in all the diagnostic task groups. Processing techniques showed significantly different efficacy according to the diagnostic task (P< 0.01). Conclusion: Image enhancement affects the image quality differently depending on the diagnostic task. And the use of optimal parameters is important for each diagnostic task.

• 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.