• Applied Microscopy
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• 제46권4호
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• pp.176-178
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• 2016

Efficient neural circuit reconstruction requires sufficient lateral and axial resolution to resolve individual synapses and map a large enough volume of brain tissue to reveal the molecular identity and origin of these synapses. Sparse circuit reconstruction using array tomography meets many of these requirements but also has some limitations. In this minireview, the advantages and disadvantages of applicable imaging techniques will be discussed.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 1999년도 KOBA 방송기술 워크샵 KOBA Broadcasting Technology Workshop
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• pp.103.2-110
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• 1999

Facial model reconstruction and surgical simulation are essential parts in the computer-aided surgical system. Plastic surgeons use it to design appropriate repair plans and procedures before actual surgery is operated. In this work, the exploration of 3-D metamorphosis to them presents new results in these two parts.

• ETRI Journal
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• 제37권6호
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• pp.1251-1258
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• 2015

We investigate an image recovery method for sparse-view computed tomography (CT) using an iterative shrinkage algorithm based on a second-order approach. The two-step iterative shrinkage-thresholding (TwIST) algorithm including a total variation regularization technique is elucidated to be more robust than other first-order methods; it enables a perfect restoration of an original image even if given only a few projection views of a parallel-beam geometry. We find that the incoherency of a projection system matrix in CT geometry sufficiently satisfies the exact reconstruction principle even when the matrix itself has a large condition number. Image reconstruction from fan-beam CT can be well carried out, but the retrieval performance is very low when compared to a parallel-beam geometry. This is considered to be due to the matrix complexity of the projection geometry. We also evaluate the image retrieval performance of the TwIST algorithm -sing measured projection data.

• Smart Structures and Systems
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• 제25권3호
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• pp.369-384
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• 2020

A wavefield sparse reconstruction technique based on compressed sensing is developed in this work to dramatically reduce the number of measurements. Firstly, a severely underdetermined representation of guided wavefield at a snapshot is established in the spatial domain. Secondly, an optimal compressed sensing model of guided wavefield sparse reconstruction is established based on l₁-norm penalty, where a suite of discrete cosine functions is selected as the dictionary to promote the sparsity. The regular, random and jittered undersampling schemes are compared and selected as the undersampling matrix of compressed sensing. Thirdly, a gradient projection method is employed to solve the compressed sensing model of wavefield sparse reconstruction from highly incomplete measurements. Finally, experiments with different excitation frequencies are conducted on an aluminum plate to verify the effectiveness of the proposed sparse reconstruction method, where a scanning laser Doppler vibrometer as the true benchmark is used to measure the original wavefield in a given inspection region. Experiments demonstrate that the missing wavefield data can be accurately reconstructed from less than 12% of the original measurements; The reconstruction accuracy of the jittered undersampling scheme is slightly higher than that of the random undersampling scheme in high probability, but the regular undersampling scheme fails to reconstruct the wavefield image; A quantified mapping relationship between the sparsity ratio and the recovery error over a special interval is established with respect to statistical modeling and analysis.

• 대한치과교정학회지
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• 제53권2호
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• pp.77-88
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• 2023

Objective: To develop a method for generating three-dimensional (3D) digital models of the periodontal ligament (PDL) using 3D cone-beam computed tomography (CBCT) reconstruction and to evaluate the accuracy and agreement of the 3D PDL models in the measurement of periodontal bone loss. Methods: CBCT data collected from four patients with skeletal Class III malocclusion prior to periodontal surgery were reconstructed at three voxel sizes (0.2 mm, 0.25 mm, and 0.3 mm), and 3D tooth and alveolar bone models were generated to obtain digital PDL models for the maxillary and mandibular anterior teeth. Linear measurements of the alveolar bone crest obtained during periodontal surgery were compared with the digital measurements for assessment of the accuracy of the digital models. The agreement and reliability of the digital PDL models were analyzed using intra- and interexaminer correlation coefficients and Bland-Altman plots. Results: Digital models of the maxillary and mandibular anterior teeth, PDL, and alveolar bone of the four patients were successfully established. Relative to the intraoperative measurements, linear measurements obtained from the 3D digital models were accurate, and there were no significant differences among different voxel sizes at different sites. High diagnostic coincidence rates were found for the maxillary anterior teeth. The digital models showed high intra- and interexaminer agreement. Conclusions: Digital PDL models generated by 3D CBCT reconstruction can provide accurate and useful information regarding the alveolar crest morphology and facilitate reproducible measurements. This could assist clinicians in the evaluation of periodontal prognosis and establishment of an appropriate orthodontic treatment plan.

• ETRI Journal
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• 제41권2호
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• pp.235-241
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• 2019

In this paper, we propose a rank-weighted reconstruction feature to improve the robustness of a feed-forward deep neural network (FFDNN)-based acoustic model. In the FFDNN-based acoustic model, an input feature is constructed by vectorizing a submatrix that is created by slicing the feature vectors of frames within a context window. In this type of feature construction, the appropriate context window size is important because it determines the amount of trivial or discriminative information, such as redundancy, or temporal context of the input features. However, we ascertained whether a single parameter is sufficiently able to control the quantity of information. Therefore, we investigated the input feature construction from the perspectives of rank and nullity, and proposed a rank-weighted reconstruction feature herein, that allows for the retention of speech information components and the reduction in trivial components. The proposed method was evaluated in the TIMIT phone recognition and Wall Street Journal (WSJ) domains. The proposed method reduced the phone error rate of the TIMIT domain from 18.4% to 18.0%, and the word error rate of the WSJ domain from 4.70% to 4.43%.

• Applied Microscopy
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• 제38권2호
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• pp.73-79
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• 2008

현재 생물학 분야에서 세포 구조를 3차로 구현하기 위해 전자 현미경을 이용하는 연구는 매우 빠르게 발전하고 있다. 최근에는 시료의 구조를 변형시키는 화학 고정법 대신 시료를 빠른 시간 내에 동결고정시킴으로써 구조 변형 없이 세포 3차 구조 구현이 가능해졌다. 이러한 기술의 도입으로 단편이미지로만 세포 구조를 이해해왔던 지금까지와 달리 Cryo-ET를 통해 인위적인 구조 변형 없는 3차 구조 구현이 가능해졌고, 이 기법은 약물전달, 나노 공학 등 여러 학문 분야에 활용됨으로써 학문 발전에 이바지 할 것이다.

• Molecules and Cells
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• 제45권2호
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• pp.84-92
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• 2022

To understand the microcircuitry of the brain, the anatomical and functional connectivity among neurons must be resolved. One of the technical hurdles to achieving this goal is that the anatomical connections, or synapses, are often smaller than the diffraction limit of light and thus are difficult to resolve by conventional microscopy, while the microcircuitry of the brain is on the scale of 1 mm or larger. To date, the gold standard method for microcircuit reconstruction has been electron microscopy (EM). However, despite its rapid development, EM has clear shortcomings as a method for microcircuit reconstruction. The greatest weakness of this method is arguably its incompatibility with functional and molecular analysis. Fluorescence microscopy, on the other hand, is readily compatible with numerous physiological and molecular analyses. We believe that recent advances in various fluorescence microscopy techniques offer a new possibility for reliable synapse detection in large volumes of neural circuits. In this minireview, we summarize recent advances in fluorescence-based microcircuit reconstruction. In the same vein as these studies, we introduce our recent efforts to analyze the long-range connectivity among brain areas and the subcellular distribution of synapses of interest in relatively large volumes of cortical tissue with array tomography and superresolution microscopy.

• Journal of Information Processing Systems
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• 제16권6호
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• pp.1343-1358
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• 2020

In the stagewise arithmetic orthogonal matching pursuit algorithm, the weak threshold used in sparsity estimation is determined via maximum iterations. Different maximum iterations correspond to different thresholds and affect the performance of the algorithm. To solve this problem, we propose an improved variable weak threshold based on the stagewise arithmetic orthogonal matching pursuit algorithm. Our proposed algorithm uses the residual error value to control the weak threshold. When the residual value decreases, the threshold value continuously increases, so that the atoms contained in the atomic set are closer to the real sparsity value, making it possible to improve the reconstruction accuracy. In addition, we improved the generalized Jaccard coefficient in order to replace the inner product method that is used in the stagewise arithmetic orthogonal matching pursuit algorithm. Our proposed algorithm uses the covariance to replace the joint expectation for two variables based on the generalized Jaccard coefficient. The improved generalized Jaccard coefficient can be used to generate a more accurate calculation of the correlation between the measurement matrixes. In addition, the residual is more accurate, which can reduce the possibility of selecting the wrong atoms. We demonstrate using simulations that the proposed algorithm produces a better reconstruction result in the reconstruction of a one-dimensional signal and two-dimensional image signal.

• Applied Microscopy
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• 제46권4호
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• pp.171-175
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• 2016

A distinctive neuronal network in the brain is believed to make us unique individuals. Electron microscopy is a valuable tool for examining ultrastructural characteristics of neurons, synapses, and subcellular organelles. A recent technological breakthrough in volume electron microscopy allows large-scale circuit reconstruction of the nervous system with unprecedented detail. Serial-section electron microscopy-previously the domain of specialists-became automated with the advent of innovative systems such as the focused ion beam and serial block-face scanning electron microscopes and the automated tape-collecting ultramicrotome. Further advances in microscopic design and instrumentation are also available, which allow the reconstruction of unprecedentedly large volumes of brain tissue at high speed. The recent introduction of correlative light and electron microscopy will help to identify specific neural circuits associated with behavioral characteristics and revolutionize our understanding of how the brain works.