• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.225-228
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• 2003

The purpose of this paper is to develop a semi -automated system for medical image processing with which tissues or organs from medical images can be segmented and classified by people who have basic knowledge of image processing. In addition, the proposed medical image processing system is independent on types of human tissues or images. In this paper, a new semi-automated image processing system with essential image processing functions for medical images is introduced

• Journal of Biomedical Engineering Research
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• v.17 no.3
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• pp.305-312
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• 1996

A new three dimensional fractal coding is proposed with a perceptually enhanced matching. Since most of medical images (e.g. computed tomoyaphy or magnetic resonance images) have three dimensional characters, searching regions are extended to adjacent slices. For a perceptually enhanced matching, a high frequency boost filter is used for pre-filtering images to be encoded, and a least mean square error matching is applied to the edge enhanced Images rather than the original images. From simulation with magnetic resonance images($255\times255$, 8bits/pixel), reconstructed images by the proposed compression algorithm show much improved subjective image quality with higher peak signnal-to-noise ratio compared to those by existing fractal coding algorithms at compression ratios of about 10.

• Korean Journal of Radiology
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• v.25 no.4
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• pp.384-394
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• 2024

Objective: To evaluate the image quality of novel dark-blood computed tomography angiography (CTA) imaging combined with deep learning reconstruction (DLR) compared to delayed-phase CTA images with hybrid iterative reconstruction (HIR), to visualize the cervical artery wall in patients with Takayasu arteritis (TAK). Materials and Methods: This prospective study continuously recruited 53 patients with TAK (mean age: 33.8 ± 10.2 years; 49 females) between January and July 2022 who underwent head-neck CTA scans. The arterial- and delayed-phase images were reconstructed using HIR and DLR. Subtracted images of the arterial-phase from the delayed-phase were then added to the original delayed-phase using a denoising filter to generate the final-dark-blood images. Qualitative image quality scores and quantitative parameters were obtained and compared among the three groups of images: Delayed-HIR, Dark-blood-HIR, and Dark-blood-DLR. Results: Compared to Delayed-HIR, Dark-blood-HIR images demonstrated higher qualitative scores in terms of vascular wall visualization and diagnostic confidence index (all P < 0.001). These qualitative scores further improved after applying DLR (Dark-blood-DLR compared to Dark-blood-HIR, all P < 0.001). Dark-blood DLR also showed higher scores for overall image noise than Dark-blood-HIR (P < 0.001). In the quantitative analysis, the contrast-to-noise ratio (CNR) values between the vessel wall and lumen for the bilateral common carotid arteries and brachiocephalic trunk were significantly higher on Dark-blood-HIR images than on Delayed-HIR images (all P < 0.05). The CNR values were significantly higher for Dark-blood-DLR than for Dark-blood-HIR in all cervical arteries (all P < 0.001). Conclusion: Compared with Delayed-HIR CTA, the dark-blood method combined with DLR improved CTA image quality and enhanced visualization of the cervical artery wall in patients with TAK.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.6C
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• pp.824-833
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• 2004

Due to the bandwidth and storage limitations, medical images are needed to be compressed before transmission and storage. DICOM (Digital Imaging and Communications in Medicine) specification, which is the medical images standard, provides a mechanism for supporting the use of JPEG still image compression standard. In this paper, we explain a method for compressing medical images by JPEG standard and propose two methods for JPEG compression. First, because medical images differ from natural images in optical feature, we propose a method to design adaptively the quantization table using spectrum analysis. Second, because medical images have higher pixel depth than natural images do, we propose a method to design Huffman table which considers the probability distribution feature of symbols. Therefore, we propose methods to design a quantization table and Huffman table suitable for medical images. Simulation results show the improved performance compared to the quantization table and the adjusted Huffman table of JPEG standard. Proposed methods which are satisfied JPEG Standard, can be applied to PACS (Picture Archiving and Communications System).

• Journal of Korea Multimedia Society
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• v.18 no.1
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• pp.17-24
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• 2015

In this paper, a novel scheme for correcting rotated region in medical images using SIFT(Scale Invariant Feature Transform) algorithm is presented. Using the feature extraction function of SIFT, the rotation angle of rotated object in medical images is calculated as follows. First, keypoints of both reference and rotated medical images are extracted by SIFT. Second, the matching process is performed to the keypoints located at the predetermined ROI(Region Of Interest) at which objects are not cropped or added by rotating the image. Finally, degrees of matched keypoints are calculated and the rotation angle of the rotated object is determined by averaging the difference of the degrees. The simulation results show that the proposed scheme has excellent performance for correcting the rotated region in medical images.

• Journal of Electrical Engineering and Technology
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• v.11 no.2
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• pp.499-507
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• 2016

Medical imaging techniques such as Magnetic Resonance Imaging (MRI), Computed Tomography (CT) and Ultrasound (US) produce a large amount of digital medical images. Hence, compression of digital images becomes essential and is very much desired in medical applications to solve both storage and transmission problems. But at the same time, an efficient image compression scheme that reduces the size of medical images without sacrificing diagnostic information is required. This paper proposes a novel threshold-based medical image compression algorithm to reduce the size of the medical image without degradation in the diagnostic information. This algorithm discusses a novel type of thresholding to maximize Compression Ratio (CR) without sacrificing diagnostic information. The compression algorithm is designed to get image with high optimum compression efficiency and also with high fidelity, especially for Peak Signal to Noise Ratio (PSNR) greater than or equal to 36 dB. This value of PSNR is chosen because it has been suggested by previous researchers that medical images, if have PSNR from 30 dB to 50 dB, will retain diagnostic information. The compression algorithm utilizes one-level wavelet decomposition with threshold-based coefficient selection.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.6
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• pp.2521-2526
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• 2015

Objective: The purpose of this study was to evaluate computed tomography (CT) virtual non-contrast (VNC) spectral imaging for gastric carcinoma. Materials and Methods: Fifty-two patients with histologically proven gastric carcinomas underwent gemstone spectral imaging (GSI) including non-contrast and contrast-enhanced hepatic arterial, portal venous, and equilibrium phase acquisitions prior to surgery. VNC arterial phase (VNCa), VNC venous phase (VNCv), and VNC equilibrium phase (VNCe) images were obtained by subtracting iodine from iodine/water images. Images were analyzed with respect to image quality, gastric carcinoma-intragastric water contrast-to-noise ratio (CNR), gastric carcinoma-perigastric fat CNR, serosal invasion, and enlarged lymph nodes around the lesions. Results: Carcinoma-water CNR values were significantly higher in VNCa, VNCv, and VNCe images than in normal CT images (2.72, 2.60, 2.61, respectively, vs 2.35, $p{\leq}0.008$). Carcinoma-perigastric fat CNR values were significantly lower in VNCa, VNCv, and VNCe images than in normal CT images (7.63, 7.49, 7.32, respectively, vs 8.48, p< 0.001). There were no significant differences of carcinoma-water CNR and carcinoma-perigastric fat CNR among VNCa, VNCv, and VNCe images. There was no difference in the determination of invasion or enlarged lymph nodes between normal CT and VNCa images. Conclusions: VNC arterial phase images may be a surrogate for conventional non-contrast CT images in gastric carcinoma evaluation.

• Korean Journal of Digital Imaging in Medicine
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• v.11 no.1
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• pp.35-41
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• 2009

This study was conducted to improve performance flow of PACS registration and output of external medical images by developing or adding File Transfer Protocol(FTP) Module on Order Communication System(OCS) and to upgrade efficiency of performance. The numbers of requests for examination of external medical images from January 2004 to December 2007 were investigated and the numbers of cases of examinations and losses were done respectively from January to June, 2007 as a period before the improvement and from July to December, 2007 as a period after it. Satisfaction of persons inputting external medical images of CD was asked directly before and after the improvement. When the numbers of requests for examination of external medical images from 2004 to 2007 2004 were investigated, they were 12,783, 16,774, 21,613 and 27,487 cases in 2004, 2005, 2005 and 2007 respectively. For the numbers of the requests from January to December, 2007 it was the lowest in February by recording 1846 and it was 2800 in October. While the number of loss of external medical images was averagely 3.6 before using FTP Module on OCS, it reduced to 0 and satisfaction increased to 98% after it. By utilizing FTP Module on OSC for PACS registration of external medical images, the images were delivered simultaneously with occurrence of order, PACS registration of many patients was conducted together and CDs were returned to patients immediately after sending images from outpatient clinics or wards to remove possibility of losing them. In addition, because the module was established on OCS and data were sent associated with order, problems related with order were decreased. By eliminating movement distance it was turned out to be very effective in terms of time and space.

• Korean Journal of Radiology
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• v.22 no.6
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• pp.951-958
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• 2021

Objective: To evaluate the usefulness of virtual monochromatic images (VMIs) obtained using dual-layer dual-energy CT (DL-DECT) for evaluating brain tumors. Materials and Methods: This retrospective study included 32 patients with brain tumors who had undergone non-contrast head CT using DL-DECT. Among them, 15 had glioblastoma (GBM), 7 had malignant lymphoma, 5 had high-grade glioma other than GBM, 3 had low-grade glioma, and 2 had metastatic tumors. Conventional polychromatic images and VMIs (40-200 keV at 10 keV intervals) were generated. We compared CT attenuation, image noise, contrast, and contrast-to-noise ratio (CNR) between tumor and white matter (WM) or grey matter (GM) between VMIs showing the highest CNR (optimized VMI) and conventional CT images using the paired t test. Two radiologists subjectively assessed the contrast, margin, noise, artifact, and diagnostic confidence of optimized VMIs and conventional images on a 4-point scale. Results: The image noise of VMIs at all energy levels tested was significantly lower than that of conventional CT images (p < 0.05). The 40-keV VMIs yielded the best CNR. Furthermore, both contrast and CNR between the tumor and WM were significantly higher in the 40 keV images than in the conventional CT images (p < 0.001); however, the contrast and CNR between tumor and GM were not significantly different (p = 0.47 and p = 0.31, respectively). The subjective scores assigned to contrast, margin, and diagnostic confidence were significantly higher for 40 keV images than for conventional CT images (p < 0.01). Conclusion: In head CT for patients with brain tumors, compared with conventional CT images, 40 keV VMIs from DL-DECT yielded superior tumor contrast and diagnostic confidence, especially for brain tumors located in the WM.

• Journal of Biomedical Engineering Research
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• v.14 no.1
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• pp.9-16
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• 1993

For efficient storage and transmission of medical images, the requirement of image com pression is increasing. Because differences between reconstructed images and original images are related with errors In the diagnosis, lossless compression is generally preferred in mod- ical images. in Run Length Coding which is one of the lossless compression method, we have applied modified scanning direction based on the Hilbert curve, which is a kind of space fill ins curve. We have substituted the traditional raster scanning by Hilbert curve direction scanning. Using this method, we have studied enhancement of compression efficiency for medical images.