• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.457-460
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• 2002

The image quality of three-dimensional (3D) images has been widely investigated by the qualitative analysis method. A need remains for an objective and quantitative method to assess the image quality of 3D volume-rendered images. The purpose of this study was to evaluate the quantitative accuracy of distance measurements on 3D volume-rendered images of a dry human skull by using multi-detector computed tomography (MDCT). A radiologist measured five times the twenty-one direct measurement line items composed among twelve reference points on the skull surface with a digital vernier caliper. The water filled skull specimen was scanned with a MDCT according to the section thicknesses of 1.25, 2.50, 3.75, and 5.00 mm for helical (high quality; pitch 3:1) scan mode. MDCT data were reconstructed with its acquisition section thickness and with 1.25 mm section thickness for all scans. An observer also measured seven times the corresponding items on 3D volume-rendered images with measuring tools provided by volumetric analysis software. The quantitative accuracy of distance measurements on the 3D volume-rendered images was statistically evaluated (p-value < 0.05) by comparatively analyzing these measurements with the direct distance measurements. The accuracy of distance measurements on the 3D volume-rendered MDCT images acquired with 1.25, 2.50, 3,75 and 5.00 mm section thickness and reconstructed with its section thickness were 48%, 33%, 23%, and 14%, respectively. Meanwhile, there were insignificant statistical differences in accuracy of distance measurements among 3D volume-rendered images reconstructed with 1.25 mm section thickness for the each acquisition section thickness. MDCT images acquired with thick section thickness and reconstructed with thin section thickness in helical scan mode should be effectively used in medical planning of 3D volume-rendered images. The quantitative analysis of distance measurement may be a useful tool for evaluating the quantitative accuracy and the defining optimal parameters of 3D volume-rendered CT images.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.322-323
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• 2002

Partial volume averaging effect of PET data influences on the accuracy of quantitative measurements of regional brain metabolism because spatial resolution of PET is limited. The purpose of this study was to evaluate the accuracy of partial volume correction carried out on $^{18}$ F-PET images using Hoffman brain phantom. $^{18}$ F-PET Hoffman phantom images were co-registered to MR slices of the same phantom. All the MR slices of the phantom were then segmented to be binary images. Each of these binary images was convolved in 2 dimensions with the spatial resolution of the PET. The original PET images were then divided by the smoothed binary images in slice-by-slice, voxel-by-voxel basis resulting in larger PET image volume in size. This enlarged partial volume corrected PET image volume was multiplied by original binary image volume to exclude extracortical region. The evaluation of partial volume corrected PET image volume was performed by region of interests (ROI) analysis applying ROIs, which were drawn on cortical regions of the original MR image slices, to corrected and original PET image volume. From the ROI analysis, range of regional mean values increases of partial volume corrected PET images was 4 to 14%, and average increase for all the ROIs was about 10% in this phantom study. Hoffman brain phantom study was useful for the objective evaluation of the partial volume correction method. This MR-based correction method would be applicable to patients in the. quantitative analysis of FDG-PET studies.

• Imaging Science in Dentistry
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• v.53 no.1
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• pp.69-75
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• 2023

Purpose: Maxillofacial trauma predominantly affects young adults between 20 and 40 years of age. Although radioprotection is a legal requirement, the significant potential of dose reduction in computed tomography (CT) is still underused in the clinical routine. The objective of this study was to evaluate whether maxillofacial fractures can be reliably detected and classified using ultra-low-dose CT. Materials and Methods: CT images of 123 clinical cases with maxillofacial fractures were classified by two readers using the AOCOIAC software and compared with the corresponding results from post-treatment images. In group 1, consisting of 97 patients with isolated facial trauma, pre-treatment CT images at different dose levels (volumetric computed tomography dose index: ultra-low dose, 2.6 mGy; low dose, <10 mGy; and regular dose, <20 mGy) were compared with post-treatment cone-beam computed tomography (CBCT). In group 2, consisting of 31 patients with complex midface fractures, pre-treatment shock room CT images were compared with post-treatment CT at different dose levels or CBCT. All images were presented in random order and classified by 2 readers blinded to the clinical results. All cases with an unequal classification were re-evaluated. Results: In both groups, ultra-low-dose CT had no clinically relevant effect on fracture classification. Fourteen cases in group 2 showed minor differences in the classification code, which were no longer obvious after comparing the images directly to each other. Conclusion: Ultra-low-dose CT images allowed the correct diagnosis and classification of maxillofacial fractures. These results might lead to a substantial reconsideration of current reference dose levels.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.2
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• pp.69-78
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• 2016

Ischemic stroke is a disease that the brain tissues cannot function by reducing blood flow due to thrombosis or embolisms. Due to the nature of the disease, it is most important to identify the status of cerebral vessel and the medical images are necessarily used for its diagnosis. Among many indicators, brain MRI is most widely utilized because experts can effectively obtain the semantic information such as cerebral anatomy aiding the diagnosis with it. However, in case of emergency diseases like ischemic stroke, even though a intelligent system is required for supporting the prompt diagnosis and treatment, the current systems have some difficulties to provide the information of medical images intuitively. In other words, as the current systems have managed the medical images based on the basic meta-data such as image name, ID and so on, they cannot consider semantic information inherent in medical images. Therefore, in this paper, to provide core information like cerebral anatomy contained in brain MRI, we suggest a template-driven medical images mapping method. The key idea of the method is defining the mapping characteristics between anatomic feature and representative images by using template images that can be representative of the whole brain MRI image set and revealing the semantic relations that only medical experts can check between images. With our method, it will be possible to manage the medical images based on semantic.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2395-2398
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• 2003

This paper focuses on lossless medical image compression methods for medical images that operate on two-dimensional(2D) reversible integer wavelet transform. We offer an application of the Set Partitioning in Hierarchical Trees(SPIHT) algorithm [1][3][9] to medical images, using a 2D wavelet decomposition and a 2D spatial dependence tree. The wavelet decomposition is accomplished with integer wavelet filters implemented with the lifting method, where careful scaling and truncations keep the integer precision small and the transform unitary. We have tested our encoder on medical images using different integer filters. Results show that our algorithm with certain filters performs as well and sometimes better in lossless coding than previous coding systems using 2D integer wavelet transforms on medical images.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.3
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• pp.172-177
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• 2009

In this paper, a new morphology-based homomorphic filtering technique is presented to enhance features in medical images. The homomorphic filtering is performed based on the morphological sub-bands, in which an image is morphologically decomposed. An evolutionary design is carried to find an optimal gain and structuring element of each sub-band. As a search algorithm, Differential Evolution scheme is utilized. Simulations show that the proposed filter improves the contrast of the interest feature in medical images.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.05
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• pp.104-107
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• 1997

A medical teleconferencing and medical image transmision system has been developed for diagnosis of the medical images between the medical doctors who are far away. The medical teleconferencing system transmits the voice and image of the doctors using the video and audio capture boards. The medical image transmission system software uses the medical image standard DICOM 3.0 for the future expansibility and the open system interconectivity. The medical images usually use CR images.

• Journal of the Korea Society of Computer and Information
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• v.14 no.12
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• pp.191-199
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• 2009

The integrated medical information system is an effective medical diagnosis assistance system which offers an environment in which medial images and diagnosis information can be shared. Because of the large-scale medical institutions and their cooperating organizations are operating the integrated medical information systems, they can share medical images and diagnosis information. However, this system can only stored and transmitted information without other functions. To resolve this problem and to enhance the efficiency of diagnostic activities, a medical image analysis system is necessary. In this paper, the proposed relationship method analyzes medical images for features generation. Under this method, the medical images have been segmented into several objects. The medical image features have been extracted from each segmented image. Then, extracted features were applied to the Relationship Method for medical image analysis. Several experimental results that show the effectiveness of the proposed method are also presented.

• Journal of the Optical Society of Korea
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• v.15 no.3
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• pp.300-304
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• 2011

Optical microscopes are widely used for medical imaging these days, but biopsy is a lengthy process that causes many problems during the ex-vivo imaging procedure. The endo-microscope has been studied to increase accessibility to the human body and to get in-vivo images to use for medical diagnosis. This research proposes a multi-modal confocal endo-microscope for bio-medical imaging. We introduce the design process for a small endoscopic probe and a coupling mechanism for the probe to make the multi-modal confocal endo-microscope. The endoscopic probe was designed to decrease chromatic and spherical aberrations, which deteriorate the images obtained with the conventional GRIN lens. Fluorescence and reflectance images of various samples were obtained with the proposed endo-microscope. We evaluated the performance of the proposed endo-microscope by analyzing the acquired images, and demonstrate the possibilities of in-vivo medical imaging for early diagnosis.

• Proceedings of the Korean Society Of Semiconductor Equipment Technology
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• 2004.05a
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• pp.217-222
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• 2004

This paper focuses on lossy medical image compression methods for medical images that operate on two-dimensional(2D) integer wavelet transform. We offer an application of the Set Partitioning in Hierarchical Trees(SPIHT) algorithm to medical images, using a 2D wavelet decomposition and a 2D spatial dependence tree. The wavelet decomposition is accomplished with integer wavelet filters implemented with the lifting method, where careful scaling and truncations keep the integer precision small and the transform unitary. We have tested our encoder on medical images using different integer filters. Results show that our algorithm with certain filters performs as well and is sometimes better lossy coding using 2D integer wavelet transforms on medical images.