• Journal of the Korean Society of Industry Convergence
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• v.26 no.6_3
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• pp.1315-1323
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• 2023

Rehabilitation assistive devices not only assist the rehabilitation therapy and daily life of the disabled and the elderly, but also assist the labor of their caregivers, so various functions are required to improve their quality of life. In this study, a design method considering its practicality is introduced for an active rehabilitation assistive device that can perform both standing and walking assistance by driving various actuators. For this purpose, the force required to assist standing was calculated using statics with the body segmentation method. Also, the overturning stability of the device was verified for various physical conditions and postures. The actuator in the active rehabilitation assistive device was operated by a patient using a graphical user interface in an embedded computer and a touch panel for easy usage. The detailed design was performed for implementation through the help of 3D-CAD and the finite element analysis, and a prototype was produced. Finally, it was proven that the design goal was satisfied by experimental validation.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.43-52
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• 2024

Medical imaginings assume a important part in the analysis of tumors and cerebrospinal fluid (CSF) leak. Magnetic resonance imaging (MRI) is an image segmentation technology, which shows an angular sectional perspective of the body which provides convenience to medical specialists to examine the patients. The images generated by MRI are detailed, which enable medical specialists to identify affected areas to help them diagnose disease. MRI imaging is usually a basic part of diagnostic and treatment. In this research, we propose new techniques using the 4D-MRI image segmentation process to detect the brain tumor in the skull. We identify the issues related to the quality of cerebrum disease images or CSF leakage (discover fluid inside the brain). The aim of this research is to construct a framework that can identify cancer-damaged areas to be isolated from non-tumor. We use 4D image light field segmentation, which is followed by MATLAB modeling techniques, and measure the size of brain-damaged cells deep inside CSF. Data is usually collected from the support vector machine (SVM) tool using MATLAB's included K-Nearest Neighbor (KNN) algorithm. We propose a 4D light field tool (LFT) modulation method that can be used for the light editing field application. Depending on the input of the user, an objective evaluation of each ray is evaluated using the KNN to maintain the 4D frequency (redundancy). These light fields' approaches can help increase the efficiency of device segmentation and light field composite pipeline editing, as they minimize boundary artefacts.

• Journal of the Korean Society of Radiology
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• v.13 no.3
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• pp.489-493
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• 2019

Obesity is increasing in our country due to lack of lifestyle and physical activity. Semi-automatic program is used in existing fat calculation program using computed tomography. Although methods for solving related problems have been proposed, this study proposes an algorithm using morphology operation and We want to solve the problem with a new method that has a simple procedure and a relatively small amount of computation. As a result of repetition of erosion and expansion Automatic fat mass calculation can be done in the future by using the developed partitioning result. By providing an accurate segmentation tool, it will be helpful to doctors and reduce the expense and inspection cost of retesting. through morphology operation, it was found that the problem was solved from the image.Automatic fat mass calculation can be done in the future by using the developed partitioning result. By providing an accurate segmentation tool, it will be helpful to doctors and reduce the expense and inspection cost of retesting.

• Journal of radiological science and technology
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• v.27 no.3
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• pp.19-24
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• 2004

MRI imaging is one of the imaging techniques showing anatomical structures of human body for medical diagnosis, and has been researched in order to provide better quality of anatomical information. In this study, we propose a very useful method to extract an interest areas and how to diagnose necrolysis of femoral neck disease automatically. Regions of femoral neck is set using anatomical features and Hough transform and advantages of both region extension and histogram-based region segmentation method are combined for better region segmentation. As a result of the proposed method, good imaging quality was obtained for femoral neck with both normal and severe necrosis as well as for femoral neck in early stage of necrolysis.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.11
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• pp.2051-2057
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• 2007

In Oriental medicine, the status of a tongue is the important indicator to diagnose one's health like physiological and clinicopathological changes of inner parts of the body. The method of tongue diagnosis is not only convenient but also non-invasive and widely used in Oriental medicine. However, tongue diagnosis is affected by examination circumstances a lot like a light source, patient's posture and doctor's condition. To develop an automatic tongue diagnosis system for an objective and standardized diagnosis, segmenting a tongue is inevitable but difficult since the colors of a tongue, lips and skin in a mouth are similar. The proposed method includes preprocessing, graph-based over-segmentation, detecting positions with a local minimum over shading, detecting edge with color difference and estimating edge geometry from the probable structure of a tongue, where preprocessing performs down-sampling to reduce computation time, histogram equalization and edge enhancement. A tongue was segmented from a face image with a tongue from a digital tongue diagnosis system by the proposed method. According to three oriental medical doctors' evaluation, it produced the segmented region to include effective information and exclude a non-tongue region. It can be used to make an objective and standardized diagnosis.

• Journal of the Korea Computer Graphics Society
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• v.27 no.4
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• pp.1-9
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• 2021

Segmenting the compartments of neurons, such as axons, dendrites, and cell bodies, is helpful in the analysis of neurological phenomena. Recently, there have been several studies to segment the compartments through deep learning. However, this approach has the potential to include errors in the results due to noise in data and differences between training data and actual data. Therefore, in order to use these for actual analysis, it is essential to proofread the results. The proofreading process requires a lot of effort and time because an expert must perform it manually. We propose an interactive neuron structure proofreading method that can more easily correct errors in the segmentation results of a deep learning. This method proofread the neuron structure based on the characteristics of the neuron with structural consistency, so that a high-accuracy proofreading result can be obtained with less interaction.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.4
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• pp.40-50
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• 2019

In recent years, it is important to visualize an accurate human body model for the low-end system in the medical imaging field where augmented reality technology and virtual reality technology are used. Decreasing the geometry of a model causes a difference from the original shape and considers the difference as an error. So, the error should be minimized while reducing geometry. In this study, the organ areas of a human body in the tomographic images such as CT or MRI is segmented and 3D geometric model is generated, thereby implementing the reconstruction method of multiple resolution level-of-detail model. In the experiment, a virtual reality platform was constructed to verify the shape of the reconstructed model, targeting the spine area. The 3D human body model and patient information can be verified using the virtual reality platform.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.6C
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• pp.593-603
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• 2009

In this paper, we propose a new integrated computer vision system designed to track multiple human beings and extract their silhouette with an active stereo camera. The proposed system consists of three modules: detection, tracking and silhouette extraction. Detection was performed by camera ego-motion compensation and disparity segmentation. For tracking, we present an efficient mean shift based tracking method in which the tracking objects are characterized as disparity weighted color histograms. The silhouette was obtained by two-step segmentation. A trimap is estimated in advance and then this was effectively incorporated into the graph cut framework for fine segmentation. The proposed system was evaluated with respect to ground truth data and it was shown to detect and track multiple people very well and also produce high quality silhouettes. The proposed system can assist in gesture and gait recognition in field of Human-Robot Interaction (HRI).

• Korean Journal of Human Ecology
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• v.24 no.4
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• pp.555-569
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• 2015

During a design process of a protective equipment for sports activities, minimizing movement restrictions is important for enhancing its functions particularly for protection. This study presents a three-dimensional(3D) modeling methodology for designing baseball catcher's leg guards that will allow maximum possible performance, while providing necessary protection. 3D scanning is performed on three positions frequently used by a catcher during the course of a game by putting markings on the subject's legs at 3cm intervals : a standing, a half squat with knees bent to 90 degrees and 120 degrees of knee flexion. Using data obtained from the 3D scan, we analyzed the changes in skin length, radii of curvatures, and cross-sectional shapes, depending on the degree of knee flexion. The results of the analysis were used to decide an on the ideal segmentation of the leg guards by modeling posture. Knee flexions to 90 degrees and to $120^{\circ}$ induced lengthwise extensions than a standing. In particular, the vertical length from the center of the leg increases to a substantially higher degree when compared to those increased from the inner and the outer side of the leg. The degree of extension is varied by positions. Therefore, the leg guards are segmented at points where the rate of increase changed. It resulted in a three-part segmentation of the leg guards at the thigh, the knee, and the shin. Since the 120 degree knee-flexion posture can accommodate other positions as well, the related 3D data are used for modeling Leg Guard (A) with the loft method. At the same time, Leg Guard (B) was modeled with two-part segmentation without separating the knee and the shin as in existing products. A biomechanical analysis of the new design is performed by simulating a 3D dynamic analysis. The analysis revealed that the three-part type (A) leg guards required less energy from the human body than the two-part type (B).

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2006.04a
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• pp.177-180
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• 2006

In this paper we proposed a method of automatic point segmentation acquired by 2D laser scanner to recognize moving objects. Recently, Laser scanner is noticed as a new method in the field of close range 3D modeling. But the majority of the researches are pointed on precise 3D modeling of static objects using expensive 3D laser scanner. 2D laser scanner is relatively cheap and can obtain 2D coordinate information of moving object's surface or can be utilized as 3D laser scanner by rotating the system body. In these reasons, some researches are in progress, which are adopting 2D laser scanner to robot control systems or detection of objects moving along linear trajectory. In our study, we automatically segmented point data of 2D laser scanner thus we could recognize each of the object passing through a section.