• Korean Journal of Artificial Intelligence
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• v.9 no.2
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• pp.1-5
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• 2021

Although CT has an advantage in describing the three-dimensional anatomical structure of the human body, it also has a disadvantage in that high doses are exposed to the patient. Recently, a deep learning-based image reconstruction method has been used to reduce patient dose. The purpose of this study is to analyze the dose reduction and image quality improvement of deep learning-based reconstruction (DLR) on the adult's chest CT examination. Adult lung phantom was used for image acquisition and analysis. Lung phantom was scanned at ultra-low-dose (ULD), low-dose (LD), and standard dose (SD) modes, and images were reconstructed using FBP (Filtered back projection), IR (Iterative reconstruction), DLR (Deep learning reconstruction) algorithms. Image quality variations with respect to varying imaging doses were evaluated using noise and SNR. At ULD mode, the noise of the DLR image was reduced by 62.42% compared to the FBP image, and at SD mode, the SNR of the DLR image was increased by 159.60% compared to the SNR of the FBP image. Based on this study, it is anticipated that the DLR will not only substantially reduce the chest CT dose but also drastic improvement of the image quality.

• Journal of the Korean Society of Radiology
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• v.5 no.5
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• pp.255-260
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• 2011

We wanted to evaluate the usefulness of three-dimensional reconstructive images using computed tomography for rib fracture patients. The reconstruction used in clinical multi planar reformation(MPR), volume rendering technique(VRT), and image data using quantitative methods and qualitative methods were compared. Much more, the artifact shadow was minimized to reconstruct with 3D volumetric image by using an law data in the analysis of the reconstructive image and chest CT scan of the evaluation result fractures of the thoracic patient. And we could know that the fractures of the thoracic determination and three dimension volume image reconstruction time were reduced.

• Journal of Radiation Industry
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• v.11 no.3
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• pp.131-137
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• 2017

To compare the radiation dose and image noise of low dose computed tomography (CT) and high resolution CT using the fixed tube current technique and automatic tube current modulation (CARE Dose 4D). Chest CT and human anthropomorphic phantom were used the RPL (radiophotoluminescence) dosimeters. For image evaluation, standard deviation of mean CT attenuation coefficient and CT attenuation coefficient was measured using ROI analysis function. The effective dose was calculated using CTDIvol and DLP. CARE Dose 4D was reduced by 74.7% and HRCT by 64.4% compared to the fixed tube current technique in low dose CT of chest phantom. In CTDIvol and DLP, the dose of CARE Dose 4D was reduced by fixed tube current technique. For effective dose, CARE Dose 4D was reduced by 47% and HRCT by 46.9% compared to the fixed tube current method, and the dose of CARE Dose 4D was significantly different (p<.05). Noise in the image was higher than that in the fixed tube current technique. Noise difference in the image of CARE Dose 4D in low dose CT was significant (p<.05). The low radiation dose and the noise difference of the CARE Dose 4D were compared with the fixed tube current technique in low dose CT and HRCT using chest phantom. The radiation doses using CARE Dose 4D were in accordance with the national and international dose standards. CARE Dose 4D should be applied to low dose CT and HRCT for clinical examination.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.10
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• pp.2163-2170
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• 2009

We present an automated, energy minimized-based method for Lung parenchyma segmenting Chest Computed Tomography(CT) datasets. Deformable model is used for energy minimized segmentation. Quantitative knowledge including expected volume, shape of Chest CT provides more feature constrain to diagnosis or surgery operation planning. Segmentation subdivides an lung image into its consistent regions or objects. Depends on energy-minimizing, the level detail image of subdivision is carried. Segmentation should stop when the objects or region of interest in an application have been detected. The deformable model that has attracted the most attention to date is popularly known as snakes. Snakes or deformable contour models represent a special case of the general multidimensional deformable model theory. This is used extensively in computer vision and image processing applications, particularly to locate object boundaries, in the mean time a new type of external force for deformable models, called gradient vector flow(GVF) was introduced by Xu. Our proposed algorithm of deformable model is new external energy of GVF for exact segmentation. In this paper, Clinical material for experiments shows better results of proposal algorithm in Lung parenchyma segmentation on Chest CT.

• Journal of the Korean Society of Radiology
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• v.17 no.7
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• pp.1033-1039
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• 2023

Low-dose chest CT, which is used as a lung screening test, also includes information on coronary artery calcification within the scan range. The purpose of this study was to investigate the usefulness of determining coronary artery calcification using Low-dose chest CT. Those who underwent low-dose chest CT and coronary artery calcification score CT on the same day were eligible. Coronary artery calcium score CT results were divided into 4 groups (Low: 1〈CACS〈10, Mild: 10〈CACS〈100, Moderate: 100〈CACS〈400, High: 400〈CACS) by referring to the Coronary artery calcium score categories and risks. After selecting 30 people each group, five radiotechnologists with more than 15 years of experience in coronary artery calcium measurement retrospectively analyzed the presence or absence of coronary artery calcification in low-dose chest CT images. The results of the five observers' uniform interpretation of the low-dose chest CT image were consistent with the coronary artery calcium score CT results in Low group: 56%, Mild group: 96.6%, Moderate group: 100%, and High group: 100%. appeared. In the Low group, all 5 observers observed calcification in 17 out of 30 cases, and in 7 cases all 5 observers decided that calcification could not be identified. Coronary artery calcification could be observed in 100% of asymptomatic adults with a calcium score of 15 or higher in low-dose chest CT scans. The minimum calcium score that can be identified is 1, and it was found that even very small calcifications can be identified when the subject's body size is small or the scan is performed at a time when heart movement is minimal.

• Korean Journal of Digital Imaging in Medicine
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• v.17 no.1
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• pp.13-18
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• 2015

Purpose : Skip the repetitive HRCT axial scan in order to reduce the exposure of patients during chest HRCT scan, Helical Scan Data into a reconstructed image, and exposure of the patient change and visually evaluate the usefulness of the HRCT images. Materials and method : Patients were enrolled in the survey are 50 people who underwent chest CT scans of patients who presented to the hospital from January 2015 to March 2015. 50 people surveyed 22 people men and 28 people women people showed an average distribution of 30 to 80 years age was 48 years. 50 patients to Somatom Sensation 64 ch (Siemens) model with 120 kVp tube voltage to a reference mAs tube current to mAs (Care dose, Siemens) as a whole, including the lungs and the chest CT scan was performed. Scan upon each patient CARE dose 4D (Automatic exposure control, Siemens Medical Solution Erlangen, Germany) was to maintain the proper radiation dose scan every cross-section through a device that automatically adjusts the tube current of. CT scan is the rotation time of the Tube slice collimation, slice width 0.6 mm, pitch factor was made under the terms of 1.4. CT scan obtained after the raw data (raw data) to the upper surface of the axial images and coronal images for each slice thickness 1 mm, 5 mm intervals in the high spatial frequency calculation method (hight spatial resolution algorithm, B60 sharp) was the use of the lung window center -500 HU, windows were reconstructed into images in the interval -1000 HU to see. Result : 1. Measure the total value of DLP 50 patients who proceed to chest CT group A (Helical Scan after scan performed with HRCT) and group B (Helical Scan after the HR image reconstruction to the original data) compared with the group divided, analysis As a result of the age, but show little difference for each age group it had a decreased average dose of about 9%. 2. A Radiation read the results of the two Radiologist and a doctor upper lobe and middle lobe of the lung takes effect the visual evaluation is not a big difference between the two images both, depending on the age of the patient, especially if the blood vessels of the lower lobe (A: 3.4, B: 4.6) and bronchi(A: 3.8, B4.7) image shake caused by breathing in anxiety (blurring lead) to the original data (raw data) showed that the reconstructed image is been more useful in diagnostic terms. Conclusion : Scan was confirmed a continuous, rapid motion video to get Helical scan is much lower lobe lung reduction in visual blurring, Helical scan data to not repeat the examination by obtaining HRCT images reorganization reduced the exposure of the patient.

• Journal of Biomedical Engineering Research
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• v.10 no.3
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• pp.243-252
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• 1989

In this study, medical images, which are X-ray image and CT image, are compressed by the adam live coding technique. The medical images may be treated as special ones, because they are different from general images in many respects. The statistical characteristics that medical images only have in transform domain are analyzed, and then the improved quantization method is proposed for medical images. For chest X-ray image and CT head image, the better results are obtained by the improved adaptive coding technique.

• Journal of Korea Multimedia Society
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• v.16 no.6
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• pp.700-707
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• 2013

In this paper, we propose a non-rigid registration method of lung parenchyma in temporal chest CT scans using region binarization modeling and locally deformable model. To cope with intensity differences between CT scans, we segment the lung vessel and parenchyma in each scan and perform binarization modeling. Then, we match them without referring any intensity information. We globally align two lung surfaces. Then, locally deformable transformation model is developed for the subsequent non-rigid registration. Subtracted quantification results after non-rigid registration are visualized by pre-defined color map. Experimental results showed that proposed registration method correctly aligned lung parenchyma in the full inspiration and expiration CT images for ten patients. Our non-rigid lung registration method may be useful for the assessment of various lung diseases by providing intuitive color-coded information of quantification results about lung parenchyma.

• Journal of the Korean Society of Radiology
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• v.17 no.3
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• pp.297-303
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• 2023

Pediatric Computed Tomography (CT) examinations can often result in exam failures or the need for frequent retests due to the difficulty of cooperation from young patients. Deep Learning Image Reconstruction (DLIR) methods offer the potential to obtain diagnostically valuable images while reducing the retest rate in CT examinations of pediatric patients with high radiation sensitivity. In this study, we investigated the possibility of applying DLIR to reduce artifacts caused by respiration or motion and obtain clinically useful images in pediatric chest CT examinations. Retrospective analysis was conducted on chest CT examination data of 43 children under the age of 7 from P Hospital in Gyeongsangnam-do. The images reconstructed using Filtered Back Projection (FBP), Adaptive Statistical Iterative Reconstruction (ASIR-50), and the deep learning algorithm TrueFidelity-Middle (TF-M) were compared. Regions of interest (ROI) were drawn on the right ascending aorta (AA) and back muscle (BM) in contrast-enhanced chest images, and noise (standard deviation, SD) was measured using Hounsfield units (HU) in each image. Statistical analysis was performed using SPSS (ver. 22.0), analyzing the mean values of the three measurements with one-way analysis of variance (ANOVA). The results showed that the SD values for AA were FBP=25.65±3.75, ASIR-50=19.08±3.93, and TF-M=17.05±4.45 (F=66.72, p=0.00), while the SD values for BM were FBP=26.64±3.81, ASIR-50=19.19±3.37, and TF-M=19.87±4.25 (F=49.54, p=0.00). Post-hoc tests revealed significant differences among the three groups. DLIR using TF-M demonstrated significantly lower noise values compared to conventional reconstruction methods. Therefore, the application of the deep learning algorithm TrueFidelity-Middle (TF-M) is expected to be clinically valuable in pediatric chest CT examinations by reducing the degradation of image quality caused by respiration or motion.

• Journal of Radiation Protection and Research
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• v.35 no.4
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• pp.135-141
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• 2010

Purpose : The patients who visited this department for pulmonary disease and need CT scans for Follow-up to observe change of CT value, evaluation of image quality and decrease of radiation dose as change of kVp. Subjects and Methods : Subjects were the patients of 20 persons visited this department for pulmonary disease and Somatom Sensation 16(Semens, Enlarge, Germany) was used. Measurement of CT value as change of kVp was done by setting up ROI diameter of 1cm at the height of thyroid, aortic arch, right pulmonary artery in arterial phase image using 100 kVp, measuring 3 times, and recorded the average. CT value of phantom was measured by scanning phantoms which means contrast media diluted by normal saline by various ratio with tube voltage of 80 kVp, 100 kVp, 120 kVp, 140 kVp and recorded the average of 3 CT values of center of phantom image. In analysing radiation dose, CTDIVOL values of the latest arterial phase image of 120 kVp and as this research set that of 100 kVp were analyzed comparatively. 2 observers graded quality of chest images by 5 degrees (Unacceptable, Suboptimal, Adequate, Good, Excellent). Results : CT value of chest image increased at 100 kVp by 14.06%~27.26% in each ROI than 120 kVp. CT value of phantom increased as tube voltage lowered at various concentration of contrast media. CTDIVOL decreased at 100 kVp(5.00 mGy) by 36% than 120 kVp(7.80 mGy) in radiation dose analysis. here were 0 Unacceptable, 1 Suboptimal, 3 Adequate, 10 Good, 6 Excellent in totally 20 persons. Conclusion : Chest CT scanning with low kilo-voltage for patients who need CT scan repeatedly can bring images valuable for diagnose, and decrease radiation dose against patients.