• Title/Summary/Keyword: smoothness model constraint

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A Variational Model For Longitudinal Brain Tissue Segmentation

  • Tang, Mingjun;Chen, Renwen;You, Zijuan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.11
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    • pp.3479-3492
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    • 2022
  • Longitudinal quantification of brain changes due to development, aging or disease plays an important role in the filed of personalized-medicine applications. However, due to the temporal variability in shape and different imaging equipment and parameters, estimating anatomical changes in longitudinal studies is significantly challenging. In this paper, a longitudinal Magnetic Resonance(MR) brain image segmentation algorithm proposed by combining intensity information and anisotropic smoothness term which contain a spatial smoothness constraint and longitudinal consistent constraint into a variational framework. The minimization of the proposed energy functional is strictly and effectively derived from a fast optimization algorithm. A large number of experimental results show that the proposed method can guarantee segmentation accuracy and longitudinal consistency in both simulated and real longitudinal MR brain images for analysis of anatomical changes over time.

A Method for Modifying a Surface Model with Nonuniform Scattered Constraint Points (불균일 이산 구속조건을 만족시키는 곡면 모델의 변형 방법)

  • Kim, S.H.;Song, S.J.
    • Korean Journal of Computational Design and Engineering
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    • v.12 no.1
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    • pp.58-73
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    • 2007
  • This paper described a method for the construction of a surface through a set of nonuniform scattered points. When the shift vectors of some points as constraints on the original surface are given, those of the other points should be computed to make the new surface. To keep up the look-see and smoothness with the original surfaces, the proper relationship should be formulated between the shifts of the constraint points and those of the other points. Vector fields for 3 dimensional shift of a point on the surface are made based in the constraint shifts. Vector fields for 3 dimensional shift of a point on the surface are made based on the constraint shifts. Multilevel B-spline approximation technique was used to construct the vector field. The technique uses coarse-to-fine hierarchy of control lattices. The developed method was applied to shoe sole design system especially for grading. Using this system, a shoe sole can be modified effectively.

An Application of Minimum Support Stabilizer as a Model Constraint in Magnetotelluric 2D Inversion (최소모델영역 연산자를 모델제한조건으로 적용한 2차원 MT 역산)

  • Lee, Seong-Kon
    • Journal of the Korean earth science society
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    • v.30 no.7
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    • pp.834-844
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    • 2009
  • Two-dimensional magnetotelluric (MT) inversion algorithm using minimum support (MS) stabilizer functional was implemented in this study to enhance the contrast of inverted images. For this implementation, this study derived a formula in discrete form for creeping model updates in the least-squares linearized inversion. A spatially varying regularization parameter determination algorithm, which is known as ACB (Active Constraint Balancing), was also adopted to stabilize the inversion process when using MS stabilizer as a model constraint. Inversion experiments for a simple isolated body model show well the feature of MS stabilizer in concentrating the anomalous body compared with the second-order derivative model constraint. This study also compared MS stabilizer and the second-order derivative model constraints for a model having multiple anomalous bodies to show the applicability of the algorithm into field data.

Improved full-waveform inversion of normalised seismic wavefield data (정규화된 탄성파 파동장 자료의 향상된 전파형 역산)

  • Kim, Hee-Joon;Matsuoka, Toshifumi
    • Geophysics and Geophysical Exploration
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    • v.9 no.1
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    • pp.86-92
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    • 2006
  • The full-waveform inversion algorithm using normalised seismic wavefields can avoid potential inversion errors due to source estimation required in conventional full-waveform inversion methods. In this paper, we have modified the inversion scheme to install a weighted smoothness constraint for better resolution, and to implement a staged approach using normalised wavefields in order of increasing frequency instead of inverting all frequency components simultaneously. The newly developed scheme is verified by using a simple two-dimensional fault model. One of the most significant improvements is based on introducing weights in model parameters, which can be derived from integrated sensitivities. The model-parameter weighting matrix is effective in selectively relaxing the smoothness constraint and in reducing artefacts in the reconstructed image. Simultaneous multiple-frequency inversion can almost be replicated by multiple single-frequency inversions. In particular, consecutively ordered single-frequency inversion, in which lower frequencies are used first, is useful for computation efficiency.

A shape from shading algorithm using a membrane model an direct recovery (박막 모델과 직접복구를 이용한 영상으로부터 형상 복구 알고리듬)

  • 박상호;이남욱
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.33B no.6
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    • pp.73-81
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    • 1996
  • In this paper, based on the constrained optimizatin technique and direct recovery method, we proesent a shape form shading (SFS) algorithm to recover a 3-D shape form an image. More specifically, we first employ the membrane model for a smoothness constraint to revoer a 3-D shape coarsely. We then compute the surface height directly to reduce the shape distortion due to a regularization term. In our approach, we can obtain a stable and accurate solution by the application of these two steps. Several simulation results on various images are provided and discussed in this paper and they show that the proposed algorithm extracts the 3-D information accurately and efficiently.

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Petrophysical Joint Inversion of Seismic and Electromagnetic Data (탄성파 탐사자료와 전자탐사자료를 이용한 저류층 물성 동시복합역산)

  • Yu, Jeongmin;Byun, Joongmoo;Seol, Soon Jee
    • Geophysics and Geophysical Exploration
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    • v.21 no.1
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    • pp.15-25
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    • 2018
  • Seismic inversion is a high-resolution tool to delineate the subsurface structures which may contain oil or gas. On the other hand, marine controlled-source electromagnetic (mCSEM) inversion can be a direct tool to indicate hydrocarbon. Thus, the joint inversion using both EM and seismic data together not only reduces the uncertainties but also takes advantage of both data simultaneously. In this paper, we have developed a simultaneous joint inversion approach for the direct estimation of reservoir petrophysical parameters, by linking electromagnetic and seismic data through rock physics model. A cross-gradient constraint is used to enhance the resolution of the inversion image and the maximum likelihood principle is applied to the relative weighting factor which controls the balance between two disparate data. By applying the developed algorithm to the synthetic model simulating the simplified gas field, we could confirm that the high-resolution images of petrophysical parameters can be obtained. However, from the other test using the synthetic model simulating an anticline reservoir, we noticed that the joint inversion produced different images depending on the model constraint used. Therefore, we modified the algorithm which has different model weighting matrix depending on the type of model parameters. Smoothness constraint and Marquardt-Levenberg constraint were applied to the water-saturation and porosity, respectively. When the improved algorithm is applied to the anticline model again, reliable porosity and water-saturation of reservoir were obtained. The inversion results indicate that the developed joint inversion algorithm can be contributed to the calculation of the accurate oil and gas reserves directly.

Dual Doppler Wind Retrieval Using a Three-dimensional Variational Method (3차원 변분법을 사용한 이중 도플러 바람장 분석)

  • Lee, SeonYong;Choi, Young-Jean;Chan, Dong-Eon
    • Atmosphere
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    • v.17 no.1
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    • pp.69-86
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    • 2007
  • The characteristics of the dual-Doppler wind retrieval method based on a three dimensional variational (3DVAR) conception were investigated from the following four points of view; the sensitivity of the number of iteration, the effect of the weak constraint term, the effect of the smoothness term, and the sensitivity of the error mixing ratio of the radial velocities. In the experiment, the radial velocities relative to the Gosan and Jindo radar sites of the Korea Meteorological Administration (KMA) were calculated from the forecasting of the WRF (Weather Research and Forecast; Skamarock, 2004) model at 1330 UTC 30 June 2006, which is the one and half hour forecast from the initial time, 1200 UTC on that day. The results showed that the retrieval performance of the horizontal wind field was robust, but that of the vertical wind was sensitive to the external conditions, such as iteration number and the on/off of the weak constraint term. The sensitivity of error mixing ratio was so large that even the horizontal wind retrieval efficiency was reduced a lot. But the sensitivity of the smooth term was not so large. When we applied this method to the real mesoscale convective system (MCS) between the Gosan and Jindo radar pair at 1430 UTC 30 June 2006, the wind structure of the convective cells in the MCS was consistently retrieved relative to the reflectivity factor structure. By comparing the vertical wind structure of this case with that of 10 minutes after, 1440 UTC 30 June 2006, we got the physical consistency of our method.

Bayesian Texture Segmentation Using Multi-layer Perceptron and Markov Random Field Model (다층 퍼셉트론과 마코프 랜덤 필드 모델을 이용한 베이지안 결 분할)

  • Kim, Tae-Hyung;Eom, Il-Kyu;Kim, Yoo-Shin
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.44 no.1
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    • pp.40-48
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    • 2007
  • This paper presents a novel texture segmentation method using multilayer perceptron (MLP) networks and Markov random fields in multiscale Bayesian framework. Multiscale wavelet coefficients are used as input for the neural networks. The output of the neural network is modeled as a posterior probability. Texture classification at each scale is performed by the posterior probabilities from MLP networks and MAP (maximum a posterior) classification. Then, in order to obtain the more improved segmentation result at the finest scale, our proposed method fuses the multiscale MAP classifications sequentially from coarse to fine scales. This process is done by computing the MAP classification given the classification at one scale and a priori knowledge regarding contextual information which is extracted from the adjacent coarser scale classification. In this fusion process, the MRF (Markov random field) prior distribution and Gibbs sampler are used, where the MRF model serves as the smoothness constraint and the Gibbs sampler acts as the MAP classifier. The proposed segmentation method shows better performance than texture segmentation using the HMT (Hidden Markov trees) model and HMTseg.

Stereo Matching by Dynamic Programming with Edges Emphasized (에지 정보를 강조한 동적계획법에 의한 스테레오 정합)

  • Joo, Jae-Heum;Oh, Jong-kyu;Seol, Sung-Wook;Lee, Chul-Hun;Nam, Ki-Gon
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.36S no.10
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    • pp.123-131
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    • 1999
  • In this paper, we proposed stereo matching algorithm by dynamic programming with edges emphasized. Existing algorithms show blur generally at depth discontinuities owing to smoothness constraint and non-existence of matching pixel in occlusion regions. Also it accompanies matching error by lackness of matching information in the untextured regions. This paper defines new cost function to make up for the problems occurred to existing algorithms. It is possible through deriving matching of edges in left and right images to be carried out between edge regions anf deriving that in the other regions to be peformed between the other regions. In case of the possibility that edges can be Produced in a large amount, matching between edge information adds weight to cost function in proportion to Path distance. Proposed algorithm was applied to various images obtained by convergent camera model as well as parallel camera model. As the result, proposed algorithm showed improved performance in the aspect of matching error and processing in the occlusion regions compared to existing algorithms. Also it could improve blur especially in discontinuity regions.

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Three-dimensional anisotropic inversion of resistivity tomography data in an abandoned mine area (폐광지역에서의 3차원 이방성 전기비저항 토모그래피 영상화)

  • Yi, Myeong-Jong;Kim, Jung-Ho;Son, Jeong-Sul
    • Geophysics and Geophysical Exploration
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    • v.14 no.1
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    • pp.7-17
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    • 2011
  • We have developed an inversion code for three-dimensional (3D) resistivity tomography including the anisotropy effect. The algorithm is based on the finite element approximations for the forward modelling and Active Constraint Balancing method is adopted to enhance the resolving power of the smoothness constraint least-squares inversion. Using numerical experiments, we have shown that anisotropic inversion is viable to get an accurate image of the subsurface when the subsurface shows strong electrical anisotropy. Moreover, anisotropy can be used as additional information in the interpretation of subsurface. This algorithm was also applied to the field dataset acquired in the abandoned old mine area, where a high-rise apartment block has been built up over a mining tunnel. The main purpose of the investigation was to evaluate the safety analysis of the building due to old mining activities. Strong electrical anisotropy has been observed and it was proven to be caused by geological setting of the site. To handle the anisotropy problem, field data were inverted by a 3D anisotropic tomography algorithm and we could obtain 3D subsurface images, which matches well with geology mapping observations. The inversion results have been used to provide the subsurface model for the safety analysis in rock engineering and we could assure the residents that the apartment has no problem in its safety after the completion of investigation works.