• KIPS Transactions on Software and Data Engineering
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• v.4 no.5
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• pp.231-240
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• 2015

Medical imagery require to protect the privacy with preserving the quality of the original contents. Therefore, reversible watermarking is a solution for this purpose. Previous researches have focused on general imagery and achieved high capacity and high quality. However, they raise a distortion over entire image and hence are not applicable to medical imagery which require to preserve the quality of the objects. In this paper, we propose a novel reversible watermarking for medical imagery, which preserve the quality of the objects and achieves high capacity. First, object and background region is segmented and then predicted error histogram-based reversible watermarking is applied for each region. For the efficient watermark embedding with small distortion in the object region, the embedding level at object region is set as low while the embedding level at background region is set as high. In experiments, the proposed algorithm is compared with the previous predicted error histogram-based algorithm in aspects of embedding capacity and perceptual quality. Results support that the proposed algorithm performs well over the previous algorithm.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.5
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• pp.39-54
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• 2012

Picture Archiving and Communication System (PACS) has been planted as one of the key infrastructures with an overall improvement in standards of medical informationization and the stream of digital hospitalization in recent days. The kind and data of digital medical imagery are also increasing rapidly in volume. This trend emphasizes the medical image compression for storing large-scale medical image data. Digital Imaging and Communications in Medicine (DICOM), de facto standard in digital medical imagery, specifies Run Length Encode (RLE), which is the typical lossless data compressing technique, for the medical image compression. However, the RLE is not appropriate approach for medical image data with bilateral symmetry of the human organism. we suggest two preprocessing algorithms that detect interested area, the minimum bounding rectangle, in a medical image to enhance data compression efficiency and that re-code image pixel values to reduce data size according to the symmetry characteristics in the interested area, and also presents an improved image compression technique for brain CT imagery with high bilateral symmetry. As the result of experiment, the suggested approach shows higher data compression ratio than the RLE compression in the DICOM standard without detecting interested area in images.

• Journal of International Academy of Physical Therapy Research
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• v.11 no.1
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• pp.2005-2011
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• 2020

Background: Motor imagery is the mental representation of an action without overt movement or muscle activation. However, few previous studies have demonstrated motor imagery training effects as an objective assessment tool in patients with early stroke. Objective: To investigate the effect of motor imagery training on Somatosensory Evoked Potentials (SSEP) and upper limb function of stroke patients. Design: A quasi-experimental study. Methods: Twenty-four patients with stroke were enrolled in this study. All subjects were assigned to the experimental or control group. All participants received traditional occupational therapy for 30 minutes, 5 times a week. The experimental group performed an additional task of motor imagery training (MIT) 20 minutes per day, 5 days a week, for 4 weeks. Both groups were assessed using the SSEP amplitude, Fugl-Meyer assessment of upper extremity (FMA UE) and Wolf motor function test. Results: After the intervention, the experimental group showed significant improvement in SSEP amplitude and FMA UE than did the control group. Conclusion: These findings suggest that the MIT effectively improve the SSEP and upper limb function of stroke patients.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.246-251
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• 1998

This paper proposes a new building segmentation method from 1m resolution imagery using an Active Contour Model, known as "Balloons". The original balloons, which was designed by Cohen(Cohen, 1991) to extract features from medical images, are modified for building segmentation. The proposed method consists of two phases. Firstly, building boundaries are extracted by balloons with a given position on buildings from an operator. Since balloons actively adjust their shapes according to the boundaries, there is no more shape limitations on detecting buildings. Secondly, buildings are segmented by connecting the corners detected from the building boundaries, because most buildings, which are man-made objects, are effectively described by polygons. The test results show that most buildings are segmented efficiently and easily. The proposed method is new and timely as 1m resolution spaceborne imagery will be available in the very near future. The proposed method can be used fur operational building segmentation from such imagery.

• Archives of Plastic Surgery
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• v.42 no.5
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• pp.635.1-635.1
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• 2015

• The Journal of Korean Physical Therapy
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• v.25 no.5
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• pp.273-281
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• 2013

Purpose: The purpose of this study is to determine the effect of motor imagery training on residual upper extremity strength and activities of daily living of chronic cervical spinal cord injury patients. Methods: Twelve ASIA A B patients, who had more than a 12-month duration of illness and C5 or 6 motor nerve injury level, were randomly divided into experimental group (n=6) and control group (n=6). Patients in the experimental group performed motor imagery training for five minutes prior to general muscle strengthening training, while those in the control group performed general muscle strengthening training only. The training was performed five times per week, 30 minutes per day, for a period of four weeks. General muscle strengthening training consisted of a progressive resistive exercise for residual upper extremity. Motor imagery training consisted of imagining this task performance. Before and after the training, EMG activity using BTS Pocket Electromyography and Spinal Cord Independent Measure III(SCIM III) were compared and analyzed. Results: The residual upper extremity muscle strengths showed improvement in both groups after training. Comparison of muscle strength improvement between the two groups showed a statistically significant improvement in the experimental group compared to the control group (p<0.05). SCIM III measurements showed significant improvement in the scores for Self-care and Transfer items in the experimental group. Conclusion: Motor imagery training was more effective than general muscle strengthening training in improving the residual upper extremity muscle strength and activities of daily living of patients with chronic cervical spinal cord injury.

• Journal of Biomedical Engineering Research
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• v.43 no.6
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• pp.375-381
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• 2022

Brain-computer interface (BCI) is a technology that allows users with motor disturbance to control machines by brainwaves without a physical controller. Motor imagery (MI)-BCI is one of the popular BCI techniques, but it needs a long calibration time for users to perform a mental task that causes high fatigue to the users. MI is reported as showing a similar neural mechanism as motor execution (ME) and motor observation (MO). However, integrative investigations of these three tasks are rarely conducted. In this study, we propose a new paradigm that incorporates three tasks (MI, ME, and MO) and conducted a comparative analysis. For this study, we collected Electroencephalograms (EEG) of motor imagery/execution/observation from 28 healthy subjects and investigated alpha event-related (de)synchronization (ERD/ERS) and classification accuracy (left vs. right motor tasks). As result, we observed ERD and ERS in MI, MO and ME although the timing is different across tasks. In addition, the MI showed strong ERD on the contralateral hemisphere, while the MO showed strong ERD on the ipsilateral side. In the classification analysis using a Riemannian geometry-based classifier, we obtained classification accuracies as MO (66.34%), MI (60.06%) and ME (58.57%). We conclude that there are similarities and differences in fundamental neural mechanisms across the three motor tasks and that these results could be used to advance the current MI-BCI further by incorporating data from ME and MO.

• Journal of Biomedical Engineering Research
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• v.32 no.4
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• pp.295-304
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• 2011

In this study, we evaluated the EEG based BCI algorithm using common spatial pattern to find realistic applicability using neurofeedback EEG based BCI algorithm - EEG mode, feature vector calculation, the number of selected channels, 3 types of classifier, window size is evaluated for 10 subjects. The experimental results have been evaluated depending on conditioned experiment whether neurofeedback is used or not In case of using neurofeedback, a few subjects presented exceptional but general tendency presented the performance improvement Through this study, we found a motivation of development for the specific classifier based BCI system and the assessment evaluation system. We proposed a need for an optimized algorithm applicable to the robust motor imagery evaluation system with more useful functionalities.

• Journal of Biomedical Engineering Research
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• v.30 no.5
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• pp.428-437
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• 2009

The Performance research about EEG-BCI algorithm in BCI-naive subjects is very important for evaluating the applicability to the public. We analyzed the result of the performance evaluation experiment about the EEG-BCI algorithm in BCI-naive subjects on three different aspects. The EEG-BCI algorithm used in this paper is composed of the common spatial pattern(CSP) and the least square linear classifier. CSP is used for obtaining the characteristic of event related desynchronization, and the least square linear classifier classifies the motor imagery EEG data of the left hand or right hand. The performance evaluation experiments about EEG-BCI algorithm is conducted for 40 men and women whose age are 23.87${\pm}$2.47. The performance evaluation about EEG-BCI algorithm in BCI-naive subjects is analyzed in terms of the accuracy, the relation between the information transfer rate and the accuracy, and the performance changes when the different types of cue were used in the training session and testing session. On the result of experiment, BCI-naive group has about 20% subjects whose accuracy exceed 0.7. And this results of the accuracy were not effected significantly by the types of cue. The Information transfer rate is in the inverse proportion to the accuracy. And the accuracy shows the severe deterioration when the motor imagery is less then 2 seconds.

• ETRI Journal
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• v.28 no.2
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• pp.162-174
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• 2006

Several photogrammetric and geographic information system applications such as surface matching, object recognition, city modeling, environmental monitoring, and change detection deal with multiple versions of the same surface that have been derived from different sources and/or at different times. Surface registration is a necessary procedure prior to the manipulation of these 3D datasets. This need is also applicable in the field of medical imaging, where imaging modalities such as magnetic resonance imaging (MRI) can provide temporal 3D imagery for monitoring disease progression. This paper will present a general automated surface registration procedure that can establish correspondences between conjugate surface elements. Experimental results using light detection and ranging (LIDAR) and MRI data will verify the feasibility, robustness, and accuracy of this approach.