• Clinical Psychopharmacology and Neuroscience
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• v.16 no.4
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• pp.449-460
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• 2018

Objective: Prior functional magnetic resonance imaging (fMRI) work has revealed that children/adolescents with disruptive behavior disorders (DBDs) show dysfunctional reward/non-reward processing of non-social reinforcements in the context of instrumental learning tasks. Neural responsiveness to social reinforcements during instrumental learning, despite the importance of this for socialization, has not yet been previously investigated. Methods: Twenty-nine healthy children/adolescents and 19 children/adolescents with DBDs performed the fMRI social/non-social reinforcement learning task. Participants responded to random fractal image stimuli and received social and non-social rewards/non-rewards according to their accuracy. Results: Children/adolescents with DBDs showed significantly reduced responses within the caudate and posterior cingulate cortex (PCC) to non-social (financial) rewards and social non-rewards (the distress of others). Connectivity analyses revealed that children/adolescents with DBDs have decreased positive functional connectivity between the ventral striatum (VST) and the ventromedial prefrontal cortex (vmPFC) seeds and the lateral frontal cortex in response to reward relative to non-reward, irrespective of its sociality. In addition, they showed decreased positive connectivity between the vmPFC seed and the amygdala in response to non-reward relative to reward. Conclusion: These data indicate compromised reinforcement processing of both non-social rewards and social non-rewards in children/adolescents with DBDs within core regions for instrumental learning and reinforcement-based decision-making (caudate and PCC). In addition, children/adolescents with DBDs show dysfunctional interactions between the VST, vmPFC, and lateral frontal cortex in response to rewarded instrumental actions potentially reflecting disruptions in attention to rewarded stimuli.

• Journal of Radiation Protection and Research
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• v.24 no.3
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• pp.161-170
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• 1999

System performances in terms of image quality between an amorphous silicon DR system and a conventional film-screen system were evaluated. Various aspects of image quality MTF (modulation transfer function), NPS (noise power spectrum), SNR(signal-to-noise ratio) and contrast were measured and calculated. The MTF of the DR system was comparable to the film-screen systems. The noise was mainly dominated by the quantum mottle in both systems and the electronic noise was found in the DR system. The contrast of the DR system was better than the film-screen systems by virtue of high sensitivity and image processing. Compared to the film-screen systems in general radiography, the DR system had similar resolution and showed better contrast with the same exposure condition after contrast manipulation. The results of this study provide some useful information about the performance of the DR system in connection with medical applications.

• Spatial Information Research
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• v.13 no.4 s.35
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• pp.345-354
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• 2005

Super resolution image reconstruction method refers to image processing algorithms that produce a high resolution(HR) image from observed several low resolution(LR) images of the same scene. This method has proven to be useful in many practical cases where multiple frames of the same scene can be obtained, such as satellite imaging, video surveillance, video enhancement and restoration, digital mosaicking, and medical imaging. In this paper, we applied the super resolution reconstruction method in spatial domain to video sequences. Test images are adjacently sampled images from continuous video sequences and are overlapped at high rate. We constructed the observation model between the HR images and LR images applied with the Maximum A Posteriori(MAP) reconstruction method which is one of the major methods in the super resolution grid construction. Based on the MAP method, we reconstructed high resolution images from low resolution images and compared the results with those from other known interpolation methods.

• Journal of Biomedical Engineering Research
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• v.44 no.5
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• pp.346-353
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• 2023

In this paper, we propose an innovative approach that leverages deep learning to find optimal reference points for achieving precise tooth segmentation in three-dimensional tooth point cloud data. A dataset consisting of 350 aligned maxillary and mandibular cloud data was used as input, and both end coordinates of individual teeth were used as correct answers. A two-dimensional image was created by projecting the rendered point cloud data along the Z-axis, where an image of individual teeth was created using an object detection algorithm. The proposed algorithm is designed by adding various modules to the Unet model that allow effective learning of a narrow range, and detects both end points of the tooth using the generated tooth image. In the evaluation using DSC, Euclid distance, and MAE as indicators, we achieved superior performance compared to other Unet-based models. In future research, we will develop an algorithm to find the reference point of the point cloud by back-projecting the reference point detected in the image in three dimensions, and based on this, we will develop an algorithm to divide the teeth individually in the point cloud through image processing techniques.

• Journal of radiological science and technology
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• v.38 no.4
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• pp.375-381
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• 2015

Digital Radiography is a big part of diagnostic radiology. Because uncorrected digital radiography image supported false effect of Patient's health care. We must be manage the correct digital radiography image. Thus, the artifact images can have effect to make a wrong diagnosis. We report types of occurrence by analyzing the artifacts that occurs in digital radiography system. We had collected the artifacts occurred in digital radiography system of general hospital from 2007 to 2014. The collected data had analyzed and then had categorize as the occurred causes. The artifacts could be categorized by hardware artifacts, software artifacts, operating errors, system artifacts, and others. Hardware artifact from a Ghost artifact that is caused by lag effect occurred most frequently. The others cases are the artifacts caused by RF noise and foreign body in equipments. Software artifacts are many different types of reasons. The uncorrected processing artifacts and the image processing error artifacts occurred most frequently. Exposure data recognize (EDR) error artifacts, the processing error of commissural line, and etc., the software artifacts were caused by various reasons. Operating artifacts were caused when the user didn't have the full understanding of the digital medical image system. System artifacts had appeared the error due to DICOM header information and the compression algorithm. The obvious artifacts should be re-examined, and it could result in increasing the exposure dose of the patient. The unclear artifact leads to a wrong diagnosis and added examination. The ability to correctly determine artifact are required. We have to reduce the artifact occurrences by understanding its characteristic and providing sustainable education as well as the maintenance of the equipments.

• Journal of Gastric Cancer
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• v.3 no.4
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• pp.195-200
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• 2003

Purpose: Advancement of computed tomography (CT) hardware and software has allowed thin section scanning and reconstruction of fascinating 2-dimentional (2D) and 3- dimentional (3D) images. Especially, the reconstruction of 3D images of gastrointestinal tract has been used in the detection and diagnosis of pre-malignant and malignant diseases. To compare the efficacy of CT gastrography with conventional upper gastrointenstinal series (UGIs) in gastric cancer patients. Materials and Methods: During Nov. 2002 and Mar. 2003, twenty-seven patients who had gastric cancer received both double contrast upper GI series and CT gastrography prior to radical surgery. Among these patients, nineteen had early gastric cancer (EGC) and 8 had advanced gastric cancer (AGC). Fifteen patients were male and 12 were female. The mean age was 54 yrs (range, $27\∼75$ yrs). The patients were placed on NPO and Stomach was distended with gas in fasting state prior to CT scanning. Double contrast upper GI series were performed as routine manual. CT scan was conducted in all patients using 8 or 16-channel multidetector CT in this study. The collimation and reconstruction for CT scanning were set at 2.5 mm and 1.25 mm, respectively. CT scanning was performed in the supine position. For image processing, CT gastrography, in which raysum and surface rendering images were constructed, virtual and 2D image in coronal and sagittal images were performed. The detectability of gastric cancer was assessed between UGIs and CT gastrography. Results: In AGCs, the detection rate of cancer using CT gastrography and virtual gastroscopy was higher than EGC cases. However, CT gastrography and virtual gastroscopy showed less favorable results than UGIs. Even though only a small number of cases had been studied, we might conclude that CT gastrography and virtual gastroscopy could replace UGIs in the detection of AGC cases. Conclusion: The detection rate used with CT gastrography and Virtual gastroscopy is not better than that of UGIs in early gastric cancer, however, in advanced gastric cancer cases, it is nearly equal to that of UGIs.

• Archives of design research
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• v.17 no.4
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• pp.51-60
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• 2004

The medical instrument industry which is one of the high value added industry has been neglected on the various system and political support because it has been recognized as an unknown field to the public although it is the very easy-approaching field for the export market that minimize a technological gap between advanced country and Korea. Especially, the product design that is very important element for the efficient medical treatment and the psychological stabilization of patient is a typical field of lack of investment and support by the unconcern and lack of understanding of design. Therefore this research suggests the current problem of design with the general inquiry of internal and external market situation and domestic medical instrument industry and also it has the conclusion of an alternative proposal for the solution with the design development processing of a moving type-image diagnostic equipment. We will emboss the importance of design competitiveness, suggest the model and basic data to the medical instrument company that starts later, and be a role of inspiration for the lasting investible desire with this research.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.3
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• pp.101-108
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• 2020

Since the performance of deep learning techniques has recently been proven in the field of image processing, there are many attempts to perform classification, analysis, and detection of images using such techniques in various fields. Among them, the expectation of medical image analysis software, which can serve as a medical diagnostic assistant, is increasing. In this study, we are attention to the capsule endoscope image, which has a large data set and takes a long time to judge. The purpose of this paper is to distinguish the gastrointestinal landmarks and to estimate the gastrointestinal transition location that are common to all patients in the judging of capsule endoscopy and take a lot of time. To do this, we designed CNN-based Classifier that can identify gastrointestinal landmarks, and used it to estimate the gastrointestinal transition location by filtering the results. Then, we estimate gastrointestinal transition location about seven of eight patients entered the suspected gastrointestinal transition area. In the case of change from the stomach to the small intestine(pylorus), and change from the small intestine to the large intestine(ileocecal valve), we can check all eight patients were found to be in the suspected gastrointestinal transition area. we can found suspected gastrointestinal transition area in the range of 100 frames, and if the reader plays images at 10 frames per second, the gastrointestinal transition could be found in 10 seconds.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.441-447
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• 2023

Intravenous infusion therapy is a standard nursing procedure in medical institutions that provides patients with drugs, fluids, blood, and nutrients into the patient's mucus. It is mainly performed and managed by nurses. Additionally, it is an injection method that injects drugs directly into the blood vessels, and is used to achieve rapid results in emergency situations, and quick and accurate effects can be expected. Even experienced nurses through education and training often make mistakes, which can not only cause discomfort to patients but also cause various problems that threaten patient safety. Various studies are being conducted to reduce the pain caused by these mistakes. This paper acquired images of veins on the back of the hands of three subjects through an image detection device and conducted a study to derive an algorithm to provide clear vein images through image processing of the collected images. To sharpen the acquired vein images, existing algorithms Histogram Equalization, CLAHE, and Unsharp Masking were selected and combined. A histogram graph was used to compare images derived by applying individual algorithms and algorithm combinations to images. The histogram graph was checked by calculating the difference between the minimum and maximum values of distributed pixels and averaging them. The algorithm combination presented in this paper was 209.1, which was higher than the average values of individual algorithms of 138.7, 132.3, and 126.2, and it was confirmed that visibility was good even in actual images.

• Korean Journal of Digital Imaging in Medicine
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• v.9 no.1
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• pp.7-15
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• 2007

This study aim to investigate image characteristics due to focus-grid and head phantom decentering from the armorphos silicon thin film transistor detector the fixed focus-grid is applied, wish to propose right use method of digital medical equipment. Acquired image according to focus-grid and head phantom position decentering using head phantom on armorphos silicon thin film transistor detector the fixed focus-grid is applied. acquired image evaluate pixel value, histogram, plot profile, surface plot using NIB (Image J) image analysis program and compared decentering image with standard image. Mean value and standard deviation value of focus-grid lateral decentering and duplex decentering of focus-grid and head phantom decreased by ratio, consequently increase of horizontality, diagonal decentering. also, deteriorated contrast of image because frequency of high pixel value decreases fairly. according increases decentering, image distortion phenomenon was increase, by next time, pixel mean value of head phantom decentering was no big change but horizontality, diagonal, mean value and standard deviation value of pixel decreased by ratio. Even if increase pixel noise of image because wide latitude and post processing ability of digital detector, radiotechnologist can not recognize. Therefore, radiotechnologist must recognize correctly the photographing factors which increases pixel noise on the grid system installation digital detector and should exam.