• Journal of the Korean Society of Radiology
• /
• v.16 no.5
• /
• pp.537-543
• /
• 2022

The purpose of this simulation study was to evaluate the possibility of pancreas detection through effective atomic number information using dual-energy computed tomography(CT). The effective atomic number of 10 tissue-equivalent materials were estimated through stoichiometric calibration. For stoichiometric calibration, HU values at low-energy (80 kV) and high-energy (140 kV) for 10 tissue-equivalent materials were used. Based on this method, the effective atomic number image of the tissue-equivalent material was extracted through an iterative algorithm. According to the results, the attenuation ratio in accordance with the effective atomic number was estimated to have an R² value of 0.9999, and the effective atomic number of Pancreas, Water, Liver, Blood, Spongiosa, and Cortical bone was overall within 1% accuracy compared to the theoretical value. Conventional pancreatic cancer examination uses a contrast medium, so there is a possibility of potential side effects of the contrast medium. In order to solve this problem, it is thought that it will be possible to contribute to an accurate and safe examination by extracting the effective atomic number using dual-energy CT without contrast enhancement. Based on this study, future research will be conducted on the detection of pancreatic cancer using the HU value of pancreatic cancer based on clinical images.

• Journal of the Korean Society of Radiology
• /
• v.16 no.6
• /
• pp.697-702
• /
• 2022

For imaging in positron emission tomography(PET), it is necessary to measure the position of the scintillation pixel interacting with the gamma rays incident on the detector. To this end, in the conventional system, a flood image of the scintillation pixel is obtained, the imaged area of each scintillation pixel is separated, and the position of the scintillation pixel is specified and acquired as a digital signal. In this study, a deep learning method was applied based on the signal formed by the photosensor of the detector, and a method was developed to directly acquire a digital signal without going through various procedures. DETECT2000 simulation was performed to verify this and evaluate the accuracy of position measurement. A detector was constructed using a 6 × 6 scintillation pixel array and a 4 × 4 photosensor, and a gamma ray event was generated at the center of the scintillation pixel and summed into four channels of signals through the Anger equation. After training the deep learning model using the acquired signal, the positions of gamma-ray events that occurred in different depth directions of the scintillation pixel were measured. The results showed accurate results at every scintillation pixel and position. When the method developed in this study is applied to the PET detector, it will be possible to measure the position of the scintillation pixel with a digital signal more conveniently.

• Journal of the Korean Society of Radiology
• /
• v.16 no.7
• /
• pp.851-856
• /
• 2022

The purpose of this study is to confirm the effect of reducing the surface dose around the radiation field in breast cancer radiotherapy using the Field-in-Field (FIF) technique. X-ray was exposed from a linear accelerator (Linac) was used for irradiation, and the surface dose was measured with a glass dosimeter. The source-to-surface distance (SSD) was 90 cm, the field size is 10 × 10 cm², and the X-ray energy was 6 MV and 10 MV, respectively. The surface dose of the FIF was compared with the dose measured in the physical wedge (PW) and dynamic wedge (DW). Wedge angles of 15° and 30° were used in the PW and DW, respectively. Surface dose was measured at 1 cm, 3 cm, and 5 cm from the center of the field size, respectively. According to the results, FIF showed lower surface dose compared to PW and DW regardless of the energy of the X-ray beam, wedge angle, and dose measurement point. Since FIF could reduce the radiation dose in periphery of the field size in breast cancer treatment, it is expected to be able to reduce the secondary damage caused by the radiation beam as well as to obtain a uniform dose distribution on the target.

• Journal of the Korean Society of Radiology
• /
• v.16 no.7
• /
• pp.961-968
• /
• 2022

Rotator cuff tears are a leading cause of shoulder pain in adults. Due to the increase in social activities, the number of patients complaining of shoulder pain is increasing, and interest in shoulder diseases is also increasing. With the development of ultrasound equipment, the sensitivity and specificity of diagnosis are high, and it is used to diagnose rotator cuff tears in musculoskeletal disease. Ultrasound is recognized as a complementary method to MRI examination in rotator cuff tears. Therefore, this study aimed to find out the diagnostic usefulness of ultrasound and MRI examinations in the diagnosis of shoulder rotator cuff tears.A retrospective analysis was performed on 262 patients who were diagnosed with final rotator cuff damage by arthroscopy after completing ultrasound and MRI examinations. Sensitivity, feature, positive predictive value, image predictive value, and touch were disassembled for the test results. In addition, the degree of clavicular tear was scored and recorded in 5 stages. Ultrasound examination was similar to MRI examination results for both full-thickness and partial tears, and there was no statistically significant difference. Partial tear test results showed higher positive predictive value and accuracy than MRI test. In conclusion, ultrasound can be fully utilized as a screening test for rotator cuff disease, and it is thought that it will be selected and used clinically according to the patient's constitution and situation.

• Journal of the Korean Society of Radiology
• /
• v.16 no.6
• /
• pp.771-778
• /
• 2022

The purpose of this study is to present a method of measuring noise by the percentage of effective line attenuation coefficient of water that can be used for quality control of CT image noise using AAPM CT performance phantom in clinical practice. In the CT images obtained by scanning the AAPM CT performance phantom with a 120 kVp CT X-ray beam, the mean CT number was measured for each pin and water in the CT number linearity insert part. The effective energy was determined as the photon energy with the largest correlation coefficient from the correlation coefficients of the linear regression analysis of the measured mean CT number for each pin and water and the linear attenuation coefficient for each photon energy. And for water and acrylic, the contrast scale was calculated as 0.000188 cm^-1 · HU^-1 from the measured mean CT number and effective line attenuation coefficient. Using the calculated contrast scale, the effective line attenuation coefficient of water, and the standard deviation measured in the water of the alignment pin part of the AAPM CT performance phantom, The noise measurement value by the percentage of effective line attenuation coefficient of water obtained 0.31 ~ 0.52% in the range of 100 ~ 300 mAs.

• Journal of the Korean Society of Radiology
• /
• v.16 no.1
• /
• pp.25-34
• /
• 2022

Brain computed tomography (CT) is useful for brain lesion diagnosis, such as brain hemorrhage, due to non-invasive methodology, 3-dimensional image provision, low radiation dose. However, there has been numerous misdiagnosis owing to a lack of radiologist and heavy workload. Recently, object detection technologies based on artificial intelligence have been developed in order to overcome the limitations of traditional diagnosis. In this study, the applicability of a deep learning-based YOLOv5s model was evaluated for brain hemorrhage detection using brain CT images. Also, the effect of hyperparameters in the trained YOLOv5s model was analyzed. The YOLOv5s model consisted of backbone, neck and output modules. The trained model was able to detect a region of brain hemorrhage and provide the information of the region. The YOLOv5s model was trained with various activation functions, optimizer functions, loss functions and epochs, and the performance of the trained model was evaluated in terms of brain hemorrhage detection accuracy and training time. The results showed that the trained YOLOv5s model is able to provide a bounding box for a region of brain hemorrhage and the accuracy of the corresponding box. The performance of the YOLOv5s model was improved by using the mish activation function, the stochastic gradient descent (SGD) optimizer function and the completed intersection over union (CIoU) loss function. Also, the accuracy and training time of the YOLOv5s model increased with the number of epochs. Therefore, the YOLOv5s model is suitable for brain hemorrhage detection using brain CT images, and the performance of the model can be maximized by using appropriate hyperparameters.

• Journal of the Korean Society of Radiology
• /
• v.17 no.2
• /
• pp.191-199
• /
• 2023

This study aimed to propose minimized radiation doses with an optimized abdomen x-ray image, which realizes a Deep Blind Image Super-Resolution Generative adversarial network (BSRGAN) technique. Entrance surface doses (ESD) measured were collected by changing exposure conditions. In the identical exposures, abdominal images were acquired and were processed with the BSRGAN. The images reconstructed by the BSRGAN were compared to a reference image with 80 kVp and 320 mA, which was evaluated by mean squared error (MSE), peak signal-to-noise ratio (PSNR), and structural similarity index measure (SSIM). In addition, signal profile analysis was employed to validate the effect of the images reconstructed by the BSRGAN. The exposure conditions with the lowest MSE (about 0.285) were shown in 90 kVp, 125 mA and 100 kVp, 100 mA, which decreased the ESD in about 52 to 53% reduction), exhibiting PSNR = 37.694 and SSIM = 0.999. The signal intensity variations in the optimized conditions rather decreased than that of the reference image. This means that the optimized exposure conditions would obtain reasonable image quality with a substantial decrease of the radiation dose, indicating it could sufficiently reflect the concept of As Low As Reasonably Achievable (ALARA) as the principle of radiation protection.

• Journal of the Korean Society of Radiology
• /
• v.17 no.2
• /
• pp.201-206
• /
• 2023

In order to improve the spatial resolution of the gamma camera, the size of the hole in the collimator must be reduced, so the sensitivity is reduced. In order to improve the sensitivity, the size of the hole must be increased, and thus the spatial resolution is reduced. In other words, spatial resolution and sensitivity show opposite characteristics. In this study, a gamma camera was designed to improve both spatial resolution and sensitivity. In order to obtain higher sensitivity in gamma cameras with the same spatial resolution, the structure of the scintillator was designed differently from the existing system. A scintillation pixel was used, and a partition wall was placed between the scintillation pixels to prevent incident gamma rays from being transmitted to other scintillation pixels to interact. Geant4 Application for Tomographic Emission (GATE) simulation was performed to evaluate the performance of the designed gamma camera. When the same sensitivity as the block-type scintillator was obtained, the spatial resolution increased by 16.5%, and when the same spatial resolution was obtained, the sensitivity increased by 61.5%. It is considered that the use of the gamma camera designed in this study can improve the sensitivity compared to the existing system while securing excellent spatial resolution.

• Journal of the Korean Society of Radiology
• /
• v.17 no.4
• /
• pp.515-521
• /
• 2023

The radiation dose received by the patient varies according to the tube current and time used during dental intraoral imaging. A large amount of tube current is required for image quality, but the radiation dose to the patient increases accordingly. Therefore, in this study, the optimal amount of tube current that can reduce the radiation dose received by the patient while securing the image quality was calculated through the evaluation of the image quality according to the tube current used during intraoral imaging through simulation. The average tube current, time, and tube voltage presented in the Guidelines for Diagnostic Reference Level for intraoral radiography were used as basic imaging conditions, and images were obtained when only the tube current was changed, and then the optimal tube current was compared and analyzed with the basic image quantity was calculated. Images were obtained by changing the tube current to 0.1, 0.5, 1, 2, 3, 4 and 5 mA under the basic conditions of 63 kV, 6 mA, and 0.29 s. The obtained image was evaluated for structural similarity index with the image taken under the condition of 6 mA using the ICY program. As a result, even under the condition of 0.5 mA tube current, the index of structural similarity with the image of 6 mA was evaluated to be high. Based on these results, it is considered that the radiation dose given to the patient can be greatly reduced if imaging is performed at 0.5 mA instead of 6 mA during dental intraoral imaging.

• Journal of the Korean Society of Radiology
• /
• v.17 no.4
• /
• pp.523-529
• /
• 2023

In order to achieve excellent spatial resolution, very small scintillation pixels are used in detectors of positron emission tomography for small animals. However, by using these very small scintillation pixels, scintillation pixels at the edge of the array may overlap in a flood image. To solve this problem, a light guide capable of changing the distribution of light was used. Depending on the material of the light guide, the light spreading tendency is different, and accordingly, the presence or absence of overlapping is different depending on the material of the light guide used. In this study, instead of the conventional glass light guide, a detector using the same material as the scintillation pixel was designed. A scintillator light guide has a higher refractive index than a glass light guide, so the light spread is different. Flood images were acquired to evaluate the degree of separation of the scintillation pixels at the edge of the detector using the two light guides. The degree of separation was evaluated by calculating the distance between the center and the spatial resolution of the image of two scintillation pixels at the edge of the obtained flood image. As a result, when the scintillator light guide was used, better spatial resolution was shown, and the distance between centers of scintillation pixels was wider. When a detector is constructed using a scintillator light guide instead of a conventional glass light guide, it is possible to use a smaller scintillation pixel, thereby securing better spatial resolution.