• Journal of Biomedical Engineering Research
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• v.43 no.4
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• pp.259-270
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• 2022

Artificial intelligence (AI) has been studied in various fields of medical imaging. Currently, top-notch deep learning (DL) techniques have led to high diagnostic accuracy and fast computation. However, they are rarely used in real clinical practices because of a lack of reliability concerning their results. Most DL models can achieve high performance by extracting features from large volumes of data. However, increasing model complexity and nonlinearity turn such models into black boxes that are seldom accessible, interpretable, and transparent. As a result, scientific interest in the field of explainable artificial intelligence (XAI) is gradually emerging. This study aims to review diverse XAI approaches currently exploited in medical imaging. We identify the concepts of the methods, introduce studies applying them to imaging modalities such as computational tomography (CT), magnetic resonance imaging (MRI), and endoscopy, and lastly discuss limitations and challenges faced by XAI for future studies.

• 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 Medical Physics Conference
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• 2006.08a
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• pp.156-156
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• 2006

• Journal of Biomedical Engineering Research
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• v.26 no.5
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• pp.283-294
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• 2005

The Center for Imaging Human Structures (CIH) was established in December 2002 to develop new diagnostic imaging techniques and to make them available to the greater community of biomedical and clinical researchers at Sungkyunkwan University. CIH has been involved in 5 specific activities to provide solutions for early diagnosis and improved treatment of human diseases. The five area goals include: 1) development of a digital mammography system with computer aided diagnosis (CAD); 2) development of digital radiological imaging techniques; 3) development of unified medical solutions using 3D image fusion; 4) development of multi-purpose digital endoscopy; and, 5) evaluation of new imaging systems for clinical application

• Journal of Biomedical Engineering Research
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• v.44 no.4
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• pp.255-263
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• 2023

Clinical ultrasound (US) is a widely used imaging modality with various clinical applications. However, capturing a large field of view often requires specialized transducers which have limitations for specific clinical scenarios. Panoramic imaging offers an alternative approach by sequentially aligning image sections acquired from freehand sweeps using a standard transducer. To reconstruct a 3D volume from these 2D sections, an external device can be employed to track the transducer's motion accurately. However, the presence of optical or electrical interferences in a clinical setting often leads to incorrect measurements from such sensors. In this paper, we propose a deep learning (DL) framework that enables the prediction of scan trajectories using only US data, eliminating the need for an external tracking device. Our approach incorporates diverse data types, including correlation volume, optical flow, B-mode images, and rawer data (IQ data). We develop a DL network capable of effectively handling these data types and introduce an attention technique to emphasize crucial local areas for precise trajectory prediction. Through extensive experimentation, we demonstrate the superiority of our proposed method over other DL-based approaches in terms of long trajectory prediction performance. Our findings highlight the potential of employing DL techniques for trajectory estimation in clinical ultrasound, offering a promising alternative for panoramic imaging.

• Journal of Internet Computing and Services
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• v.16 no.2
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• pp.109-115
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• 2015

The new medical device technologies for bio-signal information and medical information which developed in various forms have been increasing. Information gathering techniques and the increasing of the bio-signal information device are being used as the main information of the medical service in everyday life. Hence, there is increasing in utilization of the various bio-signals, but it has a problem that does not account for security reasons. Furthermore, the medical image information and bio-signal of the patient in medical field is generated by the individual device, that make the situation cannot be managed and integrated. In order to solve that problem, in this paper we integrated the QR code signal associated with the medial image information including the finding of the doctor and the bio-signal information. bio-signal. System implementation environment for medical imaging devices and bio-signal acquisition was configured through bio-signal measurement, smart device and PC. For the ROI extraction of bio-signal and the receiving of image information that transfer from the medical equipment or bio-signal measurement, .NET Framework was used to operate the QR server module on Window Server 2008 operating system. The main function of the QR server module is to parse the DICOM file generated from the medical imaging device and extract the identified ROI information to store and manage in the database. Additionally, EMR, patient health information such as OCS, extracted ROI information needed for basic information and emergency situation is managed by QR code. QR code and ROI management and the bio-signal information file also store and manage depending on the size of receiving the bio-singnal information case with a PID (patient identification) to be used by the bio-signal device. If the receiving of information is not less than the maximum size to be converted into a QR code, the QR code and the URL information can access the bio-signal information through the server. Likewise, .Net Framework is installed to provide the information in the form of the QR code, so the client can check and find the relevant information through PC and android-based smart device. Finally, the existing medical imaging information, bio-signal information and the health information of the patient are integrated over the result of executing the application service in order to provide a medical information service which is suitable in medical field.

• Journal of Biomedical Engineering Research
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• v.40 no.6
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• pp.230-234
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• 2019

Medical laser equipment using optical energy is used to surgery and treat diseases by destroying and removing tissue. Domestic laser equipment has been used steadily in the skin and cosmetics sectors and has been changed to radiate high-power energy in a wide range to shorten patient treatment time. However, side effects such as burns and damage of normal tissues occurred. To solve this problem, techniques for detecting lesions using an imaging device and selectively radiating the laser have been developed. In this study, we proposed an evaluation method to evaluate the safety and performance of target detection accuracy, laser irradiation accuracy and motion protection device technology derived from product analysis and investigation. Finally, the validity of the evaluation method was evaluated by evaluating the imaging device based laser equipment as the proposed evaluation method.

• Proceedings of the KAIS Fall Conference
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• 2010.05b
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• pp.1227-1229
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• 2010

This paper explains what DTI (Diffusion Tensor Imaging) is and what it does. We will talk about the DTI functions and what type of image it can show, and what areas are using DTI. The tractography and other applications that DTI is being used. In this paper, we explain that DTI is not only useful in medicine but also in botany. We propose to use DTI to study structure and functions of plants.

• Proceedings of the Korean Vacuum Society Conference
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• 2010.08a
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• pp.73-73
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• 2010

Various organic- and bio-conjugated nanoparticles have been studied extensively for biological applications in medical diagnoses and drug delivery systems. Gold nanoparticles (AuNP) and poly(ethylene glycol) (PEG) are known biocompatible materials to be used in vivo and are becoming increasingly important in biomedical applications. In this work, we investigated the stability of PEG-conjugated AuNPs, dialysis and centrifuge effects after synthesis or pegylation of AuNPs as a function of elapsed time by using ToF-SIMS imaging technique along with dynamic light scattering (DLS), UV-visible absorption spectroscopic and statistical analyses. Roughly 15-nm-sized AuNPs were synthesized in a citrate-conjugated form, and then converted into the thiol-terminated PEG (O-[2-(3-Mercaptopropionylamino)ethyl]-O'-methylpolyethyleneglycol, M.W.=5 kDa) form. Based on our data, we will show that ToF-SIMS imaging analysis along with DLS, UV-visible absorption and statistical analyses would be a useful method to evaluate stability of PEG-conjugated AuNPs in various environmental conditions.

• Journal of Life Science
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• v.20 no.11
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• pp.1738-1741
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• 2010

Caliper measurements of tumor volume have been widely used in the assessment of tumors in animal models. However, experiments based on caliper data have resulted in unreliable estimates of tumor growth, due to necrotic areas of tumor mass. To overcome this systematic bias, we engineered a new luciferase-expressing rat prostate cancer cell line (MLL-Luc) that produces bioluminescence from viable cancer cells. MLL-Luc cells showed a strong correlation between bioluminescence intensity and cell number ($R^2$=0.99) and also accurately quantified tumor growth, with reduced bioluminescence signals caused by necrotic cells in a subcutaneous MLL-Luc xenograft model. The accurate quantification of tumor growth with bioluminescence imaging (BLI) was confirmed by a better antitumor effect of combination chemotherapy, compared to that based on caliper measurements with a correlation between the bioluminescence signal and tumor volume ($R^2$=0.84). These data suggest that bioluminescent MLL xenografts are a powerful and quantitative tool for monitoring tumor growth and are useful in evaluating the efficacy of anticancer drugs, with less systematic bias.