• Current Optics and Photonics
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• v.7 no.6
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• pp.692-700
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• 2023

We present a method for improving the accuracy of the modal wavefront reconstruction in the radial shearing interferometers (RSIs). Our approach involves expanding the reduced radial terms of Zernike polynomials to high-order, which enables more precise reconstruction of the wavefront aberrations with high-spatial frequency. We expanded the reduced polynomials up to infinite order with symbolic variables of the radius, shearing amount, and transformation matrix elements. For the simulation of the modal wavefront reconstruction, we generated a target wavefront subsequently, magnified and measured wavefronts were generated. To validate the effectiveness of the high-order Zernike polynomials, we applied both low- and high-order polynomials to the wavefront reconstruction process. Consequently, the peak-to-valley (PV) and RMS errors notably decreased with values of 0.011λ and 0.001λ, respectively, as the order of the radial Zernike polynomial increased.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.1
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• pp.38-46
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• 2008

Key-frame selection algorithm is defined as the process of selecting a necessary images for 3D reconstruction from the uncalibrated images. Also, camera calibration of images is necessary for 3D reconstuction. In this paper, we propose a new method of Key-frame selection with the minimal error for camera calibration. Using the full-auto-calibration, we estimate camera parameters for all selected Key-frames. We remove the false matching using the fundamental matrix computed by algebraic deviation from the estimated camera parameters. Finally we obtain 3D reconstructed data. Our experimental results show that the proposed approach is required rather lower time costs than others, the error of reconstructed data is the smallest. The elapsed time for estimating the fundamental matrix is very fast and the error of estimated fundamental matrix is similar to others.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5860-5876
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• 2018

A single snapshot data can only provide limited amount of information so that the rank of covariance matrix is not full, which is not adopted to complete the parameter estimation directly using the traditional super-resolution method. Aiming at solving the problem, a joint time delay and angle estimation using matrix pencil method based on information reconstruction vector for orthogonal frequency division multiplexing (OFDM) signal is proposed. Firstly, according to the channel frequency response vector of each array element, the algorithm reconstructs the vector data with delay and angle parameter information from both frequency and space dimensions. Then the enhanced data matrix for the extended array element is constructed, and the parameter vector of time delay and angle is estimated by the two-dimensional matrix pencil (2D MP) algorithm. Finally, the joint estimation of two-dimensional parameters is accomplished by the parameter pairing. The algorithm does not need a pseudo-spectral peak search, and the location of the target can be determined only by a single receiver, which can reduce the overhead of the positioning system. The theoretical analysis and simulation results show that the estimation accuracy of the proposed method in a single snapshot and low signal-to-noise ratio environment is much higher than that of Root Multiple Signal Classification algorithm (Root-MUSIC), and this method also achieves the higher estimation performance and efficiency with lower complexity cost compared to the one-dimensional matrix pencil algorithm.

• Investigative Magnetic Resonance Imaging
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• v.25 no.4
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• pp.293-299
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• 2021

Purpose: To accelerate magnetic resonance fingerprinting (MRF) by developing a flexible deep learning reconstruction method. Materials and Methods: Synthetic data were used to train a deep learning model. The trained model was then applied to MRF for different organs and diseases. Iterative reconstruction was performed outside the deep learning model, allowing a changeable encoding matrix, i.e., with flexibility of choice for image resolution, radiofrequency coil, k-space trajectory, and undersampling mask. In vivo experiments were performed on normal brain and prostate cancer volunteers to demonstrate the model performance and generalizability. Results: In 400-dynamics brain MRF, direct nonuniform Fourier transform caused a slight increase of random fluctuations on the T2 map. These fluctuations were reduced with the proposed method. In prostate MRF, the proposed method suppressed fluctuations on both T1 and T2 maps. Conclusion: The deep learning and iterative MRF reconstruction method described in this study was flexible with different acquisition settings such as radiofrequency coils. It is generalizable for different in vivo applications.

• Archives of Plastic Surgery
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• v.43 no.6
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• pp.523-528
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• 2016

Background The use of acellular dermal matrix (ADM) in implant-based immediate breast reconstruction has been increasing. The current ADMs available for breast reconstruction are offered as aseptic or sterile. No published studies have compared aseptic and sterile ADM in implant-based immediate breast reconstruction. The authors performed a retrospective study to evaluate the outcomes of aseptic versus sterile ADM in implant-based immediate breast reconstruction. Methods Implant-based immediate breast reconstructions with ADM conducted between April 2013 and January 2016 were included. The patients were divided into 2 groups: the aseptic ADM (AlloDerm) group and the sterile ADM (MegaDerm) group. Archived records were reviewed for demographic data and postoperative complication types and frequencies. The complications included were infection, flap necrosis, capsular contracture, seroma, hematoma, and explantation for any cause. Results Twenty patients were reconstructed with aseptic ADM, and 68 patients with sterile ADM. Rates of infection (15.0% vs. 10.3%), flap necrosis (5.0% vs. 7.4%), capsular contracture (20.0% vs. 14.7%), seroma (10.0% vs. 14.7%), hematoma (0% vs. 1.5%), and explantation (10.0% vs. 8.8%) were not significantly different in the 2 groups. Conclusions Sterile ADM did not provide better results regarding infectious complications than aseptic ADM in implant-based immediate breast reconstruction.

• Archives of Plastic Surgery
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• v.46 no.3
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• pp.204-213
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• 2019

Background In implant-based breast reconstruction, acellular dermal matrix (ADM) is essential for supporting the inferolateral pole. Recent studies have compared non-sterilized freeze-dried ADM and sterilized pre-hydrated ADM, but have not assessed whether differences were attributable to factors related to sterile processing or packaging. This study was conducted to compare the clinical outcomes of breast reconstruction using two types of sterile-processed ADMs. Methods Through a retrospective chart review, we analyzed 77 consecutive patients (85 breasts) who underwent tissue expander/implant breast reconstruction with either freeze-dried ADM (35 breasts) or pre-hydrated ADM (50 breasts) from March 2016 to February 2018. Demographic variables, postoperative outcomes, and operative parameters were compared between freeze-dried and pre-hydrated ADM. Biopsy specimens were obtained for histologic analysis. Results We obtained results after adjusting for variables found to be significant in univariate analyses. The total complication rate for freeze-dried and pre-hydrated ADMs was 25.7% and 22.0%, respectively. Skin necrosis was significantly more frequent in the freeze-dried group than in the pre-hydrated group (8.6% vs. 4.0%, P=0.038). All other complications and operative parameters showed no significant differences. In the histologic analysis, collagen density, inflammation, and vascularity were higher in the pre-hydrated ADM group (P=0.042, P=0.006, P=0.005, respectively). Conclusions There are limited data comparing the outcomes of tissue expander/implant breast reconstruction using two types of sterile-processed ADMs. In this study, we found that using pre-hydrated ADM resulted in less skin necrosis and better integration into host tissue. Pre-hydrated ADM may therefore be preferable to freeze-dried ADM in terms of convenience and safety.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.343-364
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• 2021

In the 5G era, the communication networks tend to be ultra-densified, which will improve the accuracy of indoor positioning and further improve the quality of positioning service. In this study, we propose an indoor three-dimensional (3D) dynamic reconstruction fingerprint matching algorithm (DSR-FP) in a 5G ultra-dense network. The first step of the algorithm is to construct a local fingerprint matrix having low-rank characteristics using partial fingerprint data, and then reconstruct the local matrix as a complete fingerprint library using the FPCA reconstruction algorithm. In the second step of the algorithm, a dynamic base station matching strategy is used to screen out the best quality service base stations and multiple sub-optimal service base stations. Then, the fingerprints of the other base station numbers are eliminated from the fingerprint database to simplify the fingerprint database. Finally, the 3D estimated coordinates of the point to be located are obtained through the K-nearest neighbor matching algorithm. The analysis of the simulation results demonstrates that the average relative error between the reconstructed fingerprint database by the DSR-FP algorithm and the original fingerprint database is 1.21%, indicating that the accuracy of the reconstruction fingerprint database is high, and the influence of the location error can be ignored. The positioning error of the DSR-FP algorithm is less than 0.31 m. Furthermore, at the same signal-to-noise ratio, the positioning error of the DSR-FP algorithm is lesser than that of the traditional fingerprint matching algorithm, while its positioning accuracy is higher.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.29 no.1 s.232
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• pp.87-94
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• 2005

A computer code for Electrical Capacitance Tomography (ECT) is developed to sense the cross sectional phase distribution of two-phase flow in the rectangular pipe in which the tomography sensor furnished by the insulated wall, electrodes, and electric field screen. The computer code had two steps for the image reconstruction. In the forward projection step, the sensitivity matrix was constructed based on the electric field calculated by the finite difference method. In the backward projection step, the sensitivity matrix and the measured capacitances were used to reconstruct the cross sectional image. Several algorithms including LBP, TR, ITR, and PLI were employed to find the proper one for the two-phase flow analysis. Since the dielectric constant of the water in two-phase flow is sensitive to the thermal parameter such as, temperature and pressure, the developed code was evaluated to find their accuracy, speed of calculation, and sensitivity to the variation of the dielectric constant. It was found that the iterative methods are superior to the direct methods for the image reconstruction, and the PLI method was the best in the variation of the dielectric constants.

• Journal of Biomedical Engineering Research
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• v.35 no.5
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• pp.142-150
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• 2014

The key to model-based iterative reconstruction (MBIR) algorithms for transmission computed tomography lies in the ability to accurately model the data formation process from the emitted photons produced in the transmission source to the measured photons at the detector. Therefore, accurately modeling the system matrix that accounts for the data formation process is a prerequisite for MBIR-based algorithms. In this work we compared quantitative performance of the three representative ray-driven methods for calculating the system matrix; the ray-tracing method (RTM), the distance-driven method (DDM), and the strip-area based method (SAM). We implemented the ordered-subsets separable surrogates (OS-SPS) algorithm using the three different models and performed simulation studies using a digital phantom. Our experimental results show that, in spite of the more advanced features in the SAM and DDM, the traditional RTM implemented in the OS-SPS algorithm with an edge-preserving regularizer out-performs the SAM and DDM in restoring complex edges in the underlying object. The performance of the RTM in smooth regions was also comparable to that of the SAM or DDM.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.2
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• pp.367-374
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• 2022

A sampling set selection algorithm is proposed to reconstruct original graph signals from the sampled signals generated on the nodes in the sampling set. Instead of directly minimizing the reconstruction error, we focus on minimizing the upper bound on the reconstruction error to reduce the algorithm complexity. The metric is manipulated by using QR factorization to produce the upper triangular matrix and the analytic result is presented to enable a greedy selection of the next nodes at iterations by using the diagonal entries of the upper triangular matrix, leading to an efficient sampling process with reduced complexity. We run experiments for various graphs to demonstrate a competitive reconstruction performance of the proposed algorithm while offering the execution time about 3.5 times faster than one of the previous selection methods.