• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.8
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• pp.225-231
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• 2013

Medical image segmentation is an image processing technology prior to performing various medical image processing. Therefore, a variety of methods have been researched for fast and accurate medical image segmentation. Accurate judgment of segmentation region is needed to segment the interest region in which patient requested in medical image that various organs exist. However, an case that scanned a part of organs is small occurs. In this case, information to determine the segmentation region is lack. consequently, a removal of segmentation region occurs during the segmentation process. In this paper, we improved segmentation results in a small region using volume data and linear equation. In order to verify the performance of the proposed method, we segmented the lung region of chest CT images. As a result of experiments, we confirmed that image segmentation accuracy rose from 0.978 to 0.981 and standard deviation also improved from 0.281 to 0.187.

• Korean Journal of Digital Imaging in Medicine
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• v.15 no.2
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• pp.1-6
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• 2013

This study is to provide clinical data when reverse-water's-view was carried out about pediatric who did not communicate by applying self-development jaw lift tool. This study were conducted in a subject of 23 children who examined revers-water's-view from 2013 July 6 to 2013 August 5 at our hospital. Two group time which were carried out revers-water's with tool and without tool were measured. also, Image of two group were evaluated. Evaluation data obtained by measuring the average difference were analyzed by independent-t-test. After apply self-development-jaw-lift-tool, time was reduced by 35.2%(36.6sec). the results indicated significant differences(p< .05). Image evaluation was increase 43.5%(1.03point), It was statistically highly significant difference (p< .01). If apply self-development-jaw-lift-tool in pediatric revers-water's-view, operator can provide fast, convenience, high quality image to pediatric.

• The Korean Journal of Emergency Medical Services
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• v.20 no.2
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• pp.81-97
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• 2016

Purpose: This study aimed to investigate the awareness and direction of paramedics work and image in hospitals. Methods: From April 16 to May 5, 2015, data were collected through structured questionnaires from 45 paramedics and 81 nurses working in emergency medical institutions. The data were analyzed using SPSS version 18.0. Results: The work of paramedics is evaluated to be highly worthy at the in-hospital level rather than at the injury first-aid treatment level. It appears that paramedics are often forced to do what their hospitals tell them to do concerning matters related to conflicts with them and nurses. Paramedics stated that they experienced greater mental stress than those engaging in other professions, a finding similar to those of other studies. There was no statistically significant difference in opinions between the two groups about a desirable direction for the development of first-aid services at hospitals. More than two thirds of the respondents said that paramedics should be given the right to enter acting check for patients. Conclusion: Paramedics work is shown to differ in the opinions of paramedics themselves and nurses. Paramedics need for reform is associated with expanding the work of the law.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.5
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• pp.952-958
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• 2009

Recently, due to problems in terms of illegal copying of medical image and the right ownership and authentication of data, it is necessary for us to study about those problems. In this study, we propose steganography with a method of the hiding information of high-resolution in digital medical image. The proposed algorithm is one of the way that inserts secret information by protecting ROI area which is regarded as and important feature of high-resolution digital medical image. As a result, the proposed method made it possible to insert secret information of massive storage and didn't affect the imperceptibility in medical image quality based on capacity and PSNR showed the all image quality of about 33.33dB.

• Biomedical Engineering Letters
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• v.8 no.4
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• pp.355-364
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• 2018

When focusing using an ultrasonic transducer array, a main lobe is formed in the focal region of an ultrasound field, but side lobes also arise around the focal region due to the leakage. Since the side lobes cannot be completely eliminated in the focusing process, they are responsible for subsequent ultrasound image quality degradation. To improve ultrasound image quality, a signal processing strategy to reduce side lobes is definitely in demand. To this end, quantitative determination of main and side lobes is necessary. We propose a theoretically and actually error-free method of exactly discriminating and separately computing the main lobe and side lobe parts in ultrasound image by computer simulation. We refer to images constructed using the main and side lobe signals as the main and side lobe images, respectively. Since the main and side lobe images exactly represent their main and side lobe components, respectively, they can be used to evaluate ultrasound image quality. Defining the average brightness of the main and side lobe images, the conventional to side lobe image ratio, and the main to side lobe image ratio as image quality metrics, we can evaluate image characteristics in speckle images. The proposed method is also applied in assessing the performance of side lobe suppression filtering. We show that the proposed method may greatly aid in the evaluation of medical ultrasonic images using computer simulations, albeit lacking the use of actual experimental data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.7
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• pp.2359-2376
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• 2022

With the exponential growth of medical image big data represented by high-resolution CT images(CTI), the high-resolution CTI data is of great importance for clinical research and diagnosis. The paper takes lung CTI as an example to study. Retrieving answer CTIs similar to the input one from the large-scale lung CTI database can effectively assist physicians to diagnose. Compared with the conventional content-based image retrieval(CBIR) methods, the CBIR for lung CTIs demands higher retrieval accuracy in both the contour shape and the internal details of the organ. In traditional supervised deep learning networks, the learning of the network relies on the labeling of CTIs which is a very time-consuming task. To address this issue, the paper proposes a Weakly Supervised Similarity Evaluation Network (WSSENet) for efficiently support similarity analysis of lung CTIs. We conducted extensive experiments to verify the effectiveness of the WSSENet based on which the CBIR is performed.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.12
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• pp.138-145
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• 2009

Custom medical treatment is being widely adapted to lots of medical applications. A technology for 3D modeling is strongly required to fabricate medical implants for individual patient. Needs on true 3D CAD data of a patient is strongly required for tissue engineering and human body simulations. Medical imaging devices show human inner section and 3D volume rendering images of human organs. CT or MRI is one of the popular imaging devices for that use. However, those image data is not sufficient to use for medical fabrication or simulation. This paper mainly deals how to generate 3D geometry data from those medical images. A new image processing technology is introduced to reconstruct 3D geometry of a human body vacancy from the medical images. Then a surface geometry data is reconstructed by using Marching cube algorithm. Resulting CAD data is a custom 3D geometry data of human vacancy. This paper introduces a novel 3D reconstruction process and shows some typical examples with implemented software.

• Journal of Biomedical Engineering Research
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• v.35 no.5
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• pp.132-141
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• 2014

In an ordinary CT scan, a large number of projections with full field-of-view (FFOV) are necessary to reconstruct high resolution images. However, excessive x-ray dosage is a great concern in FFOV scan. Region-of-interest (ROI) CT or sparse-view CT is considered to be a solution to reduce x-ray dosage in CT scanning, but it suffers from bright-band artifacts or streak artifacts giving contrast anomaly in the reconstructed image. In this study, we propose an image reconstruction method to eliminate the bright-band artifacts and the streak artifacts simultaneously. In addition to the ROI scan for the interior projection data with relatively high sampling rate in the view direction, we get sparse-view exterior projection data with much lower sampling rate. Then, we reconstruct images by solving a constrained total variation (TV) minimization problem for the interior projection data, which is assisted by the exterior projection data in the compressed sensing (CS) framework. For the interior image reconstruction assisted by the exterior projection data, we implemented the proposed method which enforces dual data fidelity terms and a TV term. The proposed method has effectively suppressed the bright-band artifacts around the ROI boundary and the streak artifacts in the ROI image. We expect the proposed method can be used for low-dose CT scans based on limited x-ray exposure to a small ROI in the human body.

• Proceedings of the KOSOMBE Conference
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• v.1992 no.11
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• pp.105-108
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• 1992

In this paper, we have implemented the telemedicine system which has a color image system and a biosignal processor. The inputted image is acquisited to 512 by 480 color image data. The col looted data is compressed to 1/5 of the original image data by using 1/5 and compression algorithm. A biological signals are inputted by 12 bit A/D converter into the system. In case of using 2400bps modem, a frame full color image data and biological information data needed 10 minutes in transmission.

• Proceedings of the KOSOMBE Conference
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• v.1998 no.11
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• pp.113-114
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• 1998

In this paper, visualization of Visible Human data offered by NLM(National Library of Medicine) is performed using $VTK^{TM}$. Computed Tomography Data set(axial, $587\times341\times256$, and the distance between slices 1mm) is used throughout the study. Before the actual visualization routine, 8 bit-reader class of VTK is developed to transform CT data to VTK dataset. After that, the visualization procedures are done to display 3D image on PC. VTK is freeware, not a commercial software. The results of VTK show relatively good image quality and slower processing time compared with the commercial softwares like IAP, IDL, AVS. Thus if processing time is not the critical factor, VTK is worthy to be used in visualization of the medical images.