• The Journal of Korean Association of Computer Education
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• v.5 no.4
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• pp.43-52
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• 2002

A theory of binary wavelets which are performed over binary field has been recently proposed. Binary wavelet transform (BWT) of binary images can be used as an alternative to the real-valued wavelet transform of binary images in image processing applications such as compression, edge detection, and recognition. The BWT, however, requires large amount of computations for binary wavelet reconstruction since its operation is accomplished by matrix multiplication. In this paper, an efficient binary wavelet reconstruction method which utilizes filtering operation instead of matrix multiplication is presented. Experimental results show that the proposed algorithm can significantly reduce the computational complexity of the BWT. For the reconstruction of an $N{\times}N$ image, the proposed technique requires only $2MN^2$ multiplications and $2N(M-1)^2$ additions when the filter length M, while the BWT needs $2N^3$ multiplications and $2N(N-1)^2$ additions.

• Journal of IKEEE
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• v.19 no.1
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• pp.33-40
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• 2015

Inverse problem in electrical impedance tomography (EIT) is highly ill-posed therefore prior information is used to mitigate the ill-posedness. Regularization methods are often adopted in solving EIT inverse problem to have satisfactory reconstruction performance. In solving the EIT inverse problem, iterative Gauss-Newton method is generally used due to its accuracy and fast convergence. However, its performance is still suboptimal and mainly depends on the selection of regularization parameter. Although, there are few methods available to determine the regularization parameter such as L-curve method they are sometimes not applicable for all cases. Moreover, regularization parameter is a scalar and it is fixed during iteration process. Therefore, in this paper, a novel method is used to determine the regularization parameter to improve reconstruction performance. Conductivity norm is calculated at each iteration step and it used to obtain the regularization parameter which is a diagonal matrix in this case. The proposed method is applied to human thorax imaging and the reconstruction performance is compared with traditional methods. From numerical results, improved performance of proposed method is seen as compared to conventional methods.

• Archives of Plastic Surgery
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• v.42 no.3
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• pp.321-326
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• 2015

Background The acellular dermal matrix (ADM)-assisted breast reconstruction technique is widely known, but discouraging results due to early postoperative complications have been reported. As the literature identifies seroma as the most common issue after breast surgery without identifying its pathogenesis, we aimed to report the trend of postoperative daily serum collection after ADM-assisted breast reconstruction and compare it with data in the literature in order to discover more about this little-known topic. Methods A retrospective study on 28 consecutive patients who received ADM-assisted breast reconstruction between February 2013 and February 2014 was performed. In order to reduce the number of variables that could affect serum production, only one brand of ADM was used and all tissues were handled gently and precisely. The daily drainage volume was recorded per patient during the first four days of hospitalization. Likewise, postoperative complications were noted during routine follow-up. Results In total, five (17.9%) bilateral and 23 (82.1%) unilateral ADM-assisted breast reconstructions (33 implants) were performed. The mean age, body mass index, and length of hospital stay were 53.6 years, $21.3kg/m^2$, and 4.5 days, respectively. One major complication led to implant loss (3.0%), and nine minor complications were successfully treated with ambulatory surgery (27.3%). Serum collection linearly decreased after 24 hours postoperatively. Conclusions Daily drainage decreased following the theoretical decline of acute inflammation. In concordance with the literature, daily serum production may not be related to the use of ADM.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.3C
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• pp.419-425
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• 2004

This paper presents a new method which is calculated to use only three vanishing points in order to compute the dimensions of object and its pose from a single image of perspective projection taken by a camera. Our approach is to only compute three vanishing points without informations such as the focal length and rotation matrix from images in the case of perspective projection. We assume that the object can be modeled as a linear function of a dimension vector v. The input of reconstruction is a set of correspondences between features in the model and features in the image. To minimize each the dimensions of the parameterized models, this reconstruction of optimization can be solved by standard nonlinear optimization techniques with a multi-start method which generates multiple starting points for the optimizer by sampling the parameter space uniformly.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.12
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• pp.2943-2948
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• 2015

Run 3D reconstruction using a single camera, based on the information, we are advancing research on driving assistance apparatus or can be informed how to pass the obstacle existing ahead the driver. As a result depth information falls but it is possible to provide information that can pass through an obstacle on the straight. For 3D reconstruction by measuring the internal parameters, it calculates the Fundamental matrix and matching to find the feature points obtained by executing the triangulation on the basis of this. When the through experiments try to confirm the results, the depth information is present error information in the X and Y axes which can determine whether or not to pass through an obstacle has reliability.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.439-441
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• 2002

The aim of this study is to reconstruct the 3D target volume from multiple projection images. It was assumed that we were already aware of the target position exactly, and all processes were performed in Target Coordinates whose origin was the center of the target. We used six projections: two projections were used to make a Reconstruction Box and four projections were for image acquisition. Reconstruction Box was made up of voxels of 3D matrix. Projection images were transformed into 3D volume in this virtual box using geometrical based back-projection method. Algorithm was applied to an ellipsoid model and horse-shoe shaped model. Projection images were created using C program language by geometrical method and reconstruction was also accomplished using C program language and Matlab(The Mathwork Inc., USA). For ellipsoid model, reconstructed volume was slightly overestimated but target shape and position was proved to be correct. For horse-shoe shaped model, reconstructed volume was somewhat different from original target model but there was a considerable improvement in target volume determination.

• Journal of the Korean Society of Radiology
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• v.9 no.7
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• pp.487-493
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• 2015

The reconstruction on the computed tomography requires much time for calculation. The calculation time rapidly increases with enlarging matrix size for improving image quality. Multi-core processor, multi-core CPU, has widely used nowadays and has provided the reduction of the calculation time through multi-threads. In this study, the calculation time of the reconstruction process would improved using multi-threads based on the multi-core processor. The Pthread and the OpenMP used for multi-threads were used in convolution and back projection steps that required much time in the reconstruction. The Pthread and the OpenMP showed similar results in the speedup and the efficiency.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37A no.12
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• pp.1122-1132
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• 2012

Compressed sensing has been applied to many fields such as images, speech signals, radars, etc. It has been mainly applied to stationary signals, and reconstruction error could grow as compression ratios are increased by decreasing measurements. To resolve the problem, speech signals are divided into frames and processed in parallel. The frames are made sparse by dictionary learning, and adaptive compressed sensing is applied which designs the compressed sensing reconstruction matrix adaptively by using the difference between the sparse coefficient vector and its reconstruction. Through the proposed method, we could see that fast and accurate reconstruction of non-stationary signals is possible with compressed sensing.

• Archives of Plastic Surgery
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• v.46 no.1
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• pp.79-83
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• 2019

Robotic surgery facilitates surgical procedures by employing flexible arms with multiple degrees of freedom and providing high-quality 3-dimensional imaging. Robot-assisted nipple-sparing mastectomy with immediate reconstruction is currently performed to avoid breast scars. Four patients with invasive ductal carcinoma underwent robot-assisted nipple-sparing mastectomy and immediate robot-assisted expander insertion. Through a 6-cm incision along the anterior axillary line, sentinel lymph node biopsy and nipple-sparing mastectomy were performed by oncologic surgeons. The pectoralis major muscle was elevated, an acellular dermal matrix (ADM) sling was created with robotic assistance, and an expander was inserted into the subpectoral, sub-ADM pocket. No patients had major complications such as hematoma, seroma, infection, capsular contracture, or nipple-areolar necrosis. The mean operation time for expander insertion was 1 hour and 20 minutes, and it became shorter with more experience. The first patient completed 2-stage prosthetic reconstruction and was highly satisfied with the unnoticeable scar and symmetric reconstruction. We describe several cases of immediate robot-assisted prosthetic breast reconstruction. This procedure is a feasible surgical option for patients who want to conceal surgical scars.

• Archives of Plastic Surgery
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• v.48 no.2
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• pp.179-184
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• 2021

Women attach great importance to the presence of a three-dimensional nipple upon completion of the breast reconstruction process. To meet patients' expectations, nipple-areolar complex reconstruction should achieve symmetry in position, size, shape, texture, and color, as well as minimizing donor-site morbidity. However, it is well known that regardless of the reconstructive technique, loss of nipple projection can be reasonably expected. We developed and evaluated a quick, simple, and innovative technique using injectable Integra Flowable Wound Matrix to increase nipple projection after reconstruction. Twenty breast cancer patients who underwent nipple reconstruction resulting in unsatisfactory projection were enrolled in our retrospective study. Nipple projection was measured at the time of surgery and after 6 and 12 months. A visual analogue scale was used to assess patients' satisfaction. Our technique yielded reliable results in terms of the long-lasting maintenance of nipple projection. This method is high-priced, but cost-effective, since one kit may suffice for three patients. Furthermore, our patients were very appreciative of this technique as a single-step, minimally invasive, painless procedure with no reported necessity of re-intervention.