• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.6
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• pp.267-275
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• 2023

This paper presents the development of specialized software for annotating volume-of-interest on ¹⁸F-FDG PET/CT images with the goal of facilitating the studies and diagnosis of head and neck cancer (HNC). To achieve an efficient annotation process, we employed the SE-Norm-Residual Layer-based U-Net model. This model exhibited outstanding proficiency to segment cancerous regions within ¹⁸F-FDG PET/CT scans of HNC cases. Manual annotation function was also integrated, allowing researchers and clinicians to validate and refine annotations based on dataset characteristics. Workspace has a display with fusion of both PET and CT images, providing enhance user convenience through simultaneous visualization. The performance of deeplearning model was validated using a Hecktor 2021 dataset, and subsequently developed semi-automatic annotation functionalities. We began by performing image preprocessing including resampling, normalization, and co-registration, followed by an evaluation of the deep learning model performance. This model was integrated into the software, serving as an initial automatic segmentation step. Users can manually refine pre-segmented regions to correct false positives and false negatives. Annotation images are subsequently saved along with their corresponding ¹⁸F-FDG PET/CT fusion images, enabling their application across various domains. In this study, we developed a semi-automatic annotation software designed for efficiently generating annotated lesion images, with applications in HNC research and diagnosis. The findings indicated that this software surpasses conventional tools, particularly in the context of HNC-specific annotation with ¹⁸F-FDG PET/CT data. Consequently, developed software offers a robust solution for producing annotated datasets, driving advances in the studies and diagnosis of HNC.

• Journal of the Korea Computer Graphics Society
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• v.23 no.1
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• pp.49-55
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• 2017

Computed tomographic angiography (CTA) is widely used in the diagnosis and treatment of coronary artery disease because it shows not only the whole anatomical structure of the cardiovascular three-dimensionally but also provides information on the lesion and type of plaque. However, due to the large size of the image, there is a limitation in manually extracting coronary arteries, and related researches are performed to automatically extract coronary arteries accurately. As the coronary artery originate from the ascending aorta, the ascending aorta and ostium should be detected to extract the coronary tree accurately. In this paper, we propose an automatic segmentation for the ostium as a starting structure of coronary artery in CTA. First, the region of the ascending aorta is initially detected by using Hough circle transform based on the relative position and size of the ascending aorta. Second, the volume of interest is defined to reduce the search range based on the initial area. Third, the refined ascending aorta is segmented by using a two-dimensional geodesic active contour. Finally, the two ostia are detected within the region of the refined ascending aorta. For the evaluation of our method, we measured the Euclidean distance between the result and the ground truths annotated manually by medical experts in 20 CTA images. The experimental results showed that the ostia were accurately detected.

• Progress in Medical Physics
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• v.26 no.1
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• pp.52-58
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• 2015

The automated dental cavity detection program for a new concept intra-oral dental x-ray imaging device, an auxiliary diagnosis system, which is able to assist a dentist to identify dental caries in an early stage and to make an accurate diagnosis, was to be developed. The primary theory of the automatic dental cavity detection program is divided into two algorithms; one is an image segmentation skill to discriminate between a dental cavity and a normal tooth and the other is a computational method to analyze feature of an tooth image and take an advantage of it for detection of dental cavities. In the present study, it is, first, evaluated how accurately the DRLSE (Direct Regularized Level Set Evolution) method extracts demarcation surrounding the dental cavity. In order to evaluate the ability of the developed algorithm to automatically detect dental cavities, 7 tooth phantoms from incisor to molar were fabricated which contained a various form of cavities. Then, dental cavities in the tooth phantom images were analyzed with the developed algorithm. Except for two cavities whose contours were identified partially, the contours of 12 cavities were correctly discriminated by the automated dental caries detection program, which, consequently, proved the practical feasibility of the automatic dental lesion detection algorithm. However, an efficient and enhanced algorithm is required for its application to the actual dental diagnosis since shapes or conditions of the dental caries are different between individuals and complicated. In the future, the automatic dental cavity detection system will be improved adding pattern recognition or machine learning based algorithm which can deal with information of tooth status.

• Journal of the Korean Society of Radiology
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• v.16 no.2
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• pp.103-113
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• 2022

In this paper, a combined ¹⁸F-FDG(fluorodeoxyglucose) and MNP(magnetic nanoparticles) contrast agent was synthesized using N-(p-maleimidophenyl) isocyanate as the crosslinker for use in simultaneous PET-MRI scans. PET-MRI images were acquired and evaluated before and after injection of the combined contrast imaging agent (¹⁸F-FDG labeled MNP) from a glioma stem cell mouse model. After setting the region of interest (ROI) on each acquired image, the area of the lesion was calculated by segmentation. As a result, the PET image was larger than the MRI. In particular, the simultaneous PET-MRI images showed accurate lesions along with the surrounding soft tissue. The mean and standard deviation values were higher in the MRI images alone than in the PET images or the simultaneous PET-MRI images, regardless of whether the contrast agent was injected. In addition, the simultaneous PET-MRI image values were higher than for the PET images. For PSNR experiments, the original image was PET Image using 18F-FDG, MRI using MNPs, and MRI without contrast medium, and the target image was simultaneous PET-MRI image using 18F-FDG labeled MNPs contrast medium. As a result, all of them appeared significantly, suggesting that the 18F-FDG labeled MNPs contrast medium is useful. Future research is needed to develop an agent that can simultaneously diagnose and treat through SPECT-MRI imaging research that can use various nuclides.

• Pediatric Infection and Vaccine
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• v.15 no.2
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• pp.180-187
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• 2008

Purpose : We wanted to determine the characteristics of patients with Kawasaki disease (KD) who were unresponsive to intravenous immunoglobulin (IVIG). Methods : The patients with KD were divided into two groups: the IVIG responsive group (25 cases) and the IVIG unresponsive group (14 cases). We analyzed various parameters before and after the administration of IVIG, including the complete blood cell count with the differential count (%), the erythrocyte segmentation rate (ESR), the C-reactive protein (CRP) level and the protein and lipid profiles. Results : The IVIG unresponsive group had a prolonged duration of fever and a higher incidence of CAL compared to the IVIG responsive group (P<0.001, respectively). Before IVIG infusion, the neutrophil differential, the ESR and the CRP values were higher (P<0.001), and the total protein and albumin values were lower in the IVIG unresponsive group (P=0.01) compared to the IVIG responsive group. After IVIG infusion, there were no significant changes in the WBC count and CRP levels in the IVIG unresponsive group. The reduction of the HDL-cholesterol levels by IVIG was more significant in the unresponsive group (P=0.02). Conclusion : A more severe and prolonged inflammatory response occurred in the IVIG unresponsive group at an early stage, and this finding can be detected by such inflammatory parameters as the neutrophil count and the CRP and HDL-cholesterol levels after IVIG infusion.

• The Korean Journal of Nuclear Medicine Technology
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• v.18 no.1
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• pp.19-25
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• 2014

Purpose: Integrated PET/MRI has been developed recently has become a lot of help to the point oncologic, neological, cardiological nuclear medicine. By using this PET/MRI, a ${\mu}-map$ is created some special MRI sequence which may be divided parts of the body for attenuation correction. However, because an MRI contrast agent is necessary in order to obtain an more MRI information, we will evaluate to see an effect of SUV on PET image that corrected attenuation by MRI with contrast agent. Materials and Methods: As PET/MRI machine, Biograph mMR (Siemens, Germany) was used. For phantom test, 1mCi $^{18}F-FDG$ was injected in cylinderical uniformity phantom, and then acquire PET data about 10 minutes with VIBE-DIXON, UTE MRI sequence image for attenuation correction. T1 weighted contrast media, 4 cc DOTAREM (GUERBET, FRANCE) was injected in a same phatnom, and then PET data, MRI data were acquired by same methodes. Using this PET, non-contrast MRI and contrast MRI, it was reconstructed attenuation correction PET image, in which we evanuated the difference of SUVs. Additionally, for let a high desity of contrast media, 500 cc 2 plastic bottles were used. We injected $^{18}F-FDG$ with 5 cc DOTAREM in first bottle. At second bottle, only $^{18}F-FDG$ was injected. and then we evaluated a SUVs reconstructed by same methods. For clinical patient study, rectal caner-pancreas cancer patients were selected. we evaluated SUVs of PET image corrected attenuastion by contrast weighted MRI and non-contrast MRI. Results: For a phantom study, although VIBE DIXON MRI signal with contrast media is 433% higher than non-contrast media MRI, the signals intensity of ${\mu}-map$, attenuation corrected PET are same together. In case of high contrast media density, image distortion is appeared on ${\mu}-map$ and PET images. For clinical a patient study, VIBE DIXON MRI signal on lesion portion is increased in 495% by using DOTAREM. But there are no significant differences at ${\mu}-map$, non AC PET, AC-PET image whether using contrast media or not. In case of whole body PET/MRI study, %diff between contras and non contrast MRAC at lung, liver, renal cortex, femoral head, myocardium, bladder, muscle are -4.32%, -2.48%, -8.05%, -3.14%, 2.30%, 1.53%, 6.49% at each other. Conclusion: In integrated PET/MRI, a segmentation ${\mu}-map$ method is used for correcting attenuation of PET signal. although MRI signal for attenuation correciton change by using contrast media, ${\mu}-map$ will not change, and then MRAC PET signal will not change too. Therefore, MRI contrast media dose not affect for attenuation correction PET. As well, not only When we make a flow of PET/MRI protocol, order of PET and MRI sequence dose not matter, but It's possible to compare PET images before and after contrast agent injection.