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Sample records for 3d image denoising

  1. GPU-accelerated denoising of 3D magnetic resonance images

    SciTech Connect

    Howison, Mark; Wes Bethel, E.

    2014-05-29

    The raw computational power of GPU accelerators enables fast denoising of 3D MR images using bilateral filtering, anisotropic diffusion, and non-local means. In practice, applying these filtering operations requires setting multiple parameters. This study was designed to provide better guidance to practitioners for choosing the most appropriate parameters by answering two questions: what parameters yield the best denoising results in practice? And what tuning is necessary to achieve optimal performance on a modern GPU? To answer the first question, we use two different metrics, mean squared error (MSE) and mean structural similarity (MSSIM), to compare denoising quality against a reference image. Surprisingly, the best improvement in structural similarity with the bilateral filter is achieved with a small stencil size that lies within the range of real-time execution on an NVIDIA Tesla M2050 GPU. Moreover, inappropriate choices for parameters, especially scaling parameters, can yield very poor denoising performance. To answer the second question, we perform an autotuning study to empirically determine optimal memory tiling on the GPU. The variation in these results suggests that such tuning is an essential step in achieving real-time performance. These results have important implications for the real-time application of denoising to MR images in clinical settings that require fast turn-around times.

  2. Frames-Based Denoising in 3D Confocal Microscopy Imaging.

    PubMed

    Konstantinidis, Ioannis; Santamaria-Pang, Alberto; Kakadiaris, Ioannis

    2005-01-01

    In this paper, we propose a novel denoising method for 3D confocal microscopy data based on robust edge detection. Our approach relies on the construction of a non-separable frame system in 3D that incorporates the Sobel operator in dual spatial directions. This multidirectional set of digital filters is capable of robustly detecting edge information by ensemble thresholding of the filtered data. We demonstrate the application of our method to both synthetic and real confocal microscopy data by comparing it to denoising methods based on separable 3D wavelets and 3D median filtering, and report very encouraging results.

  3. Fast non local means denoising for 3D MR images.

    PubMed

    Coupé, Pierrick; Yger, Pierre; Barillot, Christian

    2006-01-01

    One critical issue in the context of image restoration is the problem of noise removal while keeping the integrity of relevant image information. Denoising is a crucial step to increase image conspicuity and to improve the performances of all the processings needed for quantitative imaging analysis. The method proposed in this paper is based on an optimized version of the Non Local (NL) Means algorithm. This approach uses the natural redundancy of information in image to remove the noise. Tests were carried out on synthetic datasets and on real 3T MR images. The results show that the NL-means approach outperforms other classical denoising methods, such as Anisotropic Diffusion Filter and Total Variation.

  4. Denoising for 3-d photon-limited imaging data using nonseparable filterbanks.

    PubMed

    Santamaria-Pang, Alberto; Bildea, Teodor Stefan; Tan, Shan; Kakadiaris, Ioannis A

    2008-12-01

    In this paper, we present a novel frame-based denoising algorithm for photon-limited 3-D images. We first construct a new 3-D nonseparable filterbank by adding elements to an existing frame in a structurally stable way. In contrast with the traditional 3-D separable wavelet system, the new filterbank is capable of using edge information in multiple directions. We then propose a data-adaptive hysteresis thresholding algorithm based on this new 3-D nonseparable filterbank. In addition, we develop a new validation strategy for denoising of photon-limited images containing sparse structures, such as neurons (the structure of interest is less than 5% of total volume). The validation method, based on tubular neighborhoods around the structure, is used to determine the optimal threshold of the proposed denoising algorithm. We compare our method with other state-of-the-art methods and report very encouraging results on applications utilizing both synthetic and real data.

  5. Edge structure preserving 3D image denoising by local surface approximation.

    PubMed

    Qiu, Peihua; Mukherjee, Partha Sarathi

    2012-08-01

    In various applications, including magnetic resonance imaging (MRI) and functional MRI (fMRI), 3D images are becoming increasingly popular. To improve the reliability of subsequent image analyses, 3D image denoising is often a necessary preprocessing step, which is the focus of the current paper. In the literature, most existing image denoising procedures are for 2D images. Their direct extensions to 3D cases generally cannot handle 3D images efficiently because the structure of a typical 3D image is substantially more complicated than that of a typical 2D image. For instance, edge locations are surfaces in 3D cases which would be much more challenging to handle compared to edge curves in 2D cases. We propose a novel 3D image denoising procedure in this paper, based on local approximation of the edge surfaces using a set of surface templates. An important property of this method is that it can preserve edges and major edge structures (e.g., intersections of two edge surfaces and pointed corners). Numerical studies show that it works well in various applications.

  6. Denoising of 3D magnetic resonance images by using higher-order singular value decomposition.

    PubMed

    Zhang, Xinyuan; Xu, Zhongbiao; Jia, Nan; Yang, Wei; Feng, Qianjin; Chen, Wufan; Feng, Yanqiu

    2015-01-01

    The denoising of magnetic resonance (MR) images is important to improve the inspection quality and reliability of quantitative image analysis. Nonlocal filters by exploiting similarity and/or sparseness among patches or cubes achieve excellent performance in denoising MR images. Recently, higher-order singular value decomposition (HOSVD) has been demonstrated to be a simple and effective method for exploiting redundancy in the 3D stack of similar patches during denoising 2D natural image. This work aims to investigate the application and improvement of HOSVD to denoising MR volume data. The wiener-augmented HOSVD method achieves comparable performance to that of BM4D. For further improvement, we propose to augment the standard HOSVD stage by a second recursive stage, which is a repeated HOSVD filtering of the weighted summation of the residual and denoised image in the first stage. The appropriate weights have been investigated by experiments with different image types and noise levels. Experimental results over synthetic and real 3D MR data demonstrate that the proposed method outperforms current state-of-the-art denoising methods.

  7. Kernel regression based feature extraction for 3D MR image denoising.

    PubMed

    López-Rubio, Ezequiel; Florentín-Núñez, María Nieves

    2011-08-01

    Kernel regression is a non-parametric estimation technique which has been successfully applied to image denoising and enhancement in recent times. Magnetic resonance 3D image denoising has two features that distinguish it from other typical image denoising applications, namely the tridimensional structure of the images and the nature of the noise, which is Rician rather than Gaussian or impulsive. Here we propose a principled way to adapt the general kernel regression framework to this particular problem. Our noise removal system is rooted on a zeroth order 3D kernel regression, which computes a weighted average of the pixels over a regression window. We propose to obtain the weights from the similarities among small sized feature vectors associated to each pixel. In turn, these features come from a second order 3D kernel regression estimation of the original image values and gradient vectors. By considering directional information in the weight computation, this approach substantially enhances the performance of the filter. Moreover, Rician noise level is automatically estimated without any need of human intervention, i.e. our method is fully automated. Experimental results over synthetic and real images demonstrate that our proposal achieves good performance with respect to the other MRI denoising filters being compared.

  8. Denoising 3D MR images by the enhanced non-local means filter for Rician noise.

    PubMed

    Liu, Hong; Yang, Cihui; Pan, Ning; Song, Enmin; Green, Richard

    2010-12-01

    The non-local means (NLM) filter removes noise by calculating the weighted average of the pixels in the global area and shows superiority over existing local filter methods that only consider local neighbor pixels. This filter has been successfully extended from 2D images to 3D images and has been applied to denoising 3D magnetic resonance (MR) images. In this article, a novel filter based on the NLM filter is proposed to improve the denoising effect. Considering the characteristics of Rician noise in the MR images, denoising by the NLM filter is first performed on the squared magnitude images. Then, unbiased correcting is carried out to eliminate the biased deviation. When performing the NLM filter, the weight is calculated based on the Gaussian-filtered image to reduce the disturbance of the noise. The performance of this filter is evaluated by carrying out a qualitative and quantitative comparison of this method with three other filters, namely, the original NLM filter, the unbiased NLM (UNLM) filter and the Rician NLM (RNLM) filter. Experimental results demonstrate that the proposed filter achieves better denoising performance over the other filters being compared.

  9. 3D MR image denoising using rough set and kernel PCA method.

    PubMed

    Phophalia, Ashish; Mitra, Suman K

    2017-02-01

    In this paper, we have presented a two stage method, using kernel principal component analysis (KPCA) and rough set theory (RST), for denoising volumetric MRI data. A rough set theory (RST) based clustering technique has been used for voxel based processing. The method groups similar voxels (3D cubes) using class and edge information derived from noisy input. Each clusters thus formed now represented via basis vector. These vectors now projected into kernel space and PCA is performed in the feature space. This work is motivated by idea that under Rician noise MRI data may be non-linear and kernel mapping will help to define linear separator between these clusters/basis vectors thus used for image denoising. We have further investigated various kernels for Rician noise for different noise levels. The best kernel is then selected on the performance basis over PSNR and structure similarity (SSIM) measures. The work has been compared with state-of-the-art methods under various measures for synthetic and real databases.

  10. GPU-Accelerated Denoising in 3D (GD3D)

    SciTech Connect

    2013-10-01

    The raw computational power GPU Accelerators enables fast denoising of 3D MR images using bilateral filtering, anisotropic diffusion, and non-local means. This software addresses two facets of this promising application: what tuning is necessary to achieve optimal performance on a modern GPU? And what parameters yield the best denoising results in practice? To answer the first question, the software performs an autotuning step to empirically determine optimal memory blocking on the GPU. To answer the second, it performs a sweep of algorithm parameters to determine the combination that best reduces the mean squared error relative to a noiseless reference image.

  11. Imaging bacterial 3D motion using digital in-line holographic microscopy and correlation-based de-noising algorithm

    PubMed Central

    Molaei, Mehdi; Sheng, Jian

    2014-01-01

    Abstract: Better understanding of bacteria environment interactions in the context of biofilm formation requires accurate 3-dimentional measurements of bacteria motility. Digital Holographic Microscopy (DHM) has demonstrated its capability in resolving 3D distribution and mobility of particulates in a dense suspension. Due to their low scattering efficiency, bacteria are substantially difficult to be imaged by DHM. In this paper, we introduce a novel correlation-based de-noising algorithm to remove the background noise and enhance the quality of the hologram. Implemented in conjunction with DHM, we demonstrate that the method allows DHM to resolve 3-D E. coli bacteria locations of a dense suspension (>107 cells/ml) with submicron resolutions (<0.5 µm) over substantial depth and to obtain thousands of 3D cell trajectories. PMID:25607177

  12. A novel structured dictionary for fast processing of 3D medical images, with application to computed tomography restoration and denoising

    NASA Astrophysics Data System (ADS)

    Karimi, Davood; Ward, Rabab K.

    2016-03-01

    Sparse representation of signals in learned overcomplete dictionaries has proven to be a powerful tool with applications in denoising, restoration, compression, reconstruction, and more. Recent research has shown that learned overcomplete dictionaries can lead to better results than analytical dictionaries such as wavelets in almost all image processing applications. However, a major disadvantage of these dictionaries is that their learning and usage is very computationally intensive. In particular, finding the sparse representation of a signal in these dictionaries requires solving an optimization problem that leads to very long computational times, especially in 3D image processing. Moreover, the sparse representation found by greedy algorithms is usually sub-optimal. In this paper, we propose a novel two-level dictionary structure that improves the performance and the speed of standard greedy sparse coding methods. The first (i.e., the top) level in our dictionary is a fixed orthonormal basis, whereas the second level includes the atoms that are learned from the training data. We explain how such a dictionary can be learned from the training data and how the sparse representation of a new signal in this dictionary can be computed. As an application, we use the proposed dictionary structure for removing the noise and artifacts in 3D computed tomography (CT) images. Our experiments with real CT images show that the proposed method achieves results that are comparable with standard dictionary-based methods while substantially reducing the computational time.

  13. Progressive image denoising.

    PubMed

    Knaus, Claude; Zwicker, Matthias

    2014-07-01

    Image denoising continues to be an active research topic. Although state-of-the-art denoising methods are numerically impressive and approch theoretical limits, they suffer from visible artifacts.While they produce acceptable results for natural images, human eyes are less forgiving when viewing synthetic images. At the same time, current methods are becoming more complex, making analysis, and implementation difficult. We propose image denoising as a simple physical process, which progressively reduces noise by deterministic annealing. The results of our implementation are numerically and visually excellent. We further demonstrate that our method is particularly suited for synthetic images. Finally, we offer a new perspective on image denoising using robust estimators.

  14. Global Image Denoising.

    PubMed

    Talebi, Hossein; Milanfar, Peyman

    2014-02-01

    Most existing state-of-the-art image denoising algorithms are based on exploiting similarity between a relatively modest number of patches. These patch-based methods are strictly dependent on patch matching, and their performance is hamstrung by the ability to reliably find sufficiently similar patches. As the number of patches grows, a point of diminishing returns is reached where the performance improvement due to more patches is offset by the lower likelihood of finding sufficiently close matches. The net effect is that while patch-based methods, such as BM3D, are excellent overall, they are ultimately limited in how well they can do on (larger) images with increasing complexity. In this paper, we address these shortcomings by developing a paradigm for truly global filtering where each pixel is estimated from all pixels in the image. Our objectives in this paper are two-fold. First, we give a statistical analysis of our proposed global filter, based on a spectral decomposition of its corresponding operator, and we study the effect of truncation of this spectral decomposition. Second, we derive an approximation to the spectral (principal) components using the Nyström extension. Using these, we demonstrate that this global filter can be implemented efficiently by sampling a fairly small percentage of the pixels in the image. Experiments illustrate that our strategy can effectively globalize any existing denoising filters to estimate each pixel using all pixels in the image, hence improving upon the best patch-based methods.

  15. Multiscale image blind denoising.

    PubMed

    Lebrun, Marc; Colom, Miguel; Morel, Jean-Michel

    2015-10-01

    Arguably several thousands papers are dedicated to image denoising. Most papers assume a fixed noise model, mainly white Gaussian or Poissonian. This assumption is only valid for raw images. Yet, in most images handled by the public and even by scientists, the noise model is imperfectly known or unknown. End users only dispose the result of a complex image processing chain effectuated by uncontrolled hardware and software (and sometimes by chemical means). For such images, recent progress in noise estimation permits to estimate from a single image a noise model, which is simultaneously signal and frequency dependent. We propose here a multiscale denoising algorithm adapted to this broad noise model. This leads to a blind denoising algorithm which we demonstrate on real JPEG images and on scans of old photographs for which the formation model is unknown. The consistency of this algorithm is also verified on simulated distorted images. This algorithm is finally compared with the unique state of the art previous blind denoising method.

  16. 3D Imaging.

    ERIC Educational Resources Information Center

    Hastings, S. K.

    2002-01-01

    Discusses 3 D imaging as it relates to digital representations in virtual library collections. Highlights include X-ray computed tomography (X-ray CT); the National Science Foundation (NSF) Digital Library Initiatives; output peripherals; image retrieval systems, including metadata; and applications of 3 D imaging for libraries and museums. (LRW)

  17. Quantum Boolean image denoising

    NASA Astrophysics Data System (ADS)

    Mastriani, Mario

    2015-05-01

    A quantum Boolean image processing methodology is presented in this work, with special emphasis in image denoising. A new approach for internal image representation is outlined together with two new interfaces: classical to quantum and quantum to classical. The new quantum Boolean image denoising called quantum Boolean mean filter works with computational basis states (CBS), exclusively. To achieve this, we first decompose the image into its three color components, i.e., red, green and blue. Then, we get the bitplanes for each color, e.g., 8 bits per pixel, i.e., 8 bitplanes per color. From now on, we will work with the bitplane corresponding to the most significant bit (MSB) of each color, exclusive manner. After a classical-to-quantum interface (which includes a classical inverter), we have a quantum Boolean version of the image within the quantum machine. This methodology allows us to avoid the problem of quantum measurement, which alters the results of the measured except in the case of CBS. Said so far is extended to quantum algorithms outside image processing too. After filtering of the inverted version of MSB (inside quantum machine), the result passes through a quantum-classical interface (which involves another classical inverter) and then proceeds to reassemble each color component and finally the ending filtered image. Finally, we discuss the more appropriate metrics for image denoising in a set of experimental results.

  18. 3D photoacoustic imaging

    NASA Astrophysics Data System (ADS)

    Carson, Jeffrey J. L.; Roumeliotis, Michael; Chaudhary, Govind; Stodilka, Robert Z.; Anastasio, Mark A.

    2010-06-01

    Our group has concentrated on development of a 3D photoacoustic imaging system for biomedical imaging research. The technology employs a sparse parallel detection scheme and specialized reconstruction software to obtain 3D optical images using a single laser pulse. With the technology we have been able to capture 3D movies of translating point targets and rotating line targets. The current limitation of our 3D photoacoustic imaging approach is its inability ability to reconstruct complex objects in the field of view. This is primarily due to the relatively small number of projections used to reconstruct objects. However, in many photoacoustic imaging situations, only a few objects may be present in the field of view and these objects may have very high contrast compared to background. That is, the objects have sparse properties. Therefore, our work had two objectives: (i) to utilize mathematical tools to evaluate 3D photoacoustic imaging performance, and (ii) to test image reconstruction algorithms that prefer sparseness in the reconstructed images. Our approach was to utilize singular value decomposition techniques to study the imaging operator of the system and evaluate the complexity of objects that could potentially be reconstructed. We also compared the performance of two image reconstruction algorithms (algebraic reconstruction and l1-norm techniques) at reconstructing objects of increasing sparseness. We observed that for a 15-element detection scheme, the number of measureable singular vectors representative of the imaging operator was consistent with the demonstrated ability to reconstruct point and line targets in the field of view. We also observed that the l1-norm reconstruction technique, which is known to prefer sparseness in reconstructed images, was superior to the algebraic reconstruction technique. Based on these findings, we concluded (i) that singular value decomposition of the imaging operator provides valuable insight into the capabilities of

  19. Wavelet-based fMRI analysis: 3-D denoising, signal separation, and validation metrics.

    PubMed

    Khullar, Siddharth; Michael, Andrew; Correa, Nicolle; Adali, Tulay; Baum, Stefi A; Calhoun, Vince D

    2011-02-14

    We present a novel integrated wavelet-domain based framework (w-ICA) for 3-D denoising functional magnetic resonance imaging (fMRI) data followed by source separation analysis using independent component analysis (ICA) in the wavelet domain. We propose the idea of a 3-D wavelet-based multi-directional denoising scheme where each volume in a 4-D fMRI data set is sub-sampled using the axial, sagittal and coronal geometries to obtain three different slice-by-slice representations of the same data. The filtered intensity value of an arbitrary voxel is computed as an expected value of the denoised wavelet coefficients corresponding to the three viewing geometries for each sub-band. This results in a robust set of denoised wavelet coefficients for each voxel. Given the de-correlated nature of these denoised wavelet coefficients, it is possible to obtain more accurate source estimates using ICA in the wavelet domain. The contributions of this work can be realized as two modules: First, in the analysis module we combine a new 3-D wavelet denoising approach with signal separation properties of ICA in the wavelet domain. This step helps obtain an activation component that corresponds closely to the true underlying signal, which is maximally independent with respect to other components. Second, we propose and describe two novel shape metrics for post-ICA comparisons between activation regions obtained through different frameworks. We verified our method using simulated as well as real fMRI data and compared our results against the conventional scheme (Gaussian smoothing+spatial ICA: s-ICA). The results show significant improvements based on two important features: (1) preservation of shape of the activation region (shape metrics) and (2) receiver operating characteristic curves. It was observed that the proposed framework was able to preserve the actual activation shape in a consistent manner even for very high noise levels in addition to significant reduction in false

  20. True 4D Image Denoising on the GPU.

    PubMed

    Eklund, Anders; Andersson, Mats; Knutsson, Hans

    2011-01-01

    The use of image denoising techniques is an important part of many medical imaging applications. One common application is to improve the image quality of low-dose (noisy) computed tomography (CT) data. While 3D image denoising previously has been applied to several volumes independently, there has not been much work done on true 4D image denoising, where the algorithm considers several volumes at the same time. The problem with 4D image denoising, compared to 2D and 3D denoising, is that the computational complexity increases exponentially. In this paper we describe a novel algorithm for true 4D image denoising, based on local adaptive filtering, and how to implement it on the graphics processing unit (GPU). The algorithm was applied to a 4D CT heart dataset of the resolution 512  × 512  × 445  × 20. The result is that the GPU can complete the denoising in about 25 minutes if spatial filtering is used and in about 8 minutes if FFT-based filtering is used. The CPU implementation requires several days of processing time for spatial filtering and about 50 minutes for FFT-based filtering. The short processing time increases the clinical value of true 4D image denoising significantly.

  1. Performance prediction for 3D filtering of multichannel images

    NASA Astrophysics Data System (ADS)

    Rubel, Oleksii; Kozhemiakin, Ruslan A.; Abramov, Sergey K.; Lukin, Vladimir V.; Vozel, Benoit; Chehdi, Kacem

    2015-10-01

    Performance of denoising based on discrete cosine transform applied to multichannel remote sensing images corrupted by additive white Gaussian noise is analyzed. Images obtained by satellite Earth Observing-1 (EO-1) mission using hyperspectral imager instrument (Hyperion) that have high input SNR are taken as test images. Denoising performance is characterized by improvement of PSNR. For hard-thresholding 3D DCT-based denoising, simple statistics (probabilities to be less than a certain threshold) are used to predict denoising efficiency using curves fitted into scatterplots. It is shown that the obtained curves (approximations) provide prediction of denoising efficiency with high accuracy. Analysis is carried out for different numbers of channels processed jointly. Universality of prediction for different number of channels is proven.

  2. Dual-domain denoising in three dimensional magnetic resonance imaging.

    PubMed

    Peng, Jing; Zhou, Jiliu; Wu, Xi

    2016-08-01

    Denoising is a crucial preprocessing procedure for three dimensional magnetic resonance imaging (3D MRI). Existing denoising methods are predominantly implemented in a single domain, ignoring information in other domains. However, denoising methods are becoming increasingly complex, making analysis and implementation challenging. The present study aimed to develop a dual-domain image denoising (DDID) algorithm for 3D MRI that encapsulates information from the spatial and transform domains. In the present study, the DDID method was used to distinguish signal from noise in the spatial and frequency domains, after which robust accurate noise estimation was introduced for iterative filtering, which is simple and beneficial for computation. In addition, the proposed method was compared quantitatively and qualitatively with existing methods for synthetic and in vivo MRI datasets. The results of the present study suggested that the novel DDID algorithm performed well and provided competitive results, as compared with existing MRI denoising filters.

  3. Image denoising by exploring external and internal correlations.

    PubMed

    Yue, Huanjing; Sun, Xiaoyan; Yang, Jingyu; Wu, Feng

    2015-06-01

    Single image denoising suffers from limited data collection within a noisy image. In this paper, we propose a novel image denoising scheme, which explores both internal and external correlations with the help of web images. For each noisy patch, we build internal and external data cubes by finding similar patches from the noisy and web images, respectively. We then propose reducing noise by a two-stage strategy using different filtering approaches. In the first stage, since the noisy patch may lead to inaccurate patch selection, we propose a graph based optimization method to improve patch matching accuracy in external denoising. The internal denoising is frequency truncation on internal cubes. By combining the internal and external denoising patches, we obtain a preliminary denoising result. In the second stage, we propose reducing noise by filtering of external and internal cubes, respectively, on transform domain. In this stage, the preliminary denoising result not only enhances the patch matching accuracy but also provides reliable estimates of filtering parameters. The final denoising image is obtained by fusing the external and internal filtering results. Experimental results show that our method constantly outperforms state-of-the-art denoising schemes in both subjective and objective quality measurements, e.g., it achieves >2 dB gain compared with BM3D at a wide range of noise levels.

  4. Nonlinear Image Denoising Methodologies

    DTIC Science & Technology

    2002-05-01

    53 5.3 A Multiscale Approach to Scale-Space Analysis . . . . . . . . . . . . . . . . 53 5.4...etc. In this thesis, Our approach to denoising is first based on a controlled nonlinear stochastic random walk to achieve a scale space analysis ( as in... stochastic treatment or interpretation of the diffusion. In addition, unless a specific stopping time is known to be adequate, the resulting evolution

  5. Adaptively Tuned Iterative Low Dose CT Image Denoising

    PubMed Central

    Hashemi, SayedMasoud; Paul, Narinder S.; Beheshti, Soosan; Cobbold, Richard S. C.

    2015-01-01

    Improving image quality is a critical objective in low dose computed tomography (CT) imaging and is the primary focus of CT image denoising. State-of-the-art CT denoising algorithms are mainly based on iterative minimization of an objective function, in which the performance is controlled by regularization parameters. To achieve the best results, these should be chosen carefully. However, the parameter selection is typically performed in an ad hoc manner, which can cause the algorithms to converge slowly or become trapped in a local minimum. To overcome these issues a noise confidence region evaluation (NCRE) method is used, which evaluates the denoising residuals iteratively and compares their statistics with those produced by additive noise. It then updates the parameters at the end of each iteration to achieve a better match to the noise statistics. By combining NCRE with the fundamentals of block matching and 3D filtering (BM3D) approach, a new iterative CT image denoising method is proposed. It is shown that this new denoising method improves the BM3D performance in terms of both the mean square error and a structural similarity index. Moreover, simulations and patient results show that this method preserves the clinically important details of low dose CT images together with a substantial noise reduction. PMID:26089972

  6. Adaptively Tuned Iterative Low Dose CT Image Denoising.

    PubMed

    Hashemi, SayedMasoud; Paul, Narinder S; Beheshti, Soosan; Cobbold, Richard S C

    2015-01-01

    Improving image quality is a critical objective in low dose computed tomography (CT) imaging and is the primary focus of CT image denoising. State-of-the-art CT denoising algorithms are mainly based on iterative minimization of an objective function, in which the performance is controlled by regularization parameters. To achieve the best results, these should be chosen carefully. However, the parameter selection is typically performed in an ad hoc manner, which can cause the algorithms to converge slowly or become trapped in a local minimum. To overcome these issues a noise confidence region evaluation (NCRE) method is used, which evaluates the denoising residuals iteratively and compares their statistics with those produced by additive noise. It then updates the parameters at the end of each iteration to achieve a better match to the noise statistics. By combining NCRE with the fundamentals of block matching and 3D filtering (BM3D) approach, a new iterative CT image denoising method is proposed. It is shown that this new denoising method improves the BM3D performance in terms of both the mean square error and a structural similarity index. Moreover, simulations and patient results show that this method preserves the clinically important details of low dose CT images together with a substantial noise reduction.

  7. Image denoising using local tangent space alignment

    NASA Astrophysics Data System (ADS)

    Feng, JianZhou; Song, Li; Huo, Xiaoming; Yang, XiaoKang; Zhang, Wenjun

    2010-07-01

    We propose a novel image denoising approach, which is based on exploring an underlying (nonlinear) lowdimensional manifold. Using local tangent space alignment (LTSA), we 'learn' such a manifold, which approximates the image content effectively. The denoising is performed by minimizing a newly defined objective function, which is a sum of two terms: (a) the difference between the noisy image and the denoised image, (b) the distance from the image patch to the manifold. We extend the LTSA method from manifold learning to denoising. We introduce the local dimension concept that leads to adaptivity to different kind of image patches, e.g. flat patches having lower dimension. We also plug in a basic denoising stage to estimate the local coordinate more accurately. It is found that the proposed method is competitive: its performance surpasses the K-SVD denoising method.

  8. Image denoising using a combined criterion

    NASA Astrophysics Data System (ADS)

    Semenishchev, Evgeny; Marchuk, Vladimir; Shrafel, Igor; Dubovskov, Vadim; Onoyko, Tatyana; Maslennikov, Stansilav

    2016-05-01

    A new image denoising method is proposed in this paper. We are considering an optimization problem with a linear objective function based on two criteria, namely, L2 norm and the first order square difference. This method is a parametric, so by a choice of the parameters we can adapt a proposed criteria of the objective function. The denoising algorithm consists of the following steps: 1) multiple denoising estimates are found on local areas of the image; 2) image edges are determined; 3) parameters of the method are fixed and denoised estimates of the local area are found; 4) local window is moved to the next position (local windows are overlapping) in order to produce the final estimate. A proper choice of parameters of the introduced method is discussed. A comparative analysis of a new denoising method with existed ones is performed on a set of test images.

  9. Green channel guiding denoising on bayer image.

    PubMed

    Tan, Xin; Lai, Shiming; Liu, Yu; Zhang, Maojun

    2014-01-01

    Denoising is an indispensable function for digital cameras. In respect that noise is diffused during the demosaicking, the denoising ought to work directly on bayer data. The difficulty of denoising on bayer image is the interlaced mosaic pattern of red, green, and blue. Guided filter is a novel time efficient explicit filter kernel which can incorporate additional information from the guidance image, but it is still not applied for bayer image. In this work, we observe that the green channel of bayer mode is higher in both sampling rate and Signal-to-Noise Ratio (SNR) than the red and blue ones. Therefore the green channel can be used to guide denoising. This kind of guidance integrates the different color channels together. Experiments on both actual and simulated bayer images indicate that green channel acts well as the guidance signal, and the proposed method is competitive with other popular filter kernel denoising methods.

  10. Autofocus for 3D imaging

    NASA Astrophysics Data System (ADS)

    Lee-Elkin, Forest

    2008-04-01

    Three dimensional (3D) autofocus remains a significant challenge for the development of practical 3D multipass radar imaging. The current 2D radar autofocus methods are not readily extendable across sensor passes. We propose a general framework that allows a class of data adaptive solutions for 3D auto-focus across passes with minimal constraints on the scene contents. The key enabling assumption is that portions of the scene are sparse in elevation which reduces the number of free variables and results in a system that is simultaneously solved for scatterer heights and autofocus parameters. The proposed method extends 2-pass interferometric synthetic aperture radar (IFSAR) methods to an arbitrary number of passes allowing the consideration of scattering from multiple height locations. A specific case from the proposed autofocus framework is solved and demonstrates autofocus and coherent multipass 3D estimation across the 8 passes of the "Gotcha Volumetric SAR Data Set" X-Band radar data.

  11. Denoising Medical Images using Calculus of Variations.

    PubMed

    Kohan, Mahdi Nakhaie; Behnam, Hamid

    2011-07-01

    We propose a method for medical image denoising using calculus of variations and local variance estimation by shaped windows. This method reduces any additive noise and preserves small patterns and edges of images. A pyramid structure-texture decomposition of images is used to separate noise and texture components based on local variance measures. The experimental results show that the proposed method has visual improvement as well as a better SNR, RMSE and PSNR than common medical image denoising methods. Experimental results in denoising a sample Magnetic Resonance image show that SNR, PSNR and RMSE have been improved by 19, 9 and 21 percents respectively.

  12. Image sequence denoising via sparse and redundant representations.

    PubMed

    Protter, Matan; Elad, Michael

    2009-01-01

    In this paper, we consider denoising of image sequences that are corrupted by zero-mean additive white Gaussian noise. Relative to single image denoising techniques, denoising of sequences aims to also utilize the temporal dimension. This assists in getting both faster algorithms and better output quality. This paper focuses on utilizing sparse and redundant representations for image sequence denoising, extending the work reported in. In the single image setting, the K-SVD algorithm is used to train a sparsifying dictionary for the corrupted image. This paper generalizes the above algorithm by offering several extensions: i) the atoms used are 3-D; ii) the dictionary is propagated from one frame to the next, reducing the number of required iterations; and iii) averaging is done on patches in both spatial and temporal neighboring locations. These modifications lead to substantial benefits in complexity and denoising performance, compared to simply running the single image algorithm sequentially. The algorithm's performance is experimentally compared to several state-of-the-art algorithms, demonstrating comparable or favorable results.

  13. Automatic parameter prediction for image denoising algorithms using perceptual quality features

    NASA Astrophysics Data System (ADS)

    Mittal, Anish; Moorthy, Anush K.; Bovik, Alan C.

    2012-03-01

    A natural scene statistics (NSS) based blind image denoising approach is proposed, where denoising is performed without knowledge of the noise variance present in the image. We show how such a parameter estimation can be used to perform blind denoising by combining blind parameter estimation with a state-of-the-art denoising algorithm.1 Our experiments show that for all noise variances simulated on a varied image content, our approach is almost always statistically superior to the reference BM3D implementation in terms of perceived visual quality at the 95% confidence level.

  14. Polarimetric 3D integral imaging in photon-starved conditions.

    PubMed

    Carnicer, Artur; Javidi, Bahram

    2015-03-09

    We develop a method for obtaining 3D polarimetric integral images from elemental images recorded in low light illumination conditions. Since photon-counting images are very sparse, calculation of the Stokes parameters and the degree of polarization should be handled carefully. In our approach, polarimetric 3D integral images are generated using the Maximum Likelihood Estimation and subsequently reconstructed by means of a Total Variation Denoising filter. In this way, polarimetric results are comparable to those obtained in conventional illumination conditions. We also show that polarimetric information retrieved from photon starved images can be used in 3D object recognition problems. To the best of our knowledge, this is the first report on 3D polarimetric photon counting integral imaging.

  15. A Decomposition Framework for Image Denoising Algorithms.

    PubMed

    Ghimpeteanu, Gabriela; Batard, Thomas; Bertalmio, Marcelo; Levine, Stacey

    2016-01-01

    In this paper, we consider an image decomposition model that provides a novel framework for image denoising. The model computes the components of the image to be processed in a moving frame that encodes its local geometry (directions of gradients and level lines). Then, the strategy we develop is to denoise the components of the image in the moving frame in order to preserve its local geometry, which would have been more affected if processing the image directly. Experiments on a whole image database tested with several denoising methods show that this framework can provide better results than denoising the image directly, both in terms of Peak signal-to-noise ratio and Structural similarity index metrics.

  16. Denoising in Contrast-Enhanced X-ray Images

    NASA Astrophysics Data System (ADS)

    Jeon, Gwanggil

    2016-12-01

    In this paper, we propose a denoising and contrast-enhancement method for medical images. The main purpose of medical image improvement is to transform lower contrast data into higher contrast, and to reduce high noise levels. To meet this goal, we propose a noise-level estimation method, whereby the noise level is estimated by computing the standard deviation and variance in a local block. The obtained noise level is then used as an input parameter for the block-matching and 3D filtering (BM3D) algorithm, and the denoising process is then performed. Noise-level estimation step is important because the BM3D algorithm does not perform well without correct noise-level information. Simulation results confirm that the proposed method outperforms other benchmarks with respect to both their objective and visual performances.

  17. Improved 3D wavelet-based de-noising of fMRI data

    NASA Astrophysics Data System (ADS)

    Khullar, Siddharth; Michael, Andrew M.; Correa, Nicolle; Adali, Tulay; Baum, Stefi A.; Calhoun, Vince D.

    2011-03-01

    Functional MRI (fMRI) data analysis deals with the problem of detecting very weak signals in very noisy data. Smoothing with a Gaussian kernel is often used to decrease noise at the cost of losing spatial specificity. We present a novel wavelet-based 3-D technique to remove noise in fMRI data while preserving the spatial features in the component maps obtained through group independent component analysis (ICA). Each volume is decomposed into eight volumetric sub-bands using a separable 3-D stationary wavelet transform. Each of the detail sub-bands are then treated through the main denoising module. This module facilitates computation of shrinkage factors through a hierarchical framework. It utilizes information iteratively from the sub-band at next higher level to estimate denoised coefficients at the current level. These de-noised sub-bands are then reconstructed back to the spatial domain using an inverse wavelet transform. Finally, the denoised group fMRI data is analyzed using ICA where the data is decomposed in to clusters of functionally correlated voxels (spatial maps) as indicators of task-related neural activity. The proposed method enables the preservation of shape of the actual activation regions associated with the BOLD activity. In addition it is able to achieve high specificity as compared to the conventionally used FWHM (full width half maximum) Gaussian kernels for smoothing fMRI data.

  18. Image denoising using the higher order singular value decomposition.

    PubMed

    Rajwade, Ajit; Rangarajan, Anand; Banerjee, Arunava

    2013-04-01

    In this paper, we propose a very simple and elegant patch-based, machine learning technique for image denoising using the higher order singular value decomposition (HOSVD). The technique simply groups together similar patches from a noisy image (with similarity defined by a statistically motivated criterion) into a 3D stack, computes the HOSVD coefficients of this stack, manipulates these coefficients by hard thresholding, and inverts the HOSVD transform to produce the final filtered image. Our technique chooses all required parameters in a principled way, relating them to the noise model. We also discuss our motivation for adopting the HOSVD as an appropriate transform for image denoising. We experimentally demonstrate the excellent performance of the technique on grayscale as well as color images. On color images, our method produces state-of-the-art results, outperforming other color image denoising algorithms at moderately high noise levels. A criterion for optimal patch-size selection and noise variance estimation from the residual images (after denoising) is also presented.

  19. Adaptive image denoising by targeted databases.

    PubMed

    Luo, Enming; Chan, Stanley H; Nguyen, Truong Q

    2015-07-01

    We propose a data-dependent denoising procedure to restore noisy images. Different from existing denoising algorithms which search for patches from either the noisy image or a generic database, the new algorithm finds patches from a database that contains relevant patches. We formulate the denoising problem as an optimal filter design problem and make two contributions. First, we determine the basis function of the denoising filter by solving a group sparsity minimization problem. The optimization formulation generalizes existing denoising algorithms and offers systematic analysis of the performance. Improvement methods are proposed to enhance the patch search process. Second, we determine the spectral coefficients of the denoising filter by considering a localized Bayesian prior. The localized prior leverages the similarity of the targeted database, alleviates the intensive Bayesian computation, and links the new method to the classical linear minimum mean squared error estimation. We demonstrate applications of the proposed method in a variety of scenarios, including text images, multiview images, and face images. Experimental results show the superiority of the new algorithm over existing methods.

  20. Image-Specific Prior Adaptation for Denoising.

    PubMed

    Lu, Xin; Lin, Zhe; Jin, Hailin; Yang, Jianchao; Wang, James Z

    2015-12-01

    Image priors are essential to many image restoration applications, including denoising, deblurring, and inpainting. Existing methods use either priors from the given image (internal) or priors from a separate collection of images (external). We find through statistical analysis that unifying the internal and external patch priors may yield a better patch prior. We propose a novel prior learning algorithm that combines the strength of both internal and external priors. In particular, we first learn a generic Gaussian mixture model from a collection of training images and then adapt the model to the given image by simultaneously adding additional components and refining the component parameters. We apply this image-specific prior to image denoising. The experimental results show that our approach yields better or competitive denoising results in terms of both the peak signal-to-noise ratio and structural similarity.

  1. Nonlocal means image denoising using orthogonal moments.

    PubMed

    Kumar, Ahlad

    2015-09-20

    An image denoising method in moment domain has been proposed. The denoising involves the development and evaluation based on the modified nonlocal means (NLM) algorithm. It uses the similarity of the neighborhood, evaluated using Krawtchouk moments. The results of the proposed denoising method have been validated using peak signal-to-noise ratio (PSNR), a well-known quality measure such as structural similarity (SSIM) index and blind/referenceless image spatial quality evaluator (BRISQUE). The denoising algorithm has been evaluated for synthetic and real clinical images contaminated by Gaussian, Poisson, and Rician noise. The algorithm performs well compared to the Zernike based denoising as indicated by the PSNR, SSIM, and BRISQUE scores of the denoised images with an improvement of 3.1 dB, 0.1285, and 4.23, respectively. Further, comparative analysis of the proposed work with the existing techniques has also been performed. It has been observed that the results are competitive in terms of PSNR, SSIM, and BRISQUE scores when evaluated for varying levels of noise.

  2. Geodesic denoising for optical coherence tomography images

    NASA Astrophysics Data System (ADS)

    Shahrian Varnousfaderani, Ehsan; Vogl, Wolf-Dieter; Wu, Jing; Gerendas, Bianca S.; Simader, Christian; Langs, Georg; Waldstein, Sebastian M.; Schmidt-Erfurth, Ursula

    2016-03-01

    Optical coherence tomography (OCT) is an optical signal acquisition method capturing micrometer resolution, cross-sectional three-dimensional images. OCT images are used widely in ophthalmology to diagnose and monitor retinal diseases such as age-related macular degeneration (AMD) and Glaucoma. While OCT allows the visualization of retinal structures such as vessels and retinal layers, image quality and contrast is reduced by speckle noise, obfuscating small, low intensity structures and structural boundaries. Existing denoising methods for OCT images may remove clinically significant image features such as texture and boundaries of anomalies. In this paper, we propose a novel patch based denoising method, Geodesic Denoising. The method reduces noise in OCT images while preserving clinically significant, although small, pathological structures, such as fluid-filled cysts in diseased retinas. Our method selects optimal image patch distribution representations based on geodesic patch similarity to noisy samples. Patch distributions are then randomly sampled to build a set of best matching candidates for every noisy sample, and the denoised value is computed based on a geodesic weighted average of the best candidate samples. Our method is evaluated qualitatively on real pathological OCT scans and quantitatively on a proposed set of ground truth, noise free synthetic OCT scans with artificially added noise and pathologies. Experimental results show that performance of our method is comparable with state of the art denoising methods while outperforming them in preserving the critical clinically relevant structures.

  3. Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising.

    PubMed

    Zhang, Kai; Zuo, Wangmeng; Chen, Yunjin; Meng, Deyu; Zhang, Lei

    2017-02-01

    Discriminative model learning for image denoising has been recently attracting considerable attentions due to its favorable denoising performance. In this paper, we take one step forward by investigating the construction of feed-forward denoising convolutional neural networks (DnCNNs) to embrace the progress in very deep architecture, learning algorithm, and regularization method into image denoising. Specifically, residual learning and batch normalization are utilized to speed up the training process as well as boost the denoising performance. Different from the existing discriminative denoising models which usually train a specific model for additive white Gaussian noise (AWGN) at a certain noise level, our DnCNN model is able to handle Gaussian denoising with unknown noise level (i.e., blind Gaussian denoising). With the residual learning strategy, DnCNN implicitly removes the latent clean image in the hidden layers. This property motivates us to train a single DnCNN model to tackle with several general image denoising tasks such as Gaussian denoising, single image super-resolution and JPEG image deblocking. Our extensive experiments demonstrate that our DnCNN model can not only exhibit high effectiveness in several general image denoising tasks, but also be efficiently implemented by benefiting from GPU computing.

  4. True 3d Images and Their Applications

    NASA Astrophysics Data System (ADS)

    Wang, Z.; wang@hzgeospace., zheng.

    2012-07-01

    A true 3D image is a geo-referenced image. Besides having its radiometric information, it also has true 3Dground coordinates XYZ for every pixels of it. For a true 3D image, especially a true 3D oblique image, it has true 3D coordinates not only for building roofs and/or open grounds, but also for all other visible objects on the ground, such as visible building walls/windows and even trees. The true 3D image breaks the 2D barrier of the traditional orthophotos by introducing the third dimension (elevation) into the image. From a true 3D image, for example, people will not only be able to read a building's location (XY), but also its height (Z). true 3D images will fundamentally change, if not revolutionize, the way people display, look, extract, use, and represent the geospatial information from imagery. In many areas, true 3D images can make profound impacts on the ways of how geospatial information is represented, how true 3D ground modeling is performed, and how the real world scenes are presented. This paper first gives a definition and description of a true 3D image and followed by a brief review of what key advancements of geospatial technologies have made the creation of true 3D images possible. Next, the paper introduces what a true 3D image is made of. Then, the paper discusses some possible contributions and impacts the true 3D images can make to geospatial information fields. At the end, the paper presents a list of the benefits of having and using true 3D images and the applications of true 3D images in a couple of 3D city modeling projects.

  5. Streak image denoising and segmentation using adaptive Gaussian guided filter.

    PubMed

    Jiang, Zhuocheng; Guo, Baoping

    2014-09-10

    In streak tube imaging lidar (STIL), streak images are obtained using a CCD camera. However, noise in the captured streak images can greatly affect the quality of reconstructed 3D contrast and range images. The greatest challenge for streak image denoising is reducing the noise while preserving details. In this paper, we propose an adaptive Gaussian guided filter (AGGF) for noise removal and detail enhancement of streak images. The proposed algorithm is based on a guided filter (GF) and part of an adaptive bilateral filter (ABF). In the AGGF, the details are enhanced by optimizing the offset parameter. AGGF-denoised streak images are significantly sharper than those denoised by the GF. Moreover, the AGGF is a fast linear time algorithm achieved by recursively implementing a Gaussian filter kernel. Experimentally, AGGF demonstrates its capacity to preserve edges and thin structures and outperforms the existing bilateral filter and domain transform filter in terms of both visual quality and peak signal-to-noise ratio performance.

  6. 3D carotid plaque MR Imaging

    PubMed Central

    Parker, Dennis L.

    2015-01-01

    SYNOPSIS There has been significant progress made in 3D carotid plaque magnetic resonance imaging techniques in recent years. 3D plaque imaging clearly represents the future in clinical use. With effective flow suppression techniques, choices of different contrast weighting acquisitions, and time-efficient imaging approaches, 3D plaque imaging offers flexible imaging plane and view angle analysis, large coverage, multi-vascular beds capability, and even can be used in fast screening. PMID:26610656

  7. An open-source Matlab code package for improved rank-reduction 3D seismic data denoising and reconstruction

    NASA Astrophysics Data System (ADS)

    Chen, Yangkang; Huang, Weilin; Zhang, Dong; Chen, Wei

    2016-10-01

    Simultaneous seismic data denoising and reconstruction is a currently popular research subject in modern reflection seismology. Traditional rank-reduction based 3D seismic data denoising and reconstruction algorithm will cause strong residual noise in the reconstructed data and thus affect the following processing and interpretation tasks. In this paper, we propose an improved rank-reduction method by modifying the truncated singular value decomposition (TSVD) formula used in the traditional method. The proposed approach can help us obtain nearly perfect reconstruction performance even in the case of low signal-to-noise ratio (SNR). The proposed algorithm is tested via one synthetic and field data examples. Considering that seismic data interpolation and denoising source packages are seldom in the public domain, we also provide a program template for the rank-reduction based simultaneous denoising and reconstruction algorithm by providing an open-source Matlab package.

  8. Adaptive Image Denoising by Mixture Adaptation

    NASA Astrophysics Data System (ADS)

    Luo, Enming; Chan, Stanley H.; Nguyen, Truong Q.

    2016-10-01

    We propose an adaptive learning procedure to learn patch-based image priors for image denoising. The new algorithm, called the Expectation-Maximization (EM) adaptation, takes a generic prior learned from a generic external database and adapts it to the noisy image to generate a specific prior. Different from existing methods that combine internal and external statistics in ad-hoc ways, the proposed algorithm is rigorously derived from a Bayesian hyper-prior perspective. There are two contributions of this paper: First, we provide full derivation of the EM adaptation algorithm and demonstrate methods to improve the computational complexity. Second, in the absence of the latent clean image, we show how EM adaptation can be modified based on pre-filtering. Experimental results show that the proposed adaptation algorithm yields consistently better denoising results than the one without adaptation and is superior to several state-of-the-art algorithms.

  9. Adaptive Image Denoising by Mixture Adaptation.

    PubMed

    Luo, Enming; Chan, Stanley H; Nguyen, Truong Q

    2016-10-01

    We propose an adaptive learning procedure to learn patch-based image priors for image denoising. The new algorithm, called the expectation-maximization (EM) adaptation, takes a generic prior learned from a generic external database and adapts it to the noisy image to generate a specific prior. Different from existing methods that combine internal and external statistics in ad hoc ways, the proposed algorithm is rigorously derived from a Bayesian hyper-prior perspective. There are two contributions of this paper. First, we provide full derivation of the EM adaptation algorithm and demonstrate methods to improve the computational complexity. Second, in the absence of the latent clean image, we show how EM adaptation can be modified based on pre-filtering. The experimental results show that the proposed adaptation algorithm yields consistently better denoising results than the one without adaptation and is superior to several state-of-the-art algorithms.

  10. Nonlocal Markovian models for image denoising

    NASA Astrophysics Data System (ADS)

    Salvadeo, Denis H. P.; Mascarenhas, Nelson D. A.; Levada, Alexandre L. M.

    2016-01-01

    Currently, the state-of-the art methods for image denoising are patch-based approaches. Redundant information present in nonlocal regions (patches) of the image is considered for better image modeling, resulting in an improved quality of filtering. In this respect, nonlocal Markov random field (MRF) models are proposed by redefining the energy functions of classical MRF models to adopt a nonlocal approach. With the new energy functions, the pairwise pixel interaction is weighted according to the similarities between the patches corresponding to each pair. Also, a maximum pseudolikelihood estimation of the spatial dependency parameter (β) for these models is presented here. For evaluating this proposal, these models are used as an a priori model in a maximum a posteriori estimation to denoise additive white Gaussian noise in images. Finally, results display a notable improvement in both quantitative and qualitative terms in comparison with the local MRFs.

  11. Simultaneous denoising and compression of multispectral images

    NASA Astrophysics Data System (ADS)

    Hagag, Ahmed; Amin, Mohamed; Abd El-Samie, Fathi E.

    2013-01-01

    A new technique for denoising and compression of multispectral satellite images to remove the effect of noise on the compression process is presented. One type of multispectral images has been considered: Landsat Enhanced Thematic Mapper Plus. The discrete wavelet transform (DWT), the dual-tree DWT, and a simple Huffman coder are used in the compression process. Simulation results show that the proposed technique is more effective than other traditional compression-only techniques.

  12. Efficiency analysis for 3D filtering of multichannel images

    NASA Astrophysics Data System (ADS)

    Kozhemiakin, Ruslan A.; Rubel, Oleksii; Abramov, Sergey K.; Lukin, Vladimir V.; Vozel, Benoit; Chehdi, Kacem

    2016-10-01

    Modern remote sensing systems basically acquire images that are multichannel (dual- or multi-polarization, multi- and hyperspectral) where noise, usually with different characteristics, is present in all components. If noise is intensive, it is desirable to remove (suppress) it before applying methods of image classification, interpreting, and information extraction. This can be done using one of two approaches - by component-wise or by vectorial (3D) filtering. The second approach has shown itself to have higher efficiency if there is essential correlation between multichannel image components as this often happens for multichannel remote sensing data of different origin. Within the class of 3D filtering techniques, there are many possibilities and variations. In this paper, we consider filtering based on discrete cosine transform (DCT) and pay attention to two aspects of processing. First, we study in detail what changes in DCT coefficient statistics take place for 3D denoising compared to component-wise processing. Second, we analyze how selection of component images united into 3D data array influences efficiency of filtering and can the observed tendencies be exploited in processing of images with rather large number of channels.

  13. Noise distribution and denoising of current density images.

    PubMed

    Beheshti, Mohammadali; Foomany, Farbod H; Magtibay, Karl; Jaffray, David A; Krishnan, Sridhar; Nanthakumar, Kumaraswamy; Umapathy, Karthikeyan

    2015-04-01

    Current density imaging (CDI) is a magnetic resonance (MR) imaging technique that could be used to study current pathways inside the tissue. The current distribution is measured indirectly as phase changes. The inherent noise in the MR imaging technique degrades the accuracy of phase measurements leading to imprecise current variations. The outcome can be affected significantly, especially at a low signal-to-noise ratio (SNR). We have shown the residual noise distribution of the phase to be Gaussian-like and the noise in CDI images approximated as a Gaussian. This finding matches experimental results. We further investigated this finding by performing comparative analysis with denoising techniques, using two CDI datasets with two different currents (20 and 45 mA). We found that the block-matching and three-dimensional (BM3D) technique outperforms other techniques when applied on current density ([Formula: see text]). The minimum gain in noise power by BM3D applied to [Formula: see text] compared with the next best technique in the analysis was found to be around 2 dB per pixel. We characterize the noise profile in CDI images and provide insights on the performance of different denoising techniques when applied at two different stages of current density reconstruction.

  14. 3-D Adaptive Sparsity Based Image Compression with Applications to Optical Coherence Tomography

    PubMed Central

    Fang, Leyuan; Li, Shutao; Kang, Xudong; Izatt, Joseph A.; Farsiu, Sina

    2015-01-01

    We present a novel general-purpose compression method for tomographic images, termed 3D adaptive sparse representation based compression (3D-ASRC). In this paper, we focus on applications of 3D-ASRC for the compression of ophthalmic 3D optical coherence tomography (OCT) images. The 3D-ASRC algorithm exploits correlations among adjacent OCT images to improve compression performance, yet is sensitive to preserving their differences. Due to the inherent denoising mechanism of the sparsity based 3D-ASRC, the quality of the compressed images are often better than the raw images they are based on. Experiments on clinical-grade retinal OCT images demonstrate the superiority of the proposed 3D-ASRC over other well-known compression methods. PMID:25561591

  15. Digital holography and 3-D imaging.

    PubMed

    Banerjee, Partha; Barbastathis, George; Kim, Myung; Kukhtarev, Nickolai

    2011-03-01

    This feature issue on Digital Holography and 3-D Imaging comprises 15 papers on digital holographic techniques and applications, computer-generated holography and encryption techniques, and 3-D display. It is hoped that future work in the area leads to innovative applications of digital holography and 3-D imaging to biology and sensing, and to the development of novel nonlinear dynamic digital holographic techniques.

  16. Musculoskeletal ultrasound image denoising using Daubechies wavelets

    NASA Astrophysics Data System (ADS)

    Gupta, Rishu; Elamvazuthi, I.; Vasant, P.

    2012-11-01

    Among various existing medical imaging modalities Ultrasound is providing promising future because of its ease availability and use of non-ionizing radiations. In this paper we have attempted to denoise ultrasound image using daubechies wavelet and analyze the results with peak signal to noise ratio and coefficient of correlation as performance measurement index. The different daubechies from 1 to 6 is used on four different ultrasound bone fracture images with three different levels from 1 to 3. The images for visual inspection and PSNR, Coefficient of correlation values are graphically shown for quantitaive analysis of resultant images.

  17. [A non-local means approach for PET image denoising].

    PubMed

    Yin, Yong; Sun, Weifeng; Lu, Jie; Liu, Tonghai

    2010-04-01

    Denoising is an important issue for medical image processing. Based on the analysis of the Non-local means algorithm recently reported by Buades A, et al. in international journals we herein propose adapting it for PET image denoising. Experimental de-noising results for real clinical PET images show that Non-local means method is superior to median filtering and wiener filtering methods and it can suppress noise in PET images effectively and preserve important details of structure for diagnosis.

  18. 3D ultrafast ultrasound imaging in vivo.

    PubMed

    Provost, Jean; Papadacci, Clement; Arango, Juan Esteban; Imbault, Marion; Fink, Mathias; Gennisson, Jean-Luc; Tanter, Mickael; Pernot, Mathieu

    2014-10-07

    Very high frame rate ultrasound imaging has recently allowed for the extension of the applications of echography to new fields of study such as the functional imaging of the brain, cardiac electrophysiology, and the quantitative imaging of the intrinsic mechanical properties of tumors, to name a few, non-invasively and in real time. In this study, we present the first implementation of Ultrafast Ultrasound Imaging in 3D based on the use of either diverging or plane waves emanating from a sparse virtual array located behind the probe. It achieves high contrast and resolution while maintaining imaging rates of thousands of volumes per second. A customized portable ultrasound system was developed to sample 1024 independent channels and to drive a 32  ×  32 matrix-array probe. Its ability to track in 3D transient phenomena occurring in the millisecond range within a single ultrafast acquisition was demonstrated for 3D Shear-Wave Imaging, 3D Ultrafast Doppler Imaging, and, finally, 3D Ultrafast combined Tissue and Flow Doppler Imaging. The propagation of shear waves was tracked in a phantom and used to characterize its stiffness. 3D Ultrafast Doppler was used to obtain 3D maps of Pulsed Doppler, Color Doppler, and Power Doppler quantities in a single acquisition and revealed, at thousands of volumes per second, the complex 3D flow patterns occurring in the ventricles of the human heart during an entire cardiac cycle, as well as the 3D in vivo interaction of blood flow and wall motion during the pulse wave in the carotid at the bifurcation. This study demonstrates the potential of 3D Ultrafast Ultrasound Imaging for the 3D mapping of stiffness, tissue motion, and flow in humans in vivo and promises new clinical applications of ultrasound with reduced intra--and inter-observer variability.

  19. 3D ultrafast ultrasound imaging in vivo

    NASA Astrophysics Data System (ADS)

    Provost, Jean; Papadacci, Clement; Esteban Arango, Juan; Imbault, Marion; Fink, Mathias; Gennisson, Jean-Luc; Tanter, Mickael; Pernot, Mathieu

    2014-10-01

    Very high frame rate ultrasound imaging has recently allowed for the extension of the applications of echography to new fields of study such as the functional imaging of the brain, cardiac electrophysiology, and the quantitative imaging of the intrinsic mechanical properties of tumors, to name a few, non-invasively and in real time. In this study, we present the first implementation of Ultrafast Ultrasound Imaging in 3D based on the use of either diverging or plane waves emanating from a sparse virtual array located behind the probe. It achieves high contrast and resolution while maintaining imaging rates of thousands of volumes per second. A customized portable ultrasound system was developed to sample 1024 independent channels and to drive a 32  ×  32 matrix-array probe. Its ability to track in 3D transient phenomena occurring in the millisecond range within a single ultrafast acquisition was demonstrated for 3D Shear-Wave Imaging, 3D Ultrafast Doppler Imaging, and, finally, 3D Ultrafast combined Tissue and Flow Doppler Imaging. The propagation of shear waves was tracked in a phantom and used to characterize its stiffness. 3D Ultrafast Doppler was used to obtain 3D maps of Pulsed Doppler, Color Doppler, and Power Doppler quantities in a single acquisition and revealed, at thousands of volumes per second, the complex 3D flow patterns occurring in the ventricles of the human heart during an entire cardiac cycle, as well as the 3D in vivo interaction of blood flow and wall motion during the pulse wave in the carotid at the bifurcation. This study demonstrates the potential of 3D Ultrafast Ultrasound Imaging for the 3D mapping of stiffness, tissue motion, and flow in humans in vivo and promises new clinical applications of ultrasound with reduced intra—and inter-observer variability.

  20. Postprocessing of Compressed Images via Sequential Denoising

    NASA Astrophysics Data System (ADS)

    Dar, Yehuda; Bruckstein, Alfred M.; Elad, Michael; Giryes, Raja

    2016-07-01

    In this work we propose a novel postprocessing technique for compression-artifact reduction. Our approach is based on posing this task as an inverse problem, with a regularization that leverages on existing state-of-the-art image denoising algorithms. We rely on the recently proposed Plug-and-Play Prior framework, suggesting the solution of general inverse problems via Alternating Direction Method of Multipliers (ADMM), leading to a sequence of Gaussian denoising steps. A key feature in our scheme is a linearization of the compression-decompression process, so as to get a formulation that can be optimized. In addition, we supply a thorough analysis of this linear approximation for several basic compression procedures. The proposed method is suitable for diverse compression techniques that rely on transform coding. Specifically, we demonstrate impressive gains in image quality for several leading compression methods - JPEG, JPEG2000, and HEVC.

  1. 3D Backscatter Imaging System

    NASA Technical Reports Server (NTRS)

    Turner, D. Clark (Inventor); Whitaker, Ross (Inventor)

    2016-01-01

    Systems and methods for imaging an object using backscattered radiation are described. The imaging system comprises both a radiation source for irradiating an object that is rotationally movable about the object, and a detector for detecting backscattered radiation from the object that can be disposed on substantially the same side of the object as the source and which can be rotationally movable about the object. The detector can be separated into multiple detector segments with each segment having a single line of sight projection through the object and so detects radiation along that line of sight. Thus, each detector segment can isolate the desired component of the backscattered radiation. By moving independently of each other about the object, the source and detector can collect multiple images of the object at different angles of rotation and generate a three dimensional reconstruction of the object. Other embodiments are described.

  2. 3D Ultrafast Ultrasound Imaging In Vivo

    PubMed Central

    Provost, Jean; Papadacci, Clement; Arango, Juan Esteban; Imbault, Marion; Gennisson, Jean-Luc; Tanter, Mickael; Pernot, Mathieu

    2014-01-01

    Very high frame rate ultrasound imaging has recently allowed for the extension of the applications of echography to new fields of study such as the functional imaging of the brain, cardiac electrophysiology, and the quantitative real-time imaging of the intrinsic mechanical properties of tumors, to name a few, non-invasively and in real time. In this study, we present the first implementation of Ultrafast Ultrasound Imaging in three dimensions based on the use of either diverging or plane waves emanating from a sparse virtual array located behind the probe. It achieves high contrast and resolution while maintaining imaging rates of thousands of volumes per second. A customized portable ultrasound system was developed to sample 1024 independent channels and to drive a 32×32 matrix-array probe. Its capability to track in 3D transient phenomena occurring in the millisecond range within a single ultrafast acquisition was demonstrated for 3-D Shear-Wave Imaging, 3-D Ultrafast Doppler Imaging and finally 3D Ultrafast combined Tissue and Flow Doppler. The propagation of shear waves was tracked in a phantom and used to characterize its stiffness. 3-D Ultrafast Doppler was used to obtain 3-D maps of Pulsed Doppler, Color Doppler, and Power Doppler quantities in a single acquisition and revealed, for the first time, the complex 3-D flow patterns occurring in the ventricles of the human heart during an entire cardiac cycle, and the 3-D in vivo interaction of blood flow and wall motion during the pulse wave in the carotid at the bifurcation. This study demonstrates the potential of 3-D Ultrafast Ultrasound Imaging for the 3-D real-time mapping of stiffness, tissue motion, and flow in humans in vivo and promises new clinical applications of ultrasound with reduced intra- and inter-observer variability. PMID:25207828

  3. A new structure of 3D dual-tree discrete wavelet transforms and applications to video denoising and coding

    NASA Astrophysics Data System (ADS)

    Shi, Fei; Wang, Beibei; Selesnick, Ivan W.; Wang, Yao

    2006-01-01

    This paper introduces an anisotropic decomposition structure of a recently introduced 3-D dual-tree discrete wavelet transform (DDWT), and explores the applications for video denoising and coding. The 3-D DDWT is an attractive video representation because it isolates motion along different directions in separate subbands, and thus leads to sparse video decompositions. Our previous investigation shows that the 3-D DDWT, compared to the standard discrete wavelet transform (DWT), complies better with the statistical models based on sparse presumptions, and gives better visual and numerical results when used for statistical denoising algorithms. Our research on video compression also shows that even with 4:1 redundancy, the 3-D DDWT needs fewer coefficients to achieve the same coding quality (in PSNR) by applying the iterative projection-based noise shaping scheme proposed by Kingsbury. The proposed anisotropic DDWT extends the superiority of isotropic DDWT with more directional subbands without adding to the redundancy. Unlike the original 3-D DDWT which applies dyadic decomposition along all three directions and produces isotropic frequency spacing, it has a non-uniform tiling of the frequency space. By applying this structure, we can improve the denoising results, and the number of significant coefficients can be reduced further, which is beneficial for video coding.

  4. Group-sparse representation with dictionary learning for medical image denoising and fusion.

    PubMed

    Li, Shutao; Yin, Haitao; Fang, Leyuan

    2012-12-01

    Recently, sparse representation has attracted a lot of interest in various areas. However, the standard sparse representation does not consider the intrinsic structure, i.e., the nonzero elements occur in clusters, called group sparsity. Furthermore, there is no dictionary learning method for group sparse representation considering the geometrical structure of space spanned by atoms. In this paper, we propose a novel dictionary learning method, called Dictionary Learning with Group Sparsity and Graph Regularization (DL-GSGR). First, the geometrical structure of atoms is modeled as the graph regularization. Then, combining group sparsity and graph regularization, the DL-GSGR is presented, which is solved by alternating the group sparse coding and dictionary updating. In this way, the group coherence of learned dictionary can be enforced small enough such that any signal can be group sparse coded effectively. Finally, group sparse representation with DL-GSGR is applied to 3-D medical image denoising and image fusion. Specifically, in 3-D medical image denoising, a 3-D processing mechanism (using the similarity among nearby slices) and temporal regularization (to perverse the correlations across nearby slices) are exploited. The experimental results on 3-D image denoising and image fusion demonstrate the superiority of our proposed denoising and fusion approaches.

  5. PRINCIPAL COMPONENTS FOR NON-LOCAL MEANS IMAGE DENOISING.

    PubMed

    Tasdizen, Tolga

    2008-01-01

    This paper presents an image denoising algorithm that uses principal component analysis (PCA) in conjunction with the non-local means image denoising. Image neighborhood vectors used in the non-local means algorithm are first projected onto a lower-dimensional subspace using PCA. Consequently, neighborhood similarity weights for denoising are computed using distances in this subspace rather than the full space. This modification to the non-local means algorithm results in improved accuracy and computational performance. We present an analysis of the proposed method's accuracy as a function of the dimensionality of the projection subspace and demonstrate that denoising accuracy peaks at a relatively low number of dimensions.

  6. Fast Translation Invariant Multiscale Image Denoising.

    PubMed

    Li, Meng; Ghosal, Subhashis

    2015-12-01

    Translation invariant (TI) cycle spinning is an effective method for removing artifacts from images. However, for a method using O(n) time, the exact TI cycle spinning by averaging all possible circulant shifts requires O(n(2)) time where n is the number of pixels, and therefore is not feasible in practice. Existing literature has investigated efficient algorithms to calculate TI version of some denoising approaches such as Haar wavelet. Multiscale methods, especially those based on likelihood decomposition, such as penalized likelihood estimator and Bayesian methods, have become popular in image processing because of their effectiveness in denoising images. As far as we know, there is no systematic investigation of the TI calculation corresponding to general multiscale approaches. In this paper, we propose a fast TI (FTI) algorithm and a more general k-TI (k-TI) algorithm allowing TI for the last k scales of the image, which are applicable to general d-dimensional images (d = 2, 3, …) with either Gaussian or Poisson noise. The proposed FTI leads to the exact TI estimation but only requires O(n log2 n) time. The proposed k-TI can achieve almost the same performance as the exact TI estimation, but requires even less time. We achieve this by exploiting the regularity present in the multiscale structure, which is justified theoretically. The proposed FTI and k-TI are generic in that they are applicable on any smoothing techniques based on the multiscale structure. We demonstrate the FTI and k-TI algorithms on some recently proposed state-of-the-art methods for both Poisson and Gaussian noised images. Both simulations and real data application confirm the appealing performance of the proposed algorithms. MATLAB toolboxes are online accessible to reproduce the results and be implemented for general multiscale denoising approaches provided by the users.

  7. Image denoising using a tight frame.

    PubMed

    Shen, Lixin; Papadakis, Manos; Kakadiaris, Ioannis A; Konstantinidis, Ioannis; Kouri, Donald; Hoffman, David

    2006-05-01

    We present a general mathematical theory for lifting frames that allows us to modify existing filters to construct new ones that form Parseval frames. We apply our theory to design nonseparable Parseval frames from separable (tensor) products of a piecewise linear spline tight frame. These new frame systems incorporate the weighted average operator, the Sobel operator, and the Laplacian operator in directions that are integer multiples of 45 degrees. A new image denoising algorithm is then proposed, tailored to the specific properties of these new frame filters. We demonstrate the performance of our algorithm on a diverse set of images with very encouraging results.

  8. 3D imaging in forensic odontology.

    PubMed

    Evans, Sam; Jones, Carl; Plassmann, Peter

    2010-06-16

    This paper describes the investigation of a new 3D capture method for acquiring and subsequent forensic analysis of bite mark injuries on human skin. When documenting bite marks with standard 2D cameras errors in photographic technique can occur if best practice is not followed. Subsequent forensic analysis of the mark is problematic when a 3D structure is recorded into a 2D space. Although strict guidelines (BAFO) exist, these are time-consuming to follow and, due to their complexity, may produce errors. A 3D image capture and processing system might avoid the problems resulting from the 2D reduction process, simplifying the guidelines and reducing errors. Proposed Solution: a series of experiments are described in this paper to demonstrate that the potential of a 3D system might produce suitable results. The experiments tested precision and accuracy of the traditional 2D and 3D methods. A 3D image capture device minimises the amount of angular distortion, therefore such a system has the potential to create more robust forensic evidence for use in courts. A first set of experiments tested and demonstrated which method of forensic analysis creates the least amount of intra-operator error. A second set tested and demonstrated which method of image capture creates the least amount of inter-operator error and visual distortion. In a third set the effects of angular distortion on 2D and 3D methods of image capture were evaluated.

  9. Nonlaser-based 3D surface imaging

    SciTech Connect

    Lu, Shin-yee; Johnson, R.K.; Sherwood, R.J.

    1994-11-15

    3D surface imaging refers to methods that generate a 3D surface representation of objects of a scene under viewing. Laser-based 3D surface imaging systems are commonly used in manufacturing, robotics and biomedical research. Although laser-based systems provide satisfactory solutions for most applications, there are situations where non laser-based approaches are preferred. The issues that make alternative methods sometimes more attractive are: (1) real-time data capturing, (2) eye-safety, (3) portability, and (4) work distance. The focus of this presentation is on generating a 3D surface from multiple 2D projected images using CCD cameras, without a laser light source. Two methods are presented: stereo vision and depth-from-focus. Their applications are described.

  10. Combining interior and exterior characteristics for remote sensing image denoising

    NASA Astrophysics Data System (ADS)

    Peng, Ni; Sun, Shujin; Wang, Runsheng; Zhong, Ping

    2016-04-01

    Remote sensing image denoising faces many challenges since a remote sensing image usually covers a wide area and thus contains complex contents. Using the patch-based statistical characteristics is a flexible method to improve the denoising performance. There are usually two kinds of statistical characteristics available: interior and exterior characteristics. Different statistical characteristics have their own strengths to restore specific image contents. Combining different statistical characteristics to use their strengths together may have the potential to improve denoising results. This work proposes a method combining statistical characteristics to adaptively select statistical characteristics for different image contents. The proposed approach is implemented through a new characteristics selection criterion learned over training data. Moreover, with the proposed combination method, this work develops a denoising algorithm for remote sensing images. Experimental results show that our method can make full use of the advantages of interior and exterior characteristics for different image contents and thus improve the denoising performance.

  11. Remote sensing image denoising by using discrete multiwavelet transform techniques

    NASA Astrophysics Data System (ADS)

    Wang, Haihui; Wang, Jun; Zhang, Jian

    2006-01-01

    We present a new method by using GHM discrete multiwavelet transform in image denoising on this paper. The developments in wavelet theory have given rise to the wavelet thresholding method, for extracting a signal from noisy data. The method of signal denoising via wavelet thresholding was popularized. Multiwavelets have recently been introduced and they offer simultaneous orthogonality, symmetry and short support. This property makes multiwavelets more suitable for various image processing applications, especially denoising. It is based on thresholding of multiwavelet coefficients arising from the standard scalar orthogonal wavelet transform. It takes into account the covariance structure of the transform. Denoising of images via thresholding of the multiwavelet coefficients result from preprocessing and the discrete multiwavelet transform can be carried out by treating the output in this paper. The form of the threshold is carefully formulated and is the key to the excellent results obtained in the extensive numerical simulations of image denoising. We apply the multiwavelet-based to remote sensing image denoising. Multiwavelet transform technique is rather a new method, and it has a big advantage over the other techniques that it less distorts spectral characteristics of the image denoising. The experimental results show that multiwavelet based image denoising schemes outperform wavelet based method both subjectively and objectively.

  12. Improved Denoising via Poisson Mixture Modeling of Image Sensor Noise.

    PubMed

    Zhang, Jiachao; Hirakawa, Keigo

    2017-04-01

    This paper describes a study aimed at comparing the real image sensor noise distribution to the models of noise often assumed in image denoising designs. A quantile analysis in pixel, wavelet transform, and variance stabilization domains reveal that the tails of Poisson, signal-dependent Gaussian, and Poisson-Gaussian models are too short to capture real sensor noise behavior. A new Poisson mixture noise model is proposed to correct the mismatch of tail behavior. Based on the fact that noise model mismatch results in image denoising that undersmoothes real sensor data, we propose a mixture of Poisson denoising method to remove the denoising artifacts without affecting image details, such as edge and textures. Experiments with real sensor data verify that denoising for real image sensor data is indeed improved by this new technique.

  13. Edge-preserving image denoising via group coordinate descent on the GPU.

    PubMed

    McGaffin, Madison Gray; Fessler, Jeffrey A

    2015-04-01

    Image denoising is a fundamental operation in image processing, and its applications range from the direct (photographic enhancement) to the technical (as a subproblem in image reconstruction algorithms). In many applications, the number of pixels has continued to grow, while the serial execution speed of computational hardware has begun to stall. New image processing algorithms must exploit the power offered by massively parallel architectures like graphics processing units (GPUs). This paper describes a family of image denoising algorithms well-suited to the GPU. The algorithms iteratively perform a set of independent, parallel 1D pixel-update subproblems. To match GPU memory limitations, they perform these pixel updates in-place and only store the noisy data, denoised image, and problem parameters. The algorithms can handle a wide range of edge-preserving roughness penalties, including differentiable convex penalties and anisotropic total variation. Both algorithms use the majorize-minimize framework to solve the 1D pixel update subproblem. Results from a large 2D image denoising problem and a 3D medical imaging denoising problem demonstrate that the proposed algorithms converge rapidly in terms of both iteration and run-time.

  14. Edge-preserving image denoising via group coordinate descent on the GPU

    PubMed Central

    McGaffin, Madison G.; Fessler, Jeffrey A.

    2015-01-01

    Image denoising is a fundamental operation in image processing, and its applications range from the direct (photographic enhancement) to the technical (as a subproblem in image reconstruction algorithms). In many applications, the number of pixels has continued to grow, while the serial execution speed of computational hardware has begun to stall. New image processing algorithms must exploit the power offered by massively parallel architectures like graphics processing units (GPUs). This paper describes a family of image denoising algorithms well-suited to the GPU. The algorithms iteratively perform a set of independent, parallel one-dimensional pixel-update subproblems. To match GPU memory limitations, they perform these pixel updates inplace and only store the noisy data, denoised image and problem parameters. The algorithms can handle a wide range of edge-preserving roughness penalties, including differentiable convex penalties and anisotropic total variation (TV). Both algorithms use the majorize-minimize (MM) framework to solve the one-dimensional pixel update subproblem. Results from a large 2D image denoising problem and a 3D medical imaging denoising problem demonstrate that the proposed algorithms converge rapidly in terms of both iteration and run-time. PMID:25675454

  15. 3D integral imaging with optical processing

    NASA Astrophysics Data System (ADS)

    Martínez-Corral, Manuel; Martínez-Cuenca, Raúl; Saavedra, Genaro; Javidi, Bahram

    2008-04-01

    Integral imaging (InI) systems are imaging devices that provide auto-stereoscopic images of 3D intensity objects. Since the birth of this new technology, InI systems have faced satisfactorily many of their initial drawbacks. Basically, two kind of procedures have been used: digital and optical procedures. The "3D Imaging and Display Group" at the University of Valencia, with the essential collaboration of Prof. Javidi, has centered its efforts in the 3D InI with optical processing. Among other achievements, our Group has proposed the annular amplitude modulation for enlargement of the depth of field, dynamic focusing for reduction of the facet-braiding effect, or the TRES and MATRES devices to enlarge the viewing angle.

  16. Denoising two-photon calcium imaging data.

    PubMed

    Malik, Wasim Q; Schummers, James; Sur, Mriganka; Brown, Emery N

    2011-01-01

    Two-photon calcium imaging is now an important tool for in vivo imaging of biological systems. By enabling neuronal population imaging with subcellular resolution, this modality offers an approach for gaining a fundamental understanding of brain anatomy and physiology. Proper analysis of calcium imaging data requires denoising, that is separating the signal from complex physiological noise. To analyze two-photon brain imaging data, we present a signal plus colored noise model in which the signal is represented as harmonic regression and the correlated noise is represented as an order autoregressive process. We provide an efficient cyclic descent algorithm to compute approximate maximum likelihood parameter estimates by combing a weighted least-squares procedure with the Burg algorithm. We use Akaike information criterion to guide selection of the harmonic regression and the autoregressive model orders. Our flexible yet parsimonious modeling approach reliably separates stimulus-evoked fluorescence response from background activity and noise, assesses goodness of fit, and estimates confidence intervals and signal-to-noise ratio. This refined separation leads to appreciably enhanced image contrast for individual cells including clear delineation of subcellular details and network activity. The application of our approach to in vivo imaging data recorded in the ferret primary visual cortex demonstrates that our method yields substantially denoised signal estimates. We also provide a general Volterra series framework for deriving this and other signal plus correlated noise models for imaging. This approach to analyzing two-photon calcium imaging data may be readily adapted to other computational biology problems which apply correlated noise models.

  17. A computationally efficient denoising and hole-filling method for depth image enhancement

    NASA Astrophysics Data System (ADS)

    Liu, Soulan; Chen, Chen; Kehtarnavaz, Nasser

    2016-04-01

    Depth maps captured by Kinect depth cameras are being widely used for 3D action recognition. However, such images often appear noisy and contain missing pixels or black holes. This paper presents a computationally efficient method for both denoising and hole-filling in depth images. The denoising is achieved by utilizing a combination of Gaussian kernel filtering and anisotropic filtering. The hole-filling is achieved by utilizing a combination of morphological filtering and zero block filtering. Experimental results using the publicly available datasets are provided indicating the superiority of the developed method in terms of both depth error and computational efficiency compared to three existing methods.

  18. Graph Laplacian Regularization for Image Denoising: Analysis in the Continuous Domain.

    PubMed

    Pang, Jiahao; Cheung, Gene

    2017-04-01

    Inverse imaging problems are inherently underdetermined, and hence, it is important to employ appropriate image priors for regularization. One recent popular prior-the graph Laplacian regularizer-assumes that the target pixel patch is smooth with respect to an appropriately chosen graph. However, the mechanisms and implications of imposing the graph Laplacian regularizer on the original inverse problem are not well understood. To address this problem, in this paper, we interpret neighborhood graphs of pixel patches as discrete counterparts of Riemannian manifolds and perform analysis in the continuous domain, providing insights into several fundamental aspects of graph Laplacian regularization for image denoising. Specifically, we first show the convergence of the graph Laplacian regularizer to a continuous-domain functional, integrating a norm measured in a locally adaptive metric space. Focusing on image denoising, we derive an optimal metric space assuming non-local self-similarity of pixel patches, leading to an optimal graph Laplacian regularizer for denoising in the discrete domain. We then interpret graph Laplacian regularization as an anisotropic diffusion scheme to explain its behavior during iterations, e.g., its tendency to promote piecewise smooth signals under certain settings. To verify our analysis, an iterative image denoising algorithm is developed. Experimental results show that our algorithm performs competitively with state-of-the-art denoising methods, such as BM3D for natural images, and outperforms them significantly for piecewise smooth images.

  19. Patch-based near-optimal image denoising.

    PubMed

    Chatterjee, Priyam; Milanfar, Peyman

    2012-04-01

    In this paper, we propose a denoising method motivated by our previous analysis of the performance bounds for image denoising. Insights from that study are used here to derive a high-performance practical denoising algorithm. We propose a patch-based Wiener filter that exploits patch redundancy for image denoising. Our framework uses both geometrically and photometrically similar patches to estimate the different filter parameters. We describe how these parameters can be accurately estimated directly from the input noisy image. Our denoising approach, designed for near-optimal performance (in the mean-squared error sense), has a sound statistical foundation that is analyzed in detail. The performance of our approach is experimentally verified on a variety of images and noise levels. The results presented here demonstrate that our proposed method is on par or exceeding the current state of the art, both visually and quantitatively.

  20. Performance evaluation and optimization of BM4D-AV denoising algorithm for cone-beam CT images

    NASA Astrophysics Data System (ADS)

    Huang, Kuidong; Tian, Xiaofei; Zhang, Dinghua; Zhang, Hua

    2015-12-01

    The broadening application of cone-beam Computed Tomography (CBCT) in medical diagnostics and nondestructive testing, necessitates advanced denoising algorithms for its 3D images. The block-matching and four dimensional filtering algorithm with adaptive variance (BM4D-AV) is applied to the 3D image denoising in this research. To optimize it, the key filtering parameters of the BM4D-AV algorithm are assessed firstly based on the simulated CBCT images and a table of optimized filtering parameters is obtained. Then, considering the complexity of the noise in realistic CBCT images, possible noise standard deviations in BM4D-AV are evaluated to attain the chosen principle for the realistic denoising. The results of corresponding experiments demonstrate that the BM4D-AV algorithm with optimized parameters presents excellent denosing effect on the realistic 3D CBCT images.

  1. Image denoising via sparse and redundant representations over learned dictionaries.

    PubMed

    Elad, Michael; Aharon, Michal

    2006-12-01

    We address the image denoising problem, where zero-mean white and homogeneous Gaussian additive noise is to be removed from a given image. The approach taken is based on sparse and redundant representations over trained dictionaries. Using the K-SVD algorithm, we obtain a dictionary that describes the image content effectively. Two training options are considered: using the corrupted image itself, or training on a corpus of high-quality image database. Since the K-SVD is limited in handling small image patches, we extend its deployment to arbitrary image sizes by defining a global image prior that forces sparsity over patches in every location in the image. We show how such Bayesian treatment leads to a simple and effective denoising algorithm. This leads to a state-of-the-art denoising performance, equivalent and sometimes surpassing recently published leading alternative denoising methods.

  2. Estimation of the degree of polarization in low-light 3D integral imaging

    NASA Astrophysics Data System (ADS)

    Carnicer, Artur; Javidi, Bahram

    2016-06-01

    The calculation of the Stokes Parameters and the Degree of Polarization in 3D integral images requires a careful manipulation of the polarimetric elemental images. This fact is particularly important if the scenes are taken in low-light conditions. In this paper, we show that the Degree of Polarization can be effectively estimated even when elemental images are recorded with few photons. The original idea was communicated in [A. Carnicer and B. Javidi, "Polarimetric 3D integral imaging in photon-starved conditions," Opt. Express 23, 6408-6417 (2015)]. First, we use the Maximum Likelihood Estimation approach for generating the 3D integral image. Nevertheless, this method produces very noisy images and thus, the degree of polarization cannot be calculated. We suggest using a Total Variation Denoising filter as a way to improve the quality of the generated 3D images. As a result, noise is suppressed but high frequency information is preserved. Finally, the degree of polarization is obtained successfully.

  3. ICER-3D Hyperspectral Image Compression Software

    NASA Technical Reports Server (NTRS)

    Xie, Hua; Kiely, Aaron; Klimesh, matthew; Aranki, Nazeeh

    2010-01-01

    Software has been developed to implement the ICER-3D algorithm. ICER-3D effects progressive, three-dimensional (3D), wavelet-based compression of hyperspectral images. If a compressed data stream is truncated, the progressive nature of the algorithm enables reconstruction of hyperspectral data at fidelity commensurate with the given data volume. The ICER-3D software is capable of providing either lossless or lossy compression, and incorporates an error-containment scheme to limit the effects of data loss during transmission. The compression algorithm, which was derived from the ICER image compression algorithm, includes wavelet-transform, context-modeling, and entropy coding subalgorithms. The 3D wavelet decomposition structure used by ICER-3D exploits correlations in all three dimensions of sets of hyperspectral image data, while facilitating elimination of spectral ringing artifacts, using a technique summarized in "Improving 3D Wavelet-Based Compression of Spectral Images" (NPO-41381), NASA Tech Briefs, Vol. 33, No. 3 (March 2009), page 7a. Correlation is further exploited by a context-modeling subalgorithm, which exploits spectral dependencies in the wavelet-transformed hyperspectral data, using an algorithm that is summarized in "Context Modeler for Wavelet Compression of Hyperspectral Images" (NPO-43239), which follows this article. An important feature of ICER-3D is a scheme for limiting the adverse effects of loss of data during transmission. In this scheme, as in the similar scheme used by ICER, the spatial-frequency domain is partitioned into rectangular error-containment regions. In ICER-3D, the partitions extend through all the wavelength bands. The data in each partition are compressed independently of those in the other partitions, so that loss or corruption of data from any partition does not affect the other partitions. Furthermore, because compression is progressive within each partition, when data are lost, any data from that partition received

  4. Acquisition and applications of 3D images

    NASA Astrophysics Data System (ADS)

    Sterian, Paul; Mocanu, Elena

    2007-08-01

    The moiré fringes method and their analysis up to medical and entertainment applications are discussed in this paper. We describe the procedure of capturing 3D images with an Inspeck Camera that is a real-time 3D shape acquisition system based on structured light techniques. The method is a high-resolution one. After processing the images, using computer, we can use the data for creating laser fashionable objects by engraving them with a Q-switched Nd:YAG. In medical field we mention the plastic surgery and the replacement of X-Ray especially in pediatric use.

  5. Adaptive regularization of the NL-means: application to image and video denoising.

    PubMed

    Sutour, Camille; Deledalle, Charles-Alban; Aujol, Jean-François

    2014-08-01

    Image denoising is a central problem in image processing and it is often a necessary step prior to higher level analysis such as segmentation, reconstruction, or super-resolution. The nonlocal means (NL-means) perform denoising by exploiting the natural redundancy of patterns inside an image; they perform a weighted average of pixels whose neighborhoods (patches) are close to each other. This reduces significantly the noise while preserving most of the image content. While it performs well on flat areas and textures, it suffers from two opposite drawbacks: it might over-smooth low-contrasted areas or leave a residual noise around edges and singular structures. Denoising can also be performed by total variation minimization-the Rudin, Osher and Fatemi model-which leads to restore regular images, but it is prone to over-smooth textures, staircasing effects, and contrast losses. We introduce in this paper a variational approach that corrects the over-smoothing and reduces the residual noise of the NL-means by adaptively regularizing nonlocal methods with the total variation. The proposed regularized NL-means algorithm combines these methods and reduces both of their respective defaults by minimizing an adaptive total variation with a nonlocal data fidelity term. Besides, this model adapts to different noise statistics and a fast solution can be obtained in the general case of the exponential family. We develop this model for image denoising and we adapt it to video denoising with 3D patches.

  6. A new method for mobile phone image denoising

    NASA Astrophysics Data System (ADS)

    Jin, Lianghai; Jin, Min; Li, Xiang; Xu, Xiangyang

    2015-12-01

    Images captured by mobile phone cameras via pipeline processing usually contain various kinds of noises, especially granular noise with different shapes and sizes in both luminance and chrominance channels. In chrominance channels, noise is closely related to image brightness. To improve image quality, this paper presents a new method to denoise such mobile phone images. The proposed scheme converts the noisy RGB image to luminance and chrominance images, which are then denoised by a common filtering framework. The common filtering framework processes a noisy pixel by first excluding the neighborhood pixels that significantly deviate from the (vector) median and then utilizing the other neighborhood pixels to restore the current pixel. In the framework, the strength of chrominance image denoising is controlled by image brightness. The experimental results show that the proposed method obviously outperforms some other representative denoising methods in terms of both objective measure and visual evaluation.

  7. Minimum risk wavelet shrinkage operator for Poisson image denoising.

    PubMed

    Cheng, Wu; Hirakawa, Keigo

    2015-05-01

    The pixel values of images taken by an image sensor are said to be corrupted by Poisson noise. To date, multiscale Poisson image denoising techniques have processed Haar frame and wavelet coefficients--the modeling of coefficients is enabled by the Skellam distribution analysis. We extend these results by solving for shrinkage operators for Skellam that minimizes the risk functional in the multiscale Poisson image denoising setting. The minimum risk shrinkage operator of this kind effectively produces denoised wavelet coefficients with minimum attainable L2 error.

  8. Nonlocal hierarchical dictionary learning using wavelets for image denoising.

    PubMed

    Yan, Ruomei; Shao, Ling; Liu, Yan

    2013-12-01

    Exploiting the sparsity within representation models for images is critical for image denoising. The best currently available denoising methods take advantage of the sparsity from image self-similarity, pre-learned, and fixed representations. Most of these methods, however, still have difficulties in tackling high noise levels or noise models other than Gaussian. In this paper, the multiresolution structure and sparsity of wavelets are employed by nonlocal dictionary learning in each decomposition level of the wavelets. Experimental results show that our proposed method outperforms two state-of-the-art image denoising algorithms on higher noise levels. Furthermore, our approach is more adaptive to the less extensively researched uniform noise.

  9. A comparative study of new and current methods for dental micro-CT image denoising

    PubMed Central

    Lashgari, Mojtaba; Qin, Jie; Swain, Michael

    2016-01-01

    Objectives: The aim of the current study was to evaluate the application of two advanced noise-reduction algorithms for dental micro-CT images and to implement a comparative analysis of the performance of new and current denoising algorithms. Methods: Denoising was performed using gaussian and median filters as the current filtering approaches and the block-matching and three-dimensional (BM3D) method and total variation method as the proposed new filtering techniques. The performance of the denoising methods was evaluated quantitatively using contrast-to-noise ratio (CNR), edge preserving index (EPI) and blurring indexes, as well as qualitatively using the double-stimulus continuous quality scale procedure. Results: The BM3D method had the best performance with regard to preservation of fine textural features (CNREdge), non-blurring of the whole image (blurring index), the clinical visual score in images with very fine features and the overall visual score for all types of images. On the other hand, the total variation method provided the best results with regard to smoothing of images in texture-free areas (CNRTex-free) and in preserving the edges and borders of image features (EPI). Conclusions: The BM3D method is the most reliable technique for denoising dental micro-CT images with very fine textural details, such as shallow enamel lesions, in which the preservation of the texture and fine features is of the greatest importance. On the other hand, the total variation method is the technique of choice for denoising images without very fine textural details in which the clinician or researcher is interested mainly in anatomical features and structural measurements. PMID:26764583

  10. Active segmentation of 3D axonal images.

    PubMed

    Muralidhar, Gautam S; Gopinath, Ajay; Bovik, Alan C; Ben-Yakar, Adela

    2012-01-01

    We present an active contour framework for segmenting neuronal axons on 3D confocal microscopy data. Our work is motivated by the need to conduct high throughput experiments involving microfluidic devices and femtosecond lasers to study the genetic mechanisms behind nerve regeneration and repair. While most of the applications for active contours have focused on segmenting closed regions in 2D medical and natural images, there haven't been many applications that have focused on segmenting open-ended curvilinear structures in 2D or higher dimensions. The active contour framework we present here ties together a well known 2D active contour model [5] along with the physics of projection imaging geometry to yield a segmented axon in 3D. Qualitative results illustrate the promise of our approach for segmenting neruonal axons on 3D confocal microscopy data.

  11. 3-D imaging of the CNS.

    PubMed

    Runge, V M; Gelblum, D Y; Wood, M L

    1990-01-01

    3-D gradient echo techniques, and in particular FLASH, represent a significant advance in MR imaging strategy allowing thin section, high resolution imaging through a large region of interest. Anatomical areas of application include the brain, spine, and extremities, although the majority of work to date has been performed in the brain. Superior T1 contrast and thus sensitivity to the presence of GdDTPA is achieved with 3-D FLASH when compared to 2-D spin echo technique. There is marked arterial and venous enhancement following Gd DTPA administration on 3-D FLASH, a less common finding with 2-D spin echo. Enhancement of the falx and tentorium is also more prominent. From a single data acquisition, requiring less than 11 min of scan time, high resolution reformatted sagittal, coronal, and axial images can obtained in addition to sections in any arbitrary plane. Tissue segmentation techniques can be applied and lesions displayed in three dimensions. These results may lead to the replacement of 2-D spin echo with 3-D FLASH for high resolution T1-weighted MR imaging of the CNS, particularly in the study of mass lesions and structural anomalies. The application of similar T2-weighted gradient echo techniques may follow, however the signal-to-noise ratio which can be achieved remains a potential limitation.

  12. Walker Ranch 3D seismic images

    SciTech Connect

    Robert J. Mellors

    2016-03-01

    Amplitude images (both vertical and depth slices) extracted from 3D seismic reflection survey over area of Walker Ranch area (adjacent to Raft River). Crossline spacing of 660 feet and inline of 165 feet using a Vibroseis source. Processing included depth migration. Micro-earthquake hypocenters on images. Stratigraphic information and nearby well tracks added to images. Images are embedded in a Microsoft Word document with additional information. Exact location and depth restricted for proprietary reasons. Data collection and processing funded by Agua Caliente. Original data remains property of Agua Caliente.

  13. Gradient histogram estimation and preservation for texture enhanced image denoising.

    PubMed

    Zuo, Wangmeng; Zhang, Lei; Song, Chunwei; Zhang, David; Gao, Huijun

    2014-06-01

    Natural image statistics plays an important role in image denoising, and various natural image priors, including gradient-based, sparse representation-based, and nonlocal self-similarity-based ones, have been widely studied and exploited for noise removal. In spite of the great success of many denoising algorithms, they tend to smooth the fine scale image textures when removing noise, degrading the image visual quality. To address this problem, in this paper, we propose a texture enhanced image denoising method by enforcing the gradient histogram of the denoised image to be close to a reference gradient histogram of the original image. Given the reference gradient histogram, a novel gradient histogram preservation (GHP) algorithm is developed to enhance the texture structures while removing noise. Two region-based variants of GHP are proposed for the denoising of images consisting of regions with different textures. An algorithm is also developed to effectively estimate the reference gradient histogram from the noisy observation of the unknown image. Our experimental results demonstrate that the proposed GHP algorithm can well preserve the texture appearance in the denoised images, making them look more natural.

  14. Color Image Denoising via Discriminatively Learned Iterative Shrinkage.

    PubMed

    Sun, Jian; Sun, Jian; Xu, Zingben

    2015-11-01

    In this paper, we propose a novel model, a discriminatively learned iterative shrinkage (DLIS) model, for color image denoising. The DLIS is a generalization of wavelet shrinkage by iteratively performing shrinkage over patch groups and whole image aggregation. We discriminatively learn the shrinkage functions and basis from the training pairs of noisy/noise-free images, which can adaptively handle different noise characteristics in luminance/chrominance channels, and the unknown structured noise in real-captured color images. Furthermore, to remove the splotchy real color noises, we design a Laplacian pyramid-based denoising framework to progressively recover the clean image from the coarsest scale to the finest scale by the DLIS model learned from the real color noises. Experiments show that our proposed approach can achieve the state-of-the-art denoising results on both synthetic denoising benchmark and real-captured color images.

  15. Terahertz digital holography image denoising using stationary wavelet transform

    NASA Astrophysics Data System (ADS)

    Cui, Shan-Shan; Li, Qi; Chen, Guanghao

    2015-04-01

    Terahertz (THz) holography is a frontier technology in terahertz imaging field. However, reconstructed images of holograms are inherently affected by speckle noise, on account of the coherent nature of light scattering. Stationary wavelet transform (SWT) is an effective tool in speckle noise removal. In this paper, two algorithms for despeckling SAR images are implemented to THz images based on SWT, which are threshold estimation and smoothing operation respectively. Denoised images are then quantitatively assessed by speckle index. Experimental results show that the stationary wavelet transform has superior denoising performance and image detail preservation to discrete wavelet transform. In terms of the threshold estimation, high levels of decomposing are needed for better denoising result. The smoothing operation combined with stationary wavelet transform manifests the optimal denoising effect at single decomposition level, with 5×5 average filtering.

  16. Backhoe 3D "gold standard" image

    NASA Astrophysics Data System (ADS)

    Gorham, LeRoy; Naidu, Kiranmai D.; Majumder, Uttam; Minardi, Michael A.

    2005-05-01

    ViSUAl-D (VIsual Sar Using ALl Dimensions), a 2004 DARPA/IXO seedling effort, is developing a capability for reliable high confidence ID from standoff ranges. Recent conflicts have demonstrated that the warfighter would greatly benefit from the ability to ID targets beyond visual and electro-optical ranges[1]. Forming optical-quality SAR images while exploiting full polarization, wide angles, and large bandwidth would be key evidence such a capability is achievable. Using data generated by the Xpatch EM scattering code, ViSUAl-D investigates all degrees of freedom available to the radar designer, including 6 GHz bandwidth, full polarization and angle sampling over 2π steradians (upper hemisphere), in order to produce a "literal" image or representation of the target. This effort includes the generation of a "Gold Standard" image that can be produced at X-band utilizing all available target data. This "Gold Standard" image of the backhoe will serve as a test bed for future more relevant military targets and their image development. The seedling team produced a public release data which was released at the 2004 SPIE conference, as well as a 3D "Gold Standard" backhoe image using a 3D image formation algorithm. This paper describes the full backhoe data set, the image formation algorithm, the visualization process and the resulting image.

  17. Tilted planes in 3D image analysis

    NASA Astrophysics Data System (ADS)

    Pargas, Roy P.; Staples, Nancy J.; Malloy, Brian F.; Cantrell, Ken; Chhatriwala, Murtuza

    1998-03-01

    Reliable 3D wholebody scanners which output digitized 3D images of a complete human body are now commercially available. This paper describes a software package, called 3DM, being developed by researchers at Clemson University and which manipulates and extracts measurements from such images. The focus of this paper is on tilted planes, a 3DM tool which allows a user to define a plane through a scanned image, tilt it in any direction, and effectively define three disjoint regions on the image: the points on the plane and the points on either side of the plane. With tilted planes, the user can accurately take measurements required in applications such as apparel manufacturing. The user can manually segment the body rather precisely. Tilted planes assist the user in analyzing the form of the body and classifying the body in terms of body shape. Finally, titled planes allow the user to eliminate extraneous and unwanted points often generated by a 3D scanner. This paper describes the user interface for tilted planes, the equations defining the plane as the user moves it through the scanned image, an overview of the algorithms, and the interaction of the tilted plane feature with other tools in 3DM.

  18. Improved Rotating Kernel Transformation Based Contourlet Domain Image Denoising Framework.

    PubMed

    Guo, Qing; Dong, Fangmin; Sun, Shuifa; Ren, Xuhong; Feng, Shiyu; Gao, Bruce Zhi

    A contourlet domain image denoising framework based on a novel Improved Rotating Kernel Transformation is proposed, where the difference of subbands in contourlet domain is taken into account. In detail: (1). A novel Improved Rotating Kernel Transformation (IRKT) is proposed to calculate the direction statistic of the image; The validity of the IRKT is verified by the corresponding extracted edge information comparing with the state-of-the-art edge detection algorithm. (2). The direction statistic represents the difference between subbands and is introduced to the threshold function based contourlet domain denoising approaches in the form of weights to get the novel framework. The proposed framework is utilized to improve the contourlet soft-thresholding (CTSoft) and contourlet bivariate-thresholding (CTB) algorithms. The denoising results on the conventional testing images and the Optical Coherence Tomography (OCT) medical images show that the proposed methods improve the existing contourlet based thresholding denoising algorithm, especially for the medical images.

  19. Evolutionary Fuzzy Block-Matching-Based Camera Raw Image Denoising.

    PubMed

    Yang, Chin-Chang; Guo, Shu-Mei; Tsai, Jason Sheng-Hong

    2016-10-03

    An evolutionary fuzzy block-matching-based image denoising algorithm is proposed to remove noise from a camera raw image. Recently, a variance stabilization transform is widely used to stabilize the noise variance, so that a Gaussian denoising algorithm can be used to remove the signal-dependent noise in camera sensors. However, in the stabilized domain, the existed denoising algorithm may blur too much detail. To provide a better estimate of the noise-free signal, a new block-matching approach is proposed to find similar blocks by the use of a type-2 fuzzy logic system (FLS). Then, these similar blocks are averaged with the weightings which are determined by the FLS. Finally, an efficient differential evolution is used to further improve the performance of the proposed denoising algorithm. The experimental results show that the proposed denoising algorithm effectively improves the performance of image denoising. Furthermore, the average performance of the proposed method is better than those of two state-of-the-art image denoising algorithms in subjective and objective measures.

  20. Feasibility of 3D harmonic contrast imaging.

    PubMed

    Voormolen, M M; Bouakaz, A; Krenning, B J; Lancée, C T; ten Cate, F J; de Jong, N

    2004-04-01

    Improved endocardial border delineation with the application of contrast agents should allow for less complex and faster tracing algorithms for left ventricular volume analysis. We developed a fast rotating phased array transducer for 3D imaging of the heart with harmonic capabilities making it suitable for contrast imaging. In this study the feasibility of 3D harmonic contrast imaging is evaluated in vitro. A commercially available tissue mimicking flow phantom was used in combination with Sonovue. Backscatter power spectra from a tissue and contrast region of interest were calculated from recorded radio frequency data. The spectra and the extracted contrast to tissue ratio from these spectra were used to optimize the excitation frequency, the pulse length and the receive filter settings of the transducer. Frequencies ranging from 1.66 to 2.35 MHz and pulse lengths of 1.5, 2 and 2.5 cycles were explored. An increase of more than 15 dB in the contrast to tissue ratio was found around the second harmonic compared with the fundamental level at an optimal excitation frequency of 1.74 MHz and a pulse length of 2.5 cycles. Using the optimal settings for 3D harmonic contrast recordings volume measurements of a left ventricular shaped agar phantom were performed. Without contrast the extracted volume data resulted in a volume error of 1.5%, with contrast an accuracy of 3.8% was achieved. The results show the feasibility of accurate volume measurements from 3D harmonic contrast images. Further investigations will include the clinical evaluation of the presented technique for improved assessment of the heart.

  1. 3D imaging system for biometric applications

    NASA Astrophysics Data System (ADS)

    Harding, Kevin; Abramovich, Gil; Paruchura, Vijay; Manickam, Swaminathan; Vemury, Arun

    2010-04-01

    There is a growing interest in the use of 3D data for many new applications beyond traditional metrology areas. In particular, using 3D data to obtain shape information of both people and objects for applications ranging from identification to game inputs does not require high degrees of calibration or resolutions in the tens of micron range, but does require a means to quickly and robustly collect data in the millimeter range. Systems using methods such as structured light or stereo have seen wide use in measurements, but due to the use of a triangulation angle, and thus the need for a separated second viewpoint, may not be practical for looking at a subject 10 meters away. Even when working close to a subject, such as capturing hands or fingers, the triangulation angle causes occlusions, shadows, and a physically large system that may get in the way. This paper will describe methods to collect medium resolution 3D data, plus highresolution 2D images, using a line of sight approach. The methods use no moving parts and as such are robust to movement (for portability), reliable, and potentially very fast at capturing 3D data. This paper will describe the optical methods considered, variations on these methods, and present experimental data obtained with the approach.

  2. Computed tomography perfusion imaging denoising using Gaussian process regression

    NASA Astrophysics Data System (ADS)

    Zhu, Fan; Carpenter, Trevor; Rodriguez Gonzalez, David; Atkinson, Malcolm; Wardlaw, Joanna

    2012-06-01

    Brain perfusion weighted images acquired using dynamic contrast studies have an important clinical role in acute stroke diagnosis and treatment decisions. However, computed tomography (CT) images suffer from low contrast-to-noise ratios (CNR) as a consequence of the limitation of the exposure to radiation of the patient. As a consequence, the developments of methods for improving the CNR are valuable. The majority of existing approaches for denoising CT images are optimized for 3D (spatial) information, including spatial decimation (spatially weighted mean filters) and techniques based on wavelet and curvelet transforms. However, perfusion imaging data is 4D as it also contains temporal information. Our approach using Gaussian process regression (GPR), which takes advantage of the temporal information, to reduce the noise level. Over the entire image, GPR gains a 99% CNR improvement over the raw images and also improves the quality of haemodynamic maps allowing a better identification of edges and detailed information. At the level of individual voxel, GPR provides a stable baseline, helps us to identify key parameters from tissue time-concentration curves and reduces the oscillations in the curve. GPR is superior to the comparable techniques used in this study.

  3. Sparsity based denoising of spectral domain optical coherence tomography images

    PubMed Central

    Fang, Leyuan; Li, Shutao; Nie, Qing; Izatt, Joseph A.; Toth, Cynthia A.; Farsiu, Sina

    2012-01-01

    In this paper, we make contact with the field of compressive sensing and present a development and generalization of tools and results for reconstructing irregularly sampled tomographic data. In particular, we focus on denoising Spectral-Domain Optical Coherence Tomography (SDOCT) volumetric data. We take advantage of customized scanning patterns, in which, a selected number of B-scans are imaged at higher signal-to-noise ratio (SNR). We learn a sparse representation dictionary for each of these high-SNR images, and utilize such dictionaries to denoise the low-SNR B-scans. We name this method multiscale sparsity based tomographic denoising (MSBTD). We show the qualitative and quantitative superiority of the MSBTD algorithm compared to popular denoising algorithms on images from normal and age-related macular degeneration eyes of a multi-center clinical trial. We have made the corresponding data set and software freely available online. PMID:22567586

  4. Image denoising based on wavelet cone of influence analysis

    NASA Astrophysics Data System (ADS)

    Pang, Wei; Li, Yufeng

    2009-11-01

    Donoho et al have proposed a method for denoising by thresholding based on wavelet transform, and indeed, the application of their method to image denoising has been extremely successful. But this method is based on the assumption that the type of noise is only additive Gaussian white noise, which is not efficient to impulse noise. In this paper, a new image denoising algorithm based on wavelet cone of influence (COI) analyzing is proposed, and which can effectively remove the impulse noise and preserve the image edges via undecimated discrete wavelet transform (UDWT). Furthermore, combining with the traditional wavelet thresholding denoising method, it can be also used to restrain more widely type of noise such as Gaussian noise, impulse noise, poisson noise and other mixed noise. Experiment results illustrate the advantages of this method.

  5. Pattern based 3D image Steganography

    NASA Astrophysics Data System (ADS)

    Thiyagarajan, P.; Natarajan, V.; Aghila, G.; Prasanna Venkatesan, V.; Anitha, R.

    2013-03-01

    This paper proposes a new high capacity Steganographic scheme using 3D geometric models. The novel algorithm re-triangulates a part of a triangle mesh and embeds the secret information into newly added position of triangle meshes. Up to nine bits of secret data can be embedded into vertices of a triangle without causing any changes in the visual quality and the geometric properties of the cover image. Experimental results show that the proposed algorithm is secure, with high capacity and low distortion rate. Our algorithm also resists against uniform affine transformations such as cropping, rotation and scaling. Also, the performance of the method is compared with other existing 3D Steganography algorithms. [Figure not available: see fulltext.

  6. Applications of discrete multiwavelet techniques to image denoising

    NASA Astrophysics Data System (ADS)

    Wang, Haihui; Peng, Jiaxiong; Wu, Wei; Ye, Bin

    2003-09-01

    In this paper, we present a new method by using 2-D discrete multiwavelet transform in image denoising. The developments in wavelet theory have given rise to the wavelet thresholding method, for extracting a signal from noisy data. The method of signal denoising via wavelet thresholding was popularized. Multiwavelets have recently been introduced and they offer simultaneous orthogonality, symmetry and short support. This property makes multiwavelets more suitable for various image processing applications, especially denoising. It is based on thresholding of multiwavelet coefficients arising from the standard scalar orthogonal wavelet transform. It takes into account the covariance structure of the transform. Denoising is images via thresholding of the multiwavelet coefficients result from preprocessing and the discrete multiwavelet transform can be carried out by threating the output in this paper. The form of the threshold is carefully formulated and is the key to the excellent results obtained in the extensive numerical simulations of image denoising. The performances of multiwavelets are compared with those of scalar wavelets. Simulations reveal that multiwavelet based image denoising schemes outperform wavelet based method both subjectively and objectively.

  7. 3D goes digital: from stereoscopy to modern 3D imaging techniques

    NASA Astrophysics Data System (ADS)

    Kerwien, N.

    2014-11-01

    In the 19th century, English physicist Charles Wheatstone discovered stereopsis, the basis for 3D perception. His construction of the first stereoscope established the foundation for stereoscopic 3D imaging. Since then, many optical instruments were influenced by these basic ideas. In recent decades, the advent of digital technologies revolutionized 3D imaging. Powerful readily available sensors and displays combined with efficient pre- or post-processing enable new methods for 3D imaging and applications. This paper draws an arc from basic concepts of 3D imaging to modern digital implementations, highlighting instructive examples from its 175 years of history.

  8. 3D seismic image processing for interpretation

    NASA Astrophysics Data System (ADS)

    Wu, Xinming

    Extracting fault, unconformity, and horizon surfaces from a seismic image is useful for interpretation of geologic structures and stratigraphic features. Although interpretation of these surfaces has been automated to some extent by others, significant manual effort is still required for extracting each type of these geologic surfaces. I propose methods to automatically extract all the fault, unconformity, and horizon surfaces from a 3D seismic image. To a large degree, these methods just involve image processing or array processing which is achieved by efficiently solving partial differential equations. For fault interpretation, I propose a linked data structure, which is simpler than triangle or quad meshes, to represent a fault surface. In this simple data structure, each sample of a fault corresponds to exactly one image sample. Using this linked data structure, I extract complete and intersecting fault surfaces without holes from 3D seismic images. I use the same structure in subsequent processing to estimate fault slip vectors. I further propose two methods, using precomputed fault surfaces and slips, to undo faulting in seismic images by simultaneously moving fault blocks and faults themselves. For unconformity interpretation, I first propose a new method to compute a unconformity likelihood image that highlights both the termination areas and the corresponding parallel unconformities and correlative conformities. I then extract unconformity surfaces from the likelihood image and use these surfaces as constraints to more accurately estimate seismic normal vectors that are discontinuous near the unconformities. Finally, I use the estimated normal vectors and use the unconformities as constraints to compute a flattened image, in which seismic reflectors are all flat and vertical gaps correspond to the unconformities. Horizon extraction is straightforward after computing a map of image flattening; we can first extract horizontal slices in the flattened space

  9. Denoising MR spectroscopic imaging data with low-rank approximations.

    PubMed

    Nguyen, Hien M; Peng, Xi; Do, Minh N; Liang, Zhi-Pei

    2013-01-01

    This paper addresses the denoising problem associated with magnetic resonance spectroscopic imaging (MRSI), where signal-to-noise ratio (SNR) has been a critical problem. A new scheme is proposed, which exploits two low-rank structures that exist in MRSI data, one due to partial separability and the other due to linear predictability. Denoising is performed by arranging the measured data in appropriate matrix forms (i.e., Casorati and Hankel) and applying low-rank approximations by singular value decomposition (SVD). The proposed method has been validated using simulated and experimental data, producing encouraging results. Specifically, the method can effectively denoise MRSI data in a wide range of SNR values while preserving spatial-spectral features. The method could prove useful for denoising MRSI data and other spatial-spectral and spatial-temporal imaging data as well.

  10. 3D GPR Imaging of Wooden Logs

    NASA Astrophysics Data System (ADS)

    Halabe, Udaya B.; Pyakurel, Sandeep

    2007-03-01

    There has been a lack of an effective NDE technique to locate internal defects within wooden logs. The few available elastic wave propagation based techniques are limited to predicting E values. Other techniques such as X-rays have not been very successful in detecting internal defects in logs. If defects such as embedded metals could be identified before the sawing process, the saw mills could significantly increase their production by reducing the probability of damage to the saw blade and the associated downtime and the repair cost. Also, if the internal defects such as knots and decayed areas could be identified in logs, the sawing blade can be oriented to exclude the defective portion and optimize the volume of high valued lumber that can be obtained from the logs. In this research, GPR has been successfully used to locate internal defects (knots, decays and embedded metals) within the logs. This paper discusses GPR imaging and mapping of the internal defects using both 2D and 3D interpretation methodology. Metal pieces were inserted in a log and the reflection patterns from these metals were interpreted from the radargrams acquired using 900 MHz antenna. Also, GPR was able to accurately identify the location of knots and decays. Scans from several orientations of the log were collected to generate 3D cylindrical volume. The actual location of the defects showed good correlation with the interpreted defects in the 3D volume. The time/depth slices from 3D cylindrical volume data were useful in understanding the extent of defects inside the log.

  11. An adaptive nonlocal means scheme for medical image denoising

    NASA Astrophysics Data System (ADS)

    Thaipanich, Tanaphol; Kuo, C.-C. Jay

    2010-03-01

    Medical images often consist of low-contrast objects corrupted by random noise arising in the image acquisition process. Thus, image denoising is one of the fundamental tasks required by medical imaging analysis. In this work, we investigate an adaptive denoising scheme based on the nonlocal (NL)-means algorithm for medical imaging applications. In contrast with the traditional NL-means algorithm, the proposed adaptive NL-means (ANL-means) denoising scheme has three unique features. First, it employs the singular value decomposition (SVD) method and the K-means clustering (K-means) technique for robust classification of blocks in noisy images. Second, the local window is adaptively adjusted to match the local property of a block. Finally, a rotated block matching algorithm is adopted for better similarity matching. Experimental results from both additive white Gaussian noise (AWGN) and Rician noise are given to demonstrate the superior performance of the proposed ANL denoising technique over various image denoising benchmarks in term of both PSNR and perceptual quality comparison.

  12. Dictionary Pair Learning on Grassmann Manifolds for Image Denoising.

    PubMed

    Zeng, Xianhua; Bian, Wei; Liu, Wei; Shen, Jialie; Tao, Dacheng

    2015-11-01

    Image denoising is a fundamental problem in computer vision and image processing that holds considerable practical importance for real-world applications. The traditional patch-based and sparse coding-driven image denoising methods convert 2D image patches into 1D vectors for further processing. Thus, these methods inevitably break down the inherent 2D geometric structure of natural images. To overcome this limitation pertaining to the previous image denoising methods, we propose a 2D image denoising model, namely, the dictionary pair learning (DPL) model, and we design a corresponding algorithm called the DPL on the Grassmann-manifold (DPLG) algorithm. The DPLG algorithm first learns an initial dictionary pair (i.e., the left and right dictionaries) by employing a subspace partition technique on the Grassmann manifold, wherein the refined dictionary pair is obtained through a sub-dictionary pair merging. The DPLG obtains a sparse representation by encoding each image patch only with the selected sub-dictionary pair. The non-zero elements of the sparse representation are further smoothed by the graph Laplacian operator to remove the noise. Consequently, the DPLG algorithm not only preserves the inherent 2D geometric structure of natural images but also performs manifold smoothing in the 2D sparse coding space. We demonstrate that the DPLG algorithm also improves the structural SIMilarity values of the perceptual visual quality for denoised images using the experimental evaluations on the benchmark images and Berkeley segmentation data sets. Moreover, the DPLG also produces the competitive peak signal-to-noise ratio values from popular image denoising algorithms.

  13. Remote sensing image denoising application by generalized morphological component analysis

    NASA Astrophysics Data System (ADS)

    Yu, Chong; Chen, Xiong

    2014-12-01

    In this paper, we introduced a remote sensing image denoising method based on generalized morphological component analysis (GMCA). This novel algorithm is the further extension of morphological component analysis (MCA) algorithm to the blind source separation framework. The iterative thresholding strategy adopted by GMCA algorithm firstly works on the most significant features in the image, and then progressively incorporates smaller features to finely tune the parameters of whole model. Mathematical analysis of the computational complexity of GMCA algorithm is provided. Several comparison experiments with state-of-the-art denoising algorithms are reported. In order to make quantitative assessment of algorithms in experiments, Peak Signal to Noise Ratio (PSNR) index and Structural Similarity (SSIM) index are calculated to assess the denoising effect from the gray-level fidelity aspect and the structure-level fidelity aspect, respectively. Quantitative analysis on experiment results, which is consistent with the visual effect illustrated by denoised images, has proven that the introduced GMCA algorithm possesses a marvelous remote sensing image denoising effectiveness and ability. It is even hard to distinguish the original noiseless image from the recovered image by adopting GMCA algorithm through visual effect.

  14. Image denoising via group Sparse representation over learned dictionary

    NASA Astrophysics Data System (ADS)

    Cheng, Pan; Deng, Chengzhi; Wang, Shengqian; Zhang, Chunfeng

    2013-10-01

    Images are one of vital ways to get information for us. However, in the practical application, images are often subject to a variety of noise, so that solving the problem of image denoising becomes particularly important. The K-SVD algorithm can improve the denoising effect by sparse coding atoms instead of the traditional method of sparse coding dictionary. In order to further improve the effect of denoising, we propose to extended the K-SVD algorithm via group sparse representation. The key point of this method is dividing the sparse coefficients into groups, so that adjusts the correlation among the elements by controlling the size of the groups. This new approach can improve the local constraints between adjacent atoms, thereby it is very important to increase the correlation between the atoms. The experimental results show that our method has a better effect on image recovery, which is efficient to prevent the block effect and can get smoother images.

  15. Pixon Based Image Denoising Scheme by Preserving Exact Edge Locations

    NASA Astrophysics Data System (ADS)

    Srikrishna, Atluri; Reddy, B. Eswara; Pompapathi, Manasani

    2016-09-01

    Denoising of an image is an essential step in many image processing applications. In any image de-noising algorithm, it is a major concern to keep interesting structures of the image like abrupt changes in image intensity values (edges). In this paper an efficient algorithm for image de-noising is proposed that obtains integrated and consecutive original image from noisy image using diffusion equations in pixon domain. The process mainly consists of two steps. In first step, the pixons for noisy image are obtained by using K-means clustering process and next step includes applying diffusion equations on the pixonal model of the image to obtain new intensity values for the restored image. The process has been applied on a variety of standard images and the objective fidelity has been compared with existing algorithms. The experimental results show that the proposed algorithm has a better performance by preserving edge details compared in terms of Figure of Merit and improved Peak-to-Signal-Noise-Ratio value. The proposed method brings out a denoising technique which preserves edge details.

  16. Blind source separation based x-ray image denoising from an image sequence.

    PubMed

    Yu, Chun-Yu; Li, Yan; Fei, Bin; Li, Wei-Liang

    2015-09-01

    Blind source separation (BSS) based x-ray image denoising from an image sequence is proposed. Without priori knowledge, the useful image signal can be separated from an x-ray image sequence, for original images are supposed as different combinations of stable image signal and random image noise. The BSS algorithms such as fixed-point independent component analysis and second-order statistics singular value decomposition are used and compared with multi-frame averaging which is a common algorithm for improving image's signal-to-noise ratio (SNR). Denoising performance is evaluated in SNR, standard deviation, entropy, and runtime. Analysis indicates that BSS is applicable to image denoising; the denoised image's quality will get better when more frames are included in an x-ray image sequence, but it will cost more time; there should be trade-off between denoising performance and runtime, which means that the number of frames included in an image sequence is enough.

  17. Image denoising based on wavelets and multifractals for singularity detection.

    PubMed

    Zhong, Junmei; Ning, Ruola

    2005-10-01

    This paper presents a very efficient algorithm for image denoising based on wavelets and multifractals for singularity detection. A challenge of image denoising is how to preserve the edges of an image when reducing noise. By modeling the intensity surface of a noisy image as statistically self-similar multifractal processes and taking advantage of the multiresolution analysis with wavelet transform to exploit the local statistical self-similarity at different scales, the pointwise singularity strength value characterizing the local singularity at each scale was calculated. By thresholding the singularity strength, wavelet coefficients at each scale were classified into two categories: the edge-related and regular wavelet coefficients and the irregular coefficients. The irregular coefficients were denoised using an approximate minimum mean-squared error (MMSE) estimation method, while the edge-related and regular wavelet coefficients were smoothed using the fuzzy weighted mean (FWM) filter aiming at preserving the edges and details when reducing noise. Furthermore, to make the FWM-based filtering more efficient for noise reduction at the lowest decomposition level, the MMSE-based filtering was performed as the first pass of denoising followed by performing the FWM-based filtering. Experimental results demonstrated that this algorithm could achieve both good visual quality and high PSNR for the denoised images.

  18. Photogrammetric 3D reconstruction using mobile imaging

    NASA Astrophysics Data System (ADS)

    Fritsch, Dieter; Syll, Miguel

    2015-03-01

    In our paper we demonstrate the development of an Android Application (AndroidSfM) for photogrammetric 3D reconstruction that works on smartphones and tablets likewise. The photos are taken with mobile devices, and can thereafter directly be calibrated using standard calibration algorithms of photogrammetry and computer vision, on that device. Due to still limited computing resources on mobile devices, a client-server handshake using Dropbox transfers the photos to the sever to run AndroidSfM for the pose estimation of all photos by Structure-from-Motion and, thereafter, uses the oriented bunch of photos for dense point cloud estimation by dense image matching algorithms. The result is transferred back to the mobile device for visualization and ad-hoc on-screen measurements.

  19. Study on Underwater Image Denoising Algorithm Based on Wavelet Transform

    NASA Astrophysics Data System (ADS)

    Jian, Sun; Wen, Wang

    2017-02-01

    This paper analyzes the application of MATLAB in underwater image processing, the transmission characteristics of the underwater laser light signal and the kinds of underwater noise has been described, the common noise suppression algorithm: Wiener filter, median filter, average filter algorithm is brought out. Then the advantages and disadvantages of each algorithm in image sharpness and edge protection areas have been compared. A hybrid filter algorithm based on wavelet transform has been proposed which can be used for Color Image Denoising. At last the PSNR and NMSE of each algorithm has been given out, which compares the ability to de-noising

  20. Image denoising with the dual-tree complex wavelet transform

    NASA Astrophysics Data System (ADS)

    Yaseen, Alauldeen S.; Pavlova, Olga N.; Pavlov, Alexey N.; Hramov, Alexander E.

    2016-04-01

    The purpose of this study is to compare image denoising techniques based on real and complex wavelet-transforms. Possibilities provided by the classical discrete wavelet transform (DWT) with hard and soft thresholding are considered, and influences of the wavelet basis and image resizing are discussed. The quality of image denoising for the standard 2-D DWT and the dual-tree complex wavelet transform (DT-CWT) is studied. It is shown that DT-CWT outperforms 2-D DWT at the appropriate selection of the threshold level.

  1. Image denoising via adaptive eigenvectors of graph Laplacian

    NASA Astrophysics Data System (ADS)

    Chen, Ying; Tang, Yibin; Xu, Ning; Zhou, Lin; Zhao, Li

    2016-07-01

    An image denoising method via adaptive eigenvectors of graph Laplacian (EGL) is proposed. Unlike the trivial parameter setting of the used eigenvectors in the traditional EGL method, in our method, the eigenvectors are adaptively selected in the whole denoising procedure. In detail, a rough image is first built with the eigenvectors from the noisy image, where the eigenvectors are selected by using the deviation estimation of the clean image. Subsequently, a guided image is effectively restored with a weighted average of the noisy and rough images. In this operation, the average coefficient is adaptively obtained to set the deviation of the guided image to approximately that of the clean image. Finally, the denoised image is achieved by a group-sparse model with the pattern from the guided image, where the eigenvectors are chosen in the error control of the noise deviation. Moreover, a modified group orthogonal matching pursuit algorithm is developed to efficiently solve the above group sparse model. The experiments show that our method not only improves the practicality of the EGL methods with the dependence reduction of the parameter setting, but also can outperform some well-developed denoising methods, especially for noise with large deviations.

  2. Denoising Magnetic Resonance Images Using Collaborative Non-Local Means.

    PubMed

    Chen, Geng; Zhang, Pei; Wu, Yafeng; Shen, Dinggang; Yap, Pew-Thian

    2016-02-12

    Noise artifacts in magnetic resonance (MR) images increase the complexity of image processing workflows and decrease the reliability of inferences drawn from the images. It is thus often desirable to remove such artifacts beforehand for more robust and effective quantitative analysis. It is important to preserve the integrity of relevant image information while removing noise in MR images. A variety of approaches have been developed for this purpose, and the non-local means (NLM) filter has been shown to be able to achieve state-of-the-art denoising performance. For effective denoising, NLM relies heavily on the existence of repeating structural patterns, which however might not always be present within a single image. This is especially true when one considers the fact that the human brain is complex and contains a lot of unique structures. In this paper we propose to leverage the repeating structures from multiple images to collaboratively denoise an image. The underlying assumption is that it is more likely to find repeating structures from multiple scans than from a single scan. Specifically, to denoise a target image, multiple images, which may be acquired from different subjects, are spatially aligned to the target image, and an NLM-like block matching is performed on these aligned images with the target image as the reference. This will significantly increase the number of matching structures and thus boost the denoising performance. Experiments on both synthetic and real data show that the proposed approach, collaborative non-local means (CNLM), outperforms the classic NLM and yields results with markedly improved structural details.

  3. Ames Lab 101: Real-Time 3D Imaging

    SciTech Connect

    Zhang, Song

    2010-01-01

    Ames Laboratory scientist Song Zhang explains his real-time 3-D imaging technology. The technique can be used to create high-resolution, real-time, precise, 3-D images for use in healthcare, security, and entertainment applications.

  4. Ames Lab 101: Real-Time 3D Imaging

    ScienceCinema

    Zhang, Song

    2016-07-12

    Ames Laboratory scientist Song Zhang explains his real-time 3-D imaging technology. The technique can be used to create high-resolution, real-time, precise, 3-D images for use in healthcare, security, and entertainment applications.

  5. Region-based image denoising through wavelet and fast discrete curvelet transform

    NASA Astrophysics Data System (ADS)

    Gu, Yanfeng; Guo, Yan; Liu, Xing; Zhang, Ye

    2008-10-01

    Image denoising always is one of important research topics in the image processing field. In this paper, fast discrete curvelet transform (FDCT) and undecimated wavelet transform (UDWT) are proposed for image denoising. A noisy image is first denoised by FDCT and UDWT separately. The whole image space is then divided into edge region and non-edge regions. After that, wavelet transform is performed on the images denoised by FDCT and UDWT respectively. Finally, the resultant image is fused through using both of edge region wavelet cofficients of the image denoised by FDCT and non-edge region wavelet cofficients of the image denoised by UDWT. The proposed method is validated through numerical experiments conducted on standard test images. The experimental results show that the proposed algorithm outperforms wavelet-based and curvelet-based image denoising methods and preserve linear features well.

  6. Single-image noise level estimation for blind denoising.

    PubMed

    Liu, Xinhao; Tanaka, Masayuki; Okutomi, Masatoshi

    2013-12-01

    Noise level is an important parameter to many image processing applications. For example, the performance of an image denoising algorithm can be much degraded due to the poor noise level estimation. Most existing denoising algorithms simply assume the noise level is known that largely prevents them from practical use. Moreover, even with the given true noise level, these denoising algorithms still cannot achieve the best performance, especially for scenes with rich texture. In this paper, we propose a patch-based noise level estimation algorithm and suggest that the noise level parameter should be tuned according to the scene complexity. Our approach includes the process of selecting low-rank patches without high frequency components from a single noisy image. The selection is based on the gradients of the patches and their statistics. Then, the noise level is estimated from the selected patches using principal component analysis. Because the true noise level does not always provide the best performance for nonblind denoising algorithms, we further tune the noise level parameter for nonblind denoising. Experiments demonstrate that both the accuracy and stability are superior to the state of the art noise level estimation algorithm for various scenes and noise levels.

  7. Blind Image Denoising via Dependent Dirichlet Process Tree.

    PubMed

    Zhu, Fengyuan; Chen, Guangyong; Hao, Jianye; Heng, Pheng-Ann

    2016-08-31

    Most existing image denoising approaches assumed the noise to be homogeneous white Gaussian distributed with known intensity. However, in real noisy images, the noise models are usually unknown beforehand and can be much more complex. This paper addresses this problem and proposes a novel blind image denoising algorithm to recover the clean image from noisy one with the unknown noise model. To model the empirical noise of an image, our method introduces the mixture of Gaussian distribution, which is flexible enough to approximate different continuous distributions. The problem of blind image denoising is reformulated as a learning problem. The procedure is to first build a two-layer structural model for noisy patches and consider the clean ones as latent variable. To control the complexity of the noisy patch model, this work proposes a novel Bayesian nonparametric prior called "Dependent Dirichlet Process Tree" to build the model. Then, this study derives a variational inference algorithm to estimate model parameters and recover clean patches. We apply our method on synthesis and real noisy images with different noise models. Comparing with previous approaches, ours achieves better performance. The experimental results indicate the efficiency of the proposed algorithm to cope with practical image denoising tasks.

  8. Statistical Methods for Image Registration and Denoising

    DTIC Science & Technology

    2008-06-19

    21 2.5.4 Nonlocal Means . . . . . . . . . . . . . . . . . 22 2.5.5 Patch -Based Denoising with Optimal Spatial Adap- tation...24 2.5.6 Other Patch -Based Methods . . . . . . . . . . 25 2.6 Chapter Summary...the nonlocal means [9], and an optimal patch -based algorithm [31]. These algorithms all include some measure of pixel similarity that allows the

  9. [3D display of sequential 2D medical images].

    PubMed

    Lu, Yisong; Chen, Yazhu

    2003-12-01

    A detailed review is given in this paper on various current 3D display methods for sequential 2D medical images and the new development in 3D medical image display. True 3D display, surface rendering, volume rendering, 3D texture mapping and distributed collaborative rendering are discussed in depth. For two kinds of medical applications: Real-time navigation system and high-fidelity diagnosis in computer aided surgery, different 3D display methods are presented.

  10. Progress in 3D imaging and display by integral imaging

    NASA Astrophysics Data System (ADS)

    Martinez-Cuenca, R.; Saavedra, G.; Martinez-Corral, M.; Pons, A.; Javidi, B.

    2009-05-01

    Three-dimensionality is currently considered an important added value in imaging devices, and therefore the search for an optimum 3D imaging and display technique is a hot topic that is attracting important research efforts. As main value, 3D monitors should provide the observers with different perspectives of a 3D scene by simply varying the head position. Three-dimensional imaging techniques have the potential to establish a future mass-market in the fields of entertainment and communications. Integral imaging (InI), which can capture true 3D color images, has been seen as the right technology to 3D viewing to audiences of more than one person. Due to the advanced degree of development, InI technology could be ready for commercialization in the coming years. This development is the result of a strong research effort performed along the past few years by many groups. Since Integral Imaging is still an emerging technology, the first aim of the "3D Imaging and Display Laboratory" at the University of Valencia, has been the realization of a thorough study of the principles that govern its operation. Is remarkable that some of these principles have been recognized and characterized by our group. Other contributions of our research have been addressed to overcome some of the classical limitations of InI systems, like the limited depth of field (in pickup and in display), the poor axial and lateral resolution, the pseudoscopic-to-orthoscopic conversion, the production of 3D images with continuous relief, or the limited range of viewing angles of InI monitors.

  11. A New Method for Nonlocal Means Image Denoising Using Multiple Images.

    PubMed

    Wang, Xingzheng; Wang, Haoqian; Yang, Jiangfeng; Zhang, Yongbing

    2016-01-01

    The basic principle of nonlocal means is to denoise a pixel using the weighted average of the neighbourhood pixels, while the weight is decided by the similarity of these pixels. The key issue of the nonlocal means method is how to select similar patches and design the weight of them. There are two main contributions of this paper: The first contribution is that we use two images to denoise the pixel. These two noised images are with the same noise deviation. Instead of using only one image, we calculate the weight from two noised images. After the first denoising process, we get a pre-denoised image and a residual image. The second contribution is combining the nonlocal property between residual image and pre-denoised image. The improved nonlocal means method pays more attention on the similarity than the original one, which turns out to be very effective in eliminating gaussian noise. Experimental results with simulated data are provided.

  12. A New Method for Nonlocal Means Image Denoising Using Multiple Images

    PubMed Central

    Wang, Xingzheng; Wang, Haoqian; Yang, Jiangfeng; Zhang, Yongbing

    2016-01-01

    The basic principle of nonlocal means is to denoise a pixel using the weighted average of the neighbourhood pixels, while the weight is decided by the similarity of these pixels. The key issue of the nonlocal means method is how to select similar patches and design the weight of them. There are two main contributions of this paper: The first contribution is that we use two images to denoise the pixel. These two noised images are with the same noise deviation. Instead of using only one image, we calculate the weight from two noised images. After the first denoising process, we get a pre-denoised image and a residual image. The second contribution is combining the nonlocal property between residual image and pre-denoised image. The improved nonlocal means method pays more attention on the similarity than the original one, which turns out to be very effective in eliminating gaussian noise. Experimental results with simulated data are provided. PMID:27459293

  13. Local Sparse Structure Denoising for Low-Light-Level Image.

    PubMed

    Han, Jing; Yue, Jiang; Zhang, Yi; Bai, Lianfa

    2015-12-01

    Sparse and redundant representations perform well in image denoising. However, sparsity-based methods fail to denoise low-light-level (LLL) images because of heavy and complex noise. They consider sparsity on image patches independently and tend to lose the texture structures. To suppress noises and maintain textures simultaneously, it is necessary to embed noise invariant features into the sparse decomposition process. We, therefore, used a local structure preserving sparse coding (LSPSc) formulation to explore the local sparse structures (both the sparsity and local structure) in image. It was found that, with the introduction of spatial local structure constraint into the general sparse coding algorithm, LSPSc could improve the robustness of sparse representation for patches in serious noise. We further used a kernel LSPSc (K-LSPSc) formulation, which extends LSPSc into the kernel space to weaken the influence of linear structure constraint in nonlinear data. Based on the robust LSPSc and K-LSPSc algorithms, we constructed a local sparse structure denoising (LSSD) model for LLL images, which was demonstrated to give high performance in the natural LLL images denoising, indicating that both the LSPSc- and K-LSPSc-based LSSD models have the stable property of noise inhibition and texture details preservation.

  14. A fast non-local image denoising algorithm

    NASA Astrophysics Data System (ADS)

    Dauwe, A.; Goossens, B.; Luong, H. Q.; Philips, W.

    2008-02-01

    In this paper we propose several improvements to the original non-local means algorithm introduced by Buades et al. which obtains state-of-the-art denoising results. The strength of this algorithm is to exploit the repetitive character of the image in order to denoise the image unlike conventional denoising algorithms, which typically operate in a local neighbourhood. Due to the enormous amount of weight computations, the original algorithm has a high computational cost. An improvement of image quality towards the original algorithm is to ignore the contributions from dissimilar windows. Even though their weights are very small at first sight, the new estimated pixel value can be severely biased due to the many small contributions. This bad influence of dissimilar windows can be eliminated by setting their corresponding weights to zero. Using the preclassification based on the first three statistical moments, only contributions from similar neighborhoods are computed. To decide whether a window is similar or dissimilar, we will derive thresholds for images corrupted with additive white Gaussian noise. Our accelerated approach is further optimized by taking advantage of the symmetry in the weights, which roughly halves the computation time, and by using a lookup table to speed up the weight computations. Compared to the original algorithm, our proposed method produces images with increased PSNR and better visual performance in less computation time. Our proposed method even outperforms state-of-the-art wavelet denoising techniques in both visual quality and PSNR values for images containing a lot of repetitive structures such as textures: the denoised images are much sharper and contain less artifacts. The proposed optimizations can also be applied in other image processing tasks which employ the concept of repetitive structures such as intra-frame super-resolution or detection of digital image forgery.

  15. Infrastructure for 3D Imaging Test Bed

    DTIC Science & Technology

    2007-05-11

    analysis. (c.) Real time detection & analysis of human gait: using a video camera we capture walking human silhouette for pattern modeling and gait ... analysis . Fig. 5 shows the scanning result result that is fed into a Geo-magic software tool for 3D meshing. Fig. 5: 3D scanning result In

  16. A hybrid spatial-spectral denoising method for infrared hyperspectral images using 2DPCA

    NASA Astrophysics Data System (ADS)

    Huang, Jun; Ma, Yong; Mei, Xiaoguang; Fan, Fan

    2016-11-01

    The traditional noise reduction methods for 3-D infrared hyperspectral images typically operate independently in either the spatial or spectral domain, and such methods overlook the relationship between the two domains. To address this issue, we propose a hybrid spatial-spectral method in this paper to link both domains. First, principal component analysis and bivariate wavelet shrinkage are performed in the 2-D spatial domain. Second, 2-D principal component analysis transformation is conducted in the 1-D spectral domain to separate the basic components from detail ones. The energy distribution of noise is unaffected by orthogonal transformation; therefore, the signal-to-noise ratio of each component is used as a criterion to determine whether a component should be protected from over-denoising or denoised with certain 1-D denoising methods. This study implements the 1-D wavelet shrinking threshold method based on Stein's unbiased risk estimator, and the quantitative results on publicly available datasets demonstrate that our method can improve denoising performance more effectively than other state-of-the-art methods can.

  17. Dictionary-based image denoising for dual energy computed tomography

    NASA Astrophysics Data System (ADS)

    Mechlem, Korbinian; Allner, Sebastian; Mei, Kai; Pfeiffer, Franz; Noël, Peter B.

    2016-03-01

    Compared to conventional computed tomography (CT), dual energy CT allows for improved material decomposition by conducting measurements at two distinct energy spectra. Since radiation exposure is a major concern in clinical CT, there is a need for tools to reduce the noise level in images while preserving diagnostic information. One way to achieve this goal is the application of image-based denoising algorithms after an analytical reconstruction has been performed. We have developed a modified dictionary denoising algorithm for dual energy CT aimed at exploiting the high spatial correlation between between images obtained from different energy spectra. Both the low-and high energy image are partitioned into small patches which are subsequently normalized. Combined patches with improved signal-to-noise ratio are formed by a weighted addition of corresponding normalized patches from both images. Assuming that corresponding low-and high energy image patches are related by a linear transformation, the signal in both patches is added coherently while noise is neglected. Conventional dictionary denoising is then performed on the combined patches. Compared to conventional dictionary denoising and bilateral filtering, our algorithm achieved superior performance in terms of qualitative and quantitative image quality measures. We demonstrate, in simulation studies, that this approach can produce 2d-histograms of the high- and low-energy reconstruction which are characterized by significantly improved material features and separation. Moreover, in comparison to other approaches that attempt denoising without simultaneously using both energy signals, superior similarity to the ground truth can be found with our proposed algorithm.

  18. Image denoising with dominant sets by a coalitional game approach.

    PubMed

    Hsiao, Pei-Chi; Chang, Long-Wen

    2013-02-01

    Dominant sets are a new graph partition method for pairwise data clustering proposed by Pavan and Pelillo. We address the problem of dominant sets with a coalitional game model, in which each data point is treated as a player and similar data points are encouraged to group together for cooperation. We propose betrayal and hermit rules to describe the cooperative behaviors among the players. After applying the betrayal and hermit rules, an optimal and stable graph partition emerges, and all the players in the partition will not change their groups. For computational feasibility, we design an approximate algorithm for finding a dominant set of mutually similar players and then apply the algorithm to an application such as image denoising. In image denoising, every pixel is treated as a player who seeks similar partners according to its patch appearance in its local neighborhood. By averaging the noisy effects with the similar pixels in the dominant sets, we improve nonlocal means image denoising to restore the intrinsic structure of the original images and achieve competitive denoising results with the state-of-the-art methods in visual and quantitative qualities.

  19. Glasses-free 3D viewing systems for medical imaging

    NASA Astrophysics Data System (ADS)

    Magalhães, Daniel S. F.; Serra, Rolando L.; Vannucci, André L.; Moreno, Alfredo B.; Li, Li M.

    2012-04-01

    In this work we show two different glasses-free 3D viewing systems for medical imaging: a stereoscopic system that employs a vertically dispersive holographic screen (VDHS) and a multi-autostereoscopic system, both used to produce 3D MRI/CT images. We describe how to obtain a VDHS in holographic plates optimized for this application, with field of view of 7 cm to each eye and focal length of 25 cm, showing images done with the system. We also describe a multi-autostereoscopic system, presenting how it can generate 3D medical imaging from viewpoints of a MRI or CT image, showing results of a 3D angioresonance image.

  20. 3D ultrasound imaging for prosthesis fabrication and diagnostic imaging

    SciTech Connect

    Morimoto, A.K.; Bow, W.J.; Strong, D.S.

    1995-06-01

    The fabrication of a prosthetic socket for a below-the-knee amputee requires knowledge of the underlying bone structure in order to provide pressure relief for sensitive areas and support for load bearing areas. The goal is to enable the residual limb to bear pressure with greater ease and utility. Conventional methods of prosthesis fabrication are based on limited knowledge about the patient`s underlying bone structure. A 3D ultrasound imaging system was developed at Sandia National Laboratories. The imaging system provides information about the location of the bones in the residual limb along with the shape of the skin surface. Computer assisted design (CAD) software can use this data to design prosthetic sockets for amputees. Ultrasound was selected as the imaging modality. A computer model was developed to analyze the effect of the various scanning parameters and to assist in the design of the overall system. The 3D ultrasound imaging system combines off-the-shelf technology for image capturing, custom hardware, and control and image processing software to generate two types of image data -- volumetric and planar. Both volumetric and planar images reveal definition of skin and bone geometry with planar images providing details on muscle fascial planes, muscle/fat interfaces, and blood vessel definition. The 3D ultrasound imaging system was tested on 9 unilateral below-the- knee amputees. Image data was acquired from both the sound limb and the residual limb. The imaging system was operated in both volumetric and planar formats. An x-ray CT (Computed Tomography) scan was performed on each amputee for comparison. Results of the test indicate beneficial use of ultrasound to generate databases for fabrication of prostheses at a lower cost and with better initial fit as compared to manually fabricated prostheses.

  1. Research of range-gated 3D imaging technology

    NASA Astrophysics Data System (ADS)

    Yang, Haitao; Zhao, Hongli; Youchen, Fan

    2016-10-01

    Laser image data-based target recognition technology is one of the key technologies of laser active imaging systems. This paper discussed the status quo of 3-D imaging development at home and abroad, analyzed the current technological bottlenecks, and built a prototype of range-gated systems to obtain a set of range-gated slice images, and then constructed the 3-D images of the target by binary method and centroid method, respectively, and by constructing different numbers of slice images explored the relationship between the number of images and the reconstruction accuracy in the 3-D image reconstruction process. The experiment analyzed the impact of two algorithms, binary method and centroid method, on the results of 3-D image reconstruction. In the binary method, a comparative analysis was made on the impact of different threshold values on the results of reconstruction, where 0.1, 0.2, 0.3 and adaptive threshold values were selected for 3-D reconstruction of the slice images. In the centroid method, 15, 10, 6, 3, and 2 images were respectively used to realize 3-D reconstruction. Experimental results showed that with the same number of slice images, the accuracy of centroid method was higher than the binary algorithm, and the binary algorithm had a large dependence on the selection of threshold; with the number of slice images dwindling, the accuracy of images reconstructed by centroid method continued to reduce, and at least three slice images were required in order to obtain one 3-D image.

  2. Image Pretreatment Tools I: Algorithms for Map Denoising and Background Subtraction Methods.

    PubMed

    Cannistraci, Carlo Vittorio; Alessio, Massimo

    2016-01-01

    One of the critical steps in two-dimensional electrophoresis (2-DE) image pre-processing is the denoising, that might aggressively affect either spot detection or pixel-based methods. The Median Modified Wiener Filter (MMWF), a new nonlinear adaptive spatial filter, resulted to be a good denoising approach to use in practice with 2-DE. MMWF is suitable for global denoising, and contemporary for the removal of spikes and Gaussian noise, being its best setting invariant on the type of noise. The second critical step rises because of the fact that 2-DE gel images may contain high levels of background, generated by the laboratory experimental procedures, that must be subtracted for accurate measurements of the proteomic optical density signals. Here we discuss an efficient mathematical method for background estimation, that is suitable to work even before the 2-DE image spot detection, and it is based on the 3D mathematical morphology (3DMM) theory.

  3. 3D Imaging by Mass Spectrometry: A New Frontier

    PubMed Central

    Seeley, Erin H.; Caprioli, Richard M.

    2012-01-01

    Summary Imaging mass spectrometry can generate three-dimensional volumes showing molecular distributions in an entire organ or animal through registration and stacking of serial tissue sections. Here we review the current state of 3D imaging mass spectrometry as well as provide insights and perspectives on the process of generating 3D mass spectral data along with a discussion of the process necessary to generate a 3D image volume. PMID:22276611

  4. Reconstruction-based 3D/2D image registration.

    PubMed

    Tomazevic, Dejan; Likar, Bostjan; Pernus, Franjo

    2005-01-01

    In this paper we present a novel 3D/2D registration method, where first, a 3D image is reconstructed from a few 2D X-ray images and next, the preoperative 3D image is brought into the best possible spatial correspondence with the reconstructed image by optimizing a similarity measure. Because the quality of the reconstructed image is generally low, we introduce a novel asymmetric mutual information similarity measure, which is able to cope with low image quality as well as with different imaging modalities. The novel 3D/2D registration method has been evaluated using standardized evaluation methodology and publicly available 3D CT, 3DRX, and MR and 2D X-ray images of two spine phantoms, for which gold standard registrations were known. In terms of robustness, reliability and capture range the proposed method outperformed the gradient-based method and the method based on digitally reconstructed radiographs (DRRs).

  5. 2D Orthogonal Locality Preserving Projection for Image Denoising.

    PubMed

    Shikkenawis, Gitam; Mitra, Suman K

    2016-01-01

    Sparse representations using transform-domain techniques are widely used for better interpretation of the raw data. Orthogonal locality preserving projection (OLPP) is a linear technique that tries to preserve local structure of data in the transform domain as well. Vectorized nature of OLPP requires high-dimensional data to be converted to vector format, hence may lose spatial neighborhood information of raw data. On the other hand, processing 2D data directly, not only preserves spatial information, but also improves the computational efficiency considerably. The 2D OLPP is expected to learn the transformation from 2D data itself. This paper derives mathematical foundation for 2D OLPP. The proposed technique is used for image denoising task. Recent state-of-the-art approaches for image denoising work on two major hypotheses, i.e., non-local self-similarity and sparse linear approximations of the data. Locality preserving nature of the proposed approach automatically takes care of self-similarity present in the image while inferring sparse basis. A global basis is adequate for the entire image. The proposed approach outperforms several state-of-the-art image denoising approaches for gray-scale, color, and texture images.

  6. 3D Imaging with Holographic Tomography

    NASA Astrophysics Data System (ADS)

    Sheppard, Colin J. R.; Kou, Shan Shan

    2010-04-01

    There are two main types of tomography that enable the 3D internal structures of objects to be reconstructed from scattered data. The commonly known computerized tomography (CT) give good results in the x-ray wavelength range where the filtered back-projection theorem and Radon transform can be used. These techniques rely on the Fourier projection-slice theorem where rays are considered to propagate straight through the object. Another type of tomography called `diffraction tomography' applies in applications in optics and acoustics where diffraction and scattering effects must be taken into account. The latter proves to be a more difficult problem, as light no longer travels straight through the sample. Holographic tomography is a popular way of performing diffraction tomography and there has been active experimental research on reconstructing complex refractive index data using this approach recently. However, there are two distinct ways of doing tomography: either by rotation of the object or by rotation of the illumination while fixing the detector. The difference between these two setups is intuitive but needs to be quantified. From Fourier optics and information transformation point of view, we use 3D transfer function analysis to quantitatively describe how spatial frequencies of the object are mapped to the Fourier domain. We first employ a paraxial treatment by calculating the Fourier transform of the defocused OTF. The shape of the calculated 3D CTF for tomography, by scanning the illumination in one direction only, takes on a form that we might call a 'peanut,' compared to the case of object rotation, where a diablo is formed, the peanut exhibiting significant differences and non-isotropy. In particular, there is a line singularity along one transverse direction. Under high numerical aperture conditions, the paraxial treatment is not accurate, and so we make use of 3D analytical geometry to calculate the behaviour in the non-paraxial case. This time, we

  7. Diffusion Weighted Image Denoising Using Overcomplete Local PCA

    PubMed Central

    Manjón, José V.; Coupé, Pierrick; Concha, Luis; Buades, Antonio; Collins, D. Louis; Robles, Montserrat

    2013-01-01

    Diffusion Weighted Images (DWI) normally shows a low Signal to Noise Ratio (SNR) due to the presence of noise from the measurement process that complicates and biases the estimation of quantitative diffusion parameters. In this paper, a new denoising methodology is proposed that takes into consideration the multicomponent nature of multi-directional DWI datasets such as those employed in diffusion imaging. This new filter reduces random noise in multicomponent DWI by locally shrinking less significant Principal Components using an overcomplete approach. The proposed method is compared with state-of-the-art methods using synthetic and real clinical MR images, showing improved performance in terms of denoising quality and estimation of diffusion parameters. PMID:24019889

  8. Optical 3D imaging and visualization of concealed objects

    NASA Astrophysics Data System (ADS)

    Berginc, G.; Bellet, J.-B.; Berechet, I.; Berechet, S.

    2016-09-01

    This paper gives new insights on optical 3D imagery. In this paper we explore the advantages of laser imagery to form a three-dimensional image of the scene. 3D laser imaging can be used for three-dimensional medical imaging and surveillance because of ability to identify tumors or concealed objects. We consider the problem of 3D reconstruction based upon 2D angle-dependent laser images. The objective of this new 3D laser imaging is to provide users a complete 3D reconstruction of objects from available 2D data limited in number. The 2D laser data used in this paper come from simulations that are based on the calculation of the laser interactions with the different meshed objects of the scene of interest or from experimental 2D laser images. We show that combining the Radom transform on 2D laser images with the Maximum Intensity Projection can generate 3D views of the considered scene from which we can extract the 3D concealed object in real time. With different original numerical or experimental examples, we investigate the effects of the input contrasts. We show the robustness and the stability of the method. We have developed a new patented method of 3D laser imaging based on three-dimensional reflective tomographic reconstruction algorithms and an associated visualization method. In this paper we present the global 3D reconstruction and visualization procedures.

  9. Two-direction nonlocal model for image denoising.

    PubMed

    Zhang, Xuande; Feng, Xiangchu; Wang, Weiwei

    2013-01-01

    Similarities inherent in natural images have been widely exploited for image denoising and other applications. In fact, if a cluster of similar image patches is rearranged into a matrix, similarities exist both between columns and rows. Using the similarities, we present a two-directional nonlocal (TDNL) variational model for image denoising. The solution of our model consists of three components: one component is a scaled version of the original observed image and the other two components are obtained by utilizing the similarities. Specifically, by using the similarity between columns, we get a nonlocal-means-like estimation of the patch with consideration to all similar patches, while the weights are not the pairwise similarities but a set of clusterwise coefficients. Moreover, by using the similarity between rows, we also get nonlocal-autoregression-like estimations for the center pixels of the similar patches. The TDNL model leads to an alternative minimization algorithm. Experiments indicate that the model can perform on par with or better than the state-of-the-art denoising methods.

  10. Oriented wavelet transform for image compression and denoising.

    PubMed

    Chappelier, Vivien; Guillemot, Christine

    2006-10-01

    In this paper, we introduce a new transform for image processing, based on wavelets and the lifting paradigm. The lifting steps of a unidimensional wavelet are applied along a local orientation defined on a quincunx sampling grid. To maximize energy compaction, the orientation minimizing the prediction error is chosen adaptively. A fine-grained multiscale analysis is provided by iterating the decomposition on the low-frequency band. In the context of image compression, the multiresolution orientation map is coded using a quad tree. The rate allocation between the orientation map and wavelet coefficients is jointly optimized in a rate-distortion sense. For image denoising, a Markov model is used to extract the orientations from the noisy image. As long as the map is sufficiently homogeneous, interesting properties of the original wavelet are preserved such as regularity and orthogonality. Perfect reconstruction is ensured by the reversibility of the lifting scheme. The mutual information between the wavelet coefficients is studied and compared to the one observed with a separable wavelet transform. The rate-distortion performance of this new transform is evaluated for image coding using state-of-the-art subband coders. Its performance in a denoising application is also assessed against the performance obtained with other transforms or denoising methods.

  11. Light field display and 3D image reconstruction

    NASA Astrophysics Data System (ADS)

    Iwane, Toru

    2016-06-01

    Light field optics and its applications become rather popular in these days. With light field optics or light field thesis, real 3D space can be described in 2D plane as 4D data, which we call as light field data. This process can be divided in two procedures. First, real3D scene is optically reduced with imaging lens. Second, this optically reduced 3D image is encoded into light field data. In later procedure we can say that 3D information is encoded onto a plane as 2D data by lens array plate. This transformation is reversible and acquired light field data can be decoded again into 3D image with the arrayed lens plate. "Refocusing" (focusing image on your favorite point after taking a picture), light-field camera's most popular function, is some kind of sectioning process from encoded 3D data (light field data) to 2D image. In this paper at first I show our actual light field camera and our 3D display using acquired and computer-simulated light field data, on which real 3D image is reconstructed. In second I explain our data processing method whose arithmetic operation is performed not in Fourier domain but in real domain. Then our 3D display system is characterized by a few features; reconstructed image is of finer resolutions than density of arrayed lenses and it is not necessary to adjust lens array plate to flat display on which light field data is displayed.

  12. 3D Imaging with Structured Illumination for Advanced Security Applications

    SciTech Connect

    Birch, Gabriel Carisle; Dagel, Amber Lynn; Kast, Brian A.; Smith, Collin S.

    2015-09-01

    Three-dimensional (3D) information in a physical security system is a highly useful dis- criminator. The two-dimensional data from an imaging systems fails to provide target dis- tance and three-dimensional motion vector, which can be used to reduce nuisance alarm rates and increase system effectiveness. However, 3D imaging devices designed primarily for use in physical security systems are uncommon. This report discusses an architecture favorable to physical security systems; an inexpensive snapshot 3D imaging system utilizing a simple illumination system. The method of acquiring 3D data, tests to understand illumination de- sign, and software modifications possible to maximize information gathering capability are discussed.

  13. Optimally stabilized PET image denoising using trilateral filtering.

    PubMed

    Mansoor, Awais; Bagci, Ulas; Mollura, Daniel J

    2014-01-01

    Low-resolution and signal-dependent noise distribution in positron emission tomography (PET) images makes denoising process an inevitable step prior to qualitative and quantitative image analysis tasks. Conventional PET denoising methods either over-smooth small-sized structures due to resolution limitation or make incorrect assumptions about the noise characteristics. Therefore, clinically important quantitative information may be corrupted. To address these challenges, we introduced a novel approach to remove signal-dependent noise in the PET images where the noise distribution was considered as Poisson-Gaussian mixed. Meanwhile, the generalized Anscombe's transformation (GAT) was used to stabilize varying nature of the PET noise. Other than noise stabilization, it is also desirable for the noise removal filter to preserve the boundaries of the structures while smoothing the noisy regions. Indeed, it is important to avoid significant loss of quantitative information such as standard uptake value (SUV)-based metrics as well as metabolic lesion volume. To satisfy all these properties, we extended bilateral filtering method into trilateral filtering through multiscaling and optimal Gaussianization process. The proposed method was tested on more than 50 PET-CT images from various patients having different cancers and achieved the superior performance compared to the widely used denoising techniques in the literature.

  14. Comparison of de-noising techniques for FIRST images

    SciTech Connect

    Fodor, I K; Kamath, C

    2001-01-22

    Data obtained through scientific observations are often contaminated by noise and artifacts from various sources. As a result, a first step in mining these data is to isolate the signal of interest by minimizing the effects of the contaminations. Once the data has been cleaned or de-noised, data mining can proceed as usual. In this paper, we describe our work in denoising astronomical images from the Faint Images of the Radio Sky at Twenty-Centimeters (FIRST) survey. We are mining this survey to detect radio-emitting galaxies with a bent-double morphology. This task is made difficult by the noise in the images caused by the processing of the sensor data. We compare three different approaches to de-noising: thresholding of wavelet coefficients advocated in the statistical community, traditional Altering methods used in the image processing community, and a simple thresholding scheme proposed by FIRST astronomers. While each approach has its merits and pitfalls, we found that for our purpose, the simple thresholding scheme worked relatively well for the FIRST dataset.

  15. Volumetric image display for complex 3D data visualization

    NASA Astrophysics Data System (ADS)

    Tsao, Che-Chih; Chen, Jyh Shing

    2000-05-01

    A volumetric image display is a new display technology capable of displaying computer generated 3D images in a volumetric space. Many viewers can walk around the display and see the image from omni-directions simultaneously without wearing any glasses. The image is real and possesses all major elements in both physiological and psychological depth cues. Due to the volumetric nature of its image, the VID can provide the most natural human-machine interface in operations involving 3D data manipulation and 3D targets monitoring. The technology creates volumetric 3D images by projecting a series of profiling images distributed in the space form a volumetric image because of the after-image effect of human eyes. Exemplary applications in biomedical image visualization were tested on a prototype display, using different methods to display a data set from Ct-scans. The features of this display technology make it most suitable for applications that require quick understanding of the 3D relations, need frequent spatial interactions with the 3D images, or involve time-varying 3D data. It can also be useful for group discussion and decision making.

  16. 3D augmented reality with integral imaging display

    NASA Astrophysics Data System (ADS)

    Shen, Xin; Hua, Hong; Javidi, Bahram

    2016-06-01

    In this paper, a three-dimensional (3D) integral imaging display for augmented reality is presented. By implementing the pseudoscopic-to-orthoscopic conversion method, elemental image arrays with different capturing parameters can be transferred into the identical format for 3D display. With the proposed merging algorithm, a new set of elemental images for augmented reality display is generated. The newly generated elemental images contain both the virtual objects and real world scene with desired depth information and transparency parameters. The experimental results indicate the feasibility of the proposed 3D augmented reality with integral imaging.

  17. On Alternative Approaches to 3D Image Perception: Monoscopic 3D Techniques

    NASA Astrophysics Data System (ADS)

    Blundell, Barry G.

    2015-06-01

    In the eighteenth century, techniques that enabled a strong sense of 3D perception to be experienced without recourse to binocular disparities (arising from the spatial separation of the eyes) underpinned the first significant commercial sales of 3D viewing devices and associated content. However following the advent of stereoscopic techniques in the nineteenth century, 3D image depiction has become inextricably linked to binocular parallax and outside the vision science and arts communities relatively little attention has been directed towards earlier approaches. Here we introduce relevant concepts and terminology and consider a number of techniques and optical devices that enable 3D perception to be experienced on the basis of planar images rendered from a single vantage point. Subsequently we allude to possible mechanisms for non-binocular parallax based 3D perception. Particular attention is given to reviewing areas likely to be thought-provoking to those involved in 3D display development, spatial visualization, HCI, and other related areas of interdisciplinary research.

  18. 2D and 3D MALDI-imaging: conceptual strategies for visualization and data mining.

    PubMed

    Thiele, Herbert; Heldmann, Stefan; Trede, Dennis; Strehlow, Jan; Wirtz, Stefan; Dreher, Wolfgang; Berger, Judith; Oetjen, Janina; Kobarg, Jan Hendrik; Fischer, Bernd; Maass, Peter

    2014-01-01

    3D imaging has a significant impact on many challenges in life sciences, because biology is a 3-dimensional phenomenon. Current 3D imaging-technologies (various types MRI, PET, SPECT) are labeled, i.e. they trace the localization of a specific compound in the body. In contrast, 3D MALDI mass spectrometry-imaging (MALDI-MSI) is a label-free method imaging the spatial distribution of molecular compounds. It complements 3D imaging labeled methods, immunohistochemistry, and genetics-based methods. However, 3D MALDI-MSI cannot tap its full potential due to the lack of statistical methods for analysis and interpretation of large and complex 3D datasets. To overcome this, we established a complete and robust 3D MALDI-MSI pipeline combined with efficient computational data analysis methods for 3D edge preserving image denoising, 3D spatial segmentation as well as finding colocalized m/z values, which will be reviewed here in detail. Furthermore, we explain, why the integration and correlation of the MALDI imaging data with other imaging modalities allows to enhance the interpretation of the molecular data and provides visualization of molecular patterns that may otherwise not be apparent. Therefore, a 3D data acquisition workflow is described generating a set of 3 different dimensional images representing the same anatomies. First, an in-vitro MRI measurement is performed which results in a three-dimensional image modality representing the 3D structure of the measured object. After sectioning the 3D object into N consecutive slices, all N slices are scanned using an optical digital scanner, enabling for performing the MS measurements. Scanning the individual sections results into low-resolution images, which define the base coordinate system for the whole pipeline. The scanned images conclude the information from the spatial (MRI) and the mass spectrometric (MALDI-MSI) dimension and are used for the spatial three-dimensional reconstruction of the object performed by image

  19. Robust L1 PCA and application in image denoising

    NASA Astrophysics Data System (ADS)

    Gao, Junbin; Kwan, Paul W. H.; Guo, Yi

    2007-11-01

    The so-called robust L1 PCA was introduced in our recent work [1] based on the L1 noise assumption. Due to the heavy tail characteristics of the L1 distribution, the proposed model has been proved much more robust against data outliers. In this paper, we further demonstrate how the learned robust L1 PCA model can be used to denoise image data.

  20. Undecimated Wavelet Transforms for Image De-noising

    SciTech Connect

    Gyaourova, A; Kamath, C; Fodor, I K

    2002-11-19

    A few different approaches exist for computing undecimated wavelet transform. In this work we construct three undecimated schemes and evaluate their performance for image noise reduction. We use standard wavelet based de-noising techniques and compare the performance of our algorithms with the original undecimated wavelet transform, as well as with the decimated wavelet transform. The experiments we have made show that our algorithms have better noise removal/blurring ratio.

  1. An MRI denoising method using image data redundancy and local SNR estimation.

    PubMed

    Golshan, Hosein M; Hasanzadeh, Reza P R; Yousefzadeh, Shahrokh C

    2013-09-01

    This paper presents an LMMSE-based method for the three-dimensional (3D) denoising of MR images assuming a Rician noise model. Conventionally, the LMMSE method estimates the noise-less signal values using the observed MR data samples within local neighborhoods. This is not an efficient procedure to deal with this issue while the 3D MR data intrinsically includes many similar samples that can be used to improve the estimation results. To overcome this problem, we model MR data as random fields and establish a principled way which is capable of choosing the samples not only from a local neighborhood but also from a large portion of the given data. To follow the similar samples within the MR data, an effective similarity measure based on the local statistical moments of images is presented. The parameters of the proposed filter are automatically chosen from the estimated local signal-to-noise ratio. To further enhance the denoising performance, a recursive version of the introduced approach is also addressed. The proposed filter is compared with related state-of-the-art filters using both synthetic and real MR datasets. The experimental results demonstrate the superior performance of our proposal in removing the noise and preserving the anatomical structures of MR images.

  2. Local Spectral Component Decomposition for Multi-Channel Image Denoising.

    PubMed

    Rizkinia, Mia; Baba, Tatsuya; Shirai, Keiichiro; Okuda, Masahiro

    2016-07-01

    We propose a method for local spectral component decomposition based on the line feature of local distribution. Our aim is to reduce noise on multi-channel images by exploiting the linear correlation in the spectral domain of a local region. We first calculate a linear feature over the spectral components of an M -channel image, which we call the spectral line, and then, using the line, we decompose the image into three components: a single M -channel image and two gray-scale images. By virtue of the decomposition, the noise is concentrated on the two images, and thus our algorithm needs to denoise only the two gray-scale images, regardless of the number of the channels. As a result, image deterioration due to the imbalance of the spectral component correlation can be avoided. The experiment shows that our method improves image quality with less deterioration while preserving vivid contrast. Our method is especially effective for hyperspectral images. The experimental results demonstrate that our proposed method can compete with the other state-of-the-art denoising methods.

  3. Imaging hypoxia using 3D photoacoustic spectroscopy

    NASA Astrophysics Data System (ADS)

    Stantz, Keith M.

    2010-02-01

    Purpose: The objective is to develop a multivariate in vivo hemodynamic model of tissue oxygenation (MiHMO2) based on 3D photoacoustic spectroscopy. Introduction: Low oxygen levels, or hypoxia, deprives cancer cells of oxygen and confers resistance to irradiation, some chemotherapeutic drugs, and oxygen-dependent therapies (phototherapy) leading to treatment failure and poor disease-free and overall survival. For example, clinical studies of patients with breast carcinomas, cervical cancer, and head and neck carcinomas (HNC) are more likely to suffer local reoccurrence and metastasis if their tumors are hypoxic. A novel method to non invasively measure tumor hypoxia, identify its type, and monitor its heterogeneity is devised by measuring tumor hemodynamics, MiHMO2. Material and Methods: Simulations are performed to compare tumor pO2 levels and hypoxia based on physiology - perfusion, fractional plasma volume, fractional cellular volume - and its hemoglobin status - oxygen saturation and hemoglobin concentration - based on in vivo measurements of breast, prostate, and ovarian tumors. Simulations of MiHMO2 are performed to assess the influence of scanner resolutions and different mathematic models of oxygen delivery. Results: Sensitivity of pO2 and hypoxic fraction to photoacoustic scanner resolution and dependencies on model complexity will be presented using hemodynamic parameters for different tumors. Conclusions: Photoacoustic CT spectroscopy provides a unique ability to monitor hemodynamic and cellular physiology in tissue, which can be used to longitudinally monitor tumor oxygenation and its response to anti-angiogenic therapies.

  4. Improved deadzone modeling for bivariate wavelet shrinkage-based image denoising

    NASA Astrophysics Data System (ADS)

    DelMarco, Stephen

    2016-05-01

    Modern image processing performed on-board low Size, Weight, and Power (SWaP) platforms, must provide high- performance while simultaneously reducing memory footprint, power consumption, and computational complexity. Image preprocessing, along with downstream image exploitation algorithms such as object detection and recognition, and georegistration, place a heavy burden on power and processing resources. Image preprocessing often includes image denoising to improve data quality for downstream exploitation algorithms. High-performance image denoising is typically performed in the wavelet domain, where noise generally spreads and the wavelet transform compactly captures high information-bearing image characteristics. In this paper, we improve modeling fidelity of a previously-developed, computationally-efficient wavelet-based denoising algorithm. The modeling improvements enhance denoising performance without significantly increasing computational cost, thus making the approach suitable for low-SWAP platforms. Specifically, this paper presents modeling improvements to the Sendur-Selesnick model (SSM) which implements a bivariate wavelet shrinkage denoising algorithm that exploits interscale dependency between wavelet coefficients. We formulate optimization problems for parameters controlling deadzone size which leads to improved denoising performance. Two formulations are provided; one with a simple, closed form solution which we use for numerical result generation, and the second as an integral equation formulation involving elliptic integrals. We generate image denoising performance results over different image sets drawn from public domain imagery, and investigate the effect of wavelet filter tap length on denoising performance. We demonstrate denoising performance improvement when using the enhanced modeling over performance obtained with the baseline SSM model.

  5. Dedicated 3D photoacoustic breast imaging

    PubMed Central

    Kruger, Robert A.; Kuzmiak, Cherie M.; Lam, Richard B.; Reinecke, Daniel R.; Del Rio, Stephen P.; Steed, Doreen

    2013-01-01

    Purpose: To report the design and imaging methodology of a photoacoustic scanner dedicated to imaging hemoglobin distribution throughout a human breast. Methods: The authors developed a dedicated breast photoacoustic mammography (PAM) system using a spherical detector aperture based on our previous photoacoustic tomography scanner. The system uses 512 detectors with rectilinear scanning. The scan shape is a spiral pattern whose radius varies from 24 to 96 mm, thereby allowing a field of view that accommodates a wide range of breast sizes. The authors measured the contrast-to-noise ratio (CNR) using a target comprised of 1-mm dots printed on clear plastic. Each dot absorption coefficient was approximately the same as a 1-mm thickness of whole blood at 756 nm, the output wavelength of the Alexandrite laser used by this imaging system. The target was immersed in varying depths of an 8% solution of stock Liposyn II-20%, which mimics the attenuation of breast tissue (1.1 cm−1). The spatial resolution was measured using a 6 μm-diameter carbon fiber embedded in agar. The breasts of four healthy female volunteers, spanning a range of breast size from a brassiere C cup to a DD cup, were imaged using a 96-mm spiral protocol. Results: The CNR target was clearly visualized to a depth of 53 mm. Spatial resolution, which was estimated from the full width at half-maximum of a profile across the PAM image of a carbon fiber, was 0.42 mm. In the four human volunteers, the vasculature was well visualized throughout the breast tissue, including to the chest wall. Conclusions: CNR, lateral field-of-view and penetration depth of our dedicated PAM scanning system is sufficient to image breasts as large as 1335 mL, which should accommodate up to 90% of the women in the United States. PMID:24320471

  6. 3-D capacitance density imaging system

    DOEpatents

    Fasching, G.E.

    1988-03-18

    A three-dimensional capacitance density imaging of a gasified bed or the like in a containment vessel is achieved using a plurality of electrodes provided circumferentially about the bed in levels and along the bed in channels. The electrodes are individually and selectively excited electrically at each level to produce a plurality of current flux field patterns generated in the bed at each level. The current flux field patterns are suitably sensed and a density pattern of the bed at each level determined. By combining the determined density patterns at each level, a three-dimensional density image of the bed is achieved. 7 figs.

  7. 3-D seismic imaging of complex geologies

    SciTech Connect

    Womble, D.E.; Dosanjh, S.S.; VanDyke, J.P.; Oldfield, R.A.; Greenberg, D.S.

    1995-02-01

    We present three codes for the Intel Paragon that address the problem of three-dimensional seismic imaging of complex geologies. The first code models acoustic wave propagation and can be used to generate data sets to calibrate and validate seismic imaging codes. This code reported the fastest timings for acoustic wave propagation codes at a recent SEG (Society of Exploration Geophysicists) meeting. The second code implements a Kirchhoff method for pre-stack depth migration. Development of this code is almost complete, and preliminary results are presented. The third code implements a wave equation approach to seismic migration and is a Paragon implementation of a code from the ARCO Seismic Benchmark Suite.

  8. A novel de-noising method for B ultrasound images

    NASA Astrophysics Data System (ADS)

    Tian, Da-Yong; Mo, Jia-qing; Yu, Yin-Feng; Lv, Xiao-Yi; Yu, Xiao; Jia, Zhen-Hong

    2015-12-01

    B ultrasound as a kind of ultrasonic imaging, which has become the indispensable diagnosis method in clinical medicine. However, the presence of speckle noise in ultrasound image greatly reduces the image quality and interferes with the accuracy of the diagnosis. Therefore, how to construct a method which can eliminate the speckle noise effectively, and at the same time keep the image details effectively is the research target of the current ultrasonic image de-noising. This paper is intended to remove the inherent speckle noise of B ultrasound image. The novel algorithm proposed is based on both wavelet transformation of B ultrasound images and data fusion of B ultrasound images, with a smaller mean squared error (MSE) and greater signal to noise ratio (SNR) compared with other algorithms. The results of this study can effectively remove speckle noise from B ultrasound images, and can well preserved the details and edge information which will produce better visual effects.

  9. Phase Sensitive Cueing for 3D Objects in Overhead Images

    SciTech Connect

    Paglieroni, D

    2005-02-04

    Locating specific 3D objects in overhead images is an important problem in many remote sensing applications. 3D objects may contain either one connected component or multiple disconnected components. Solutions must accommodate images acquired with diverse sensors at various times of the day, in various seasons of the year, or under various weather conditions. Moreover, the physical manifestation of a 3D object with fixed physical dimensions in an overhead image is highly dependent on object physical dimensions, object position/orientation, image spatial resolution, and imaging geometry (e.g., obliqueness). This paper describes a two-stage computer-assisted approach for locating 3D objects in overhead images. In the matching stage, the computer matches models of 3D objects to overhead images. The strongest degree of match over all object orientations is computed at each pixel. Unambiguous local maxima in the degree of match as a function of pixel location are then found. In the cueing stage, the computer sorts image thumbnails in descending order of figure-of-merit and presents them to human analysts for visual inspection and interpretation. The figure-of-merit associated with an image thumbnail is computed from the degrees of match to a 3D object model associated with unambiguous local maxima that lie within the thumbnail. This form of computer assistance is invaluable when most of the relevant thumbnails are highly ranked, and the amount of inspection time needed is much less for the highly ranked thumbnails than for images as a whole.

  10. 3D laser imaging for concealed object identification

    NASA Astrophysics Data System (ADS)

    Berechet, Ion; Berginc, Gérard; Berechet, Stefan

    2014-09-01

    This paper deals with new optical non-conventional 3D laser imaging. Optical non-conventional imaging explores the advantages of laser imaging to form a three-dimensional image of the scene. 3D laser imaging can be used for threedimensional medical imaging, topography, surveillance, robotic vision because of ability to detect and recognize objects. In this paper, we present a 3D laser imaging for concealed object identification. The objective of this new 3D laser imaging is to provide the user a complete 3D reconstruction of the concealed object from available 2D data limited in number and with low representativeness. The 2D laser data used in this paper come from simulations that are based on the calculation of the laser interactions with the different interfaces of the scene of interest and from experimental results. We show the global 3D reconstruction procedures capable to separate objects from foliage and reconstruct a threedimensional image of the considered object. In this paper, we present examples of reconstruction and completion of three-dimensional images and we analyse the different parameters of the identification process such as resolution, the scenario of camouflage, noise impact and lacunarity degree.

  11. Parametric surface denoising

    NASA Astrophysics Data System (ADS)

    Kakadiaris, Ioannis A.; Konstantinidis, Ioannis; Papadakis, Manos; Ding, Wei; Shen, Lixin

    2005-08-01

    Three dimensional (3D) surfaces can be sampled parametrically in the form of range image data. Smoothing/denoising of such raw data is usually accomplished by adapting techniques developed for intensity image processing, since both range and intensity images comprise parametrically sampled geometry and appearance measurements, respectively. We present a transform-based algorithm for surface denoising, motivated by our previous work on intensity image denoising, which utilizes a non-separable Parseval frame and an ensemble thresholding scheme. The frame is constructed from separable (tensor) products of a piecewise linear spline tight frame and incorporates the weighted average operator and the Sobel operators in directions that are integer multiples of 45°. We compare the performance of this algorithm with other transform-based methods from the recent literature. Our results indicate that such transform methods are suited to the task of smoothing range images.

  12. Critical comparison of 3D imaging approaches

    SciTech Connect

    Bennett, C L

    1999-06-03

    Currently three imaging spectrometer architectures, tunable filter, dispersive, and Fourier transform, are viable for imaging the universe in three dimensions. There are domains of greatest utility for each of these architectures. The optimum choice among the various alternative architectures is dependent on the nature of the desired observations, the maturity of the relevant technology, and the character of the backgrounds. The domain appropriate for each of the alternatives is delineated; both for instruments having ideal performance as well as for instrumentation based on currently available technology. The environment and science objectives for the Next Generation Space Telescope will be used as a specific representative case to provide a basis for comparison of the various alternatives.

  13. 3-D Imaging Based, Radiobiological Dosimetry

    PubMed Central

    Sgouros, George; Frey, Eric; Wahl, Richard; He, Bin; Prideaux, Andrew; Hobbs, Robert

    2008-01-01

    Targeted radionuclide therapy holds promise as a new treatment against cancer. Advances in imaging are making it possible to evaluate the spatial distribution of radioactivity in tumors and normal organs over time. Matched anatomical imaging such as combined SPECT/CT and PET/CT have also made it possible to obtain tissue density information in conjunction with the radioactivity distribution. Coupled with sophisticated iterative reconstruction algorithims, these advances have made it possible to perform highly patient-specific dosimetry that also incorporates radiobiological modeling. Such sophisticated dosimetry techniques are still in the research investigation phase. Given the attendant logistical and financial costs, a demonstrated improvement in patient care will be a prerequisite for the adoption of such highly-patient specific internal dosimetry methods. PMID:18662554

  14. Total variation versus wavelet-based methods for image denoising in fluorescence lifetime imaging microscopy.

    PubMed

    Chang, Ching-Wei; Mycek, Mary-Ann

    2012-05-01

    We report the first application of wavelet-based denoising (noise removal) methods to time-domain box-car fluorescence lifetime imaging microscopy (FLIM) images and compare the results to novel total variation (TV) denoising methods. Methods were tested first on artificial images and then applied to low-light live-cell images. Relative to undenoised images, TV methods could improve lifetime precision up to 10-fold in artificial images, while preserving the overall accuracy of lifetime and amplitude values of a single-exponential decay model and improving local lifetime fitting in live-cell images. Wavelet-based methods were at least 4-fold faster than TV methods, but could introduce significant inaccuracies in recovered lifetime values. The denoising methods discussed can potentially enhance a variety of FLIM applications, including live-cell, in vivo animal, or endoscopic imaging studies, especially under challenging imaging conditions such as low-light or fast video-rate imaging.

  15. A 3D Level Set Method for Microwave Breast Imaging

    PubMed Central

    Colgan, Timothy J.; Hagness, Susan C.; Van Veen, Barry D.

    2015-01-01

    Objective Conventional inverse-scattering algorithms for microwave breast imaging result in moderate resolution images with blurred boundaries between tissues. Recent 2D numerical microwave imaging studies demonstrate that the use of a level set method preserves dielectric boundaries, resulting in a more accurate, higher resolution reconstruction of the dielectric properties distribution. Previously proposed level set algorithms are computationally expensive and thus impractical in 3D. In this paper we present a computationally tractable 3D microwave imaging algorithm based on level sets. Methods We reduce the computational cost of the level set method using a Jacobian matrix, rather than an adjoint method, to calculate Frechet derivatives. We demonstrate the feasibility of 3D imaging using simulated array measurements from 3D numerical breast phantoms. We evaluate performance by comparing full 3D reconstructions to those from a conventional microwave imaging technique. We also quantitatively assess the efficacy of our algorithm in evaluating breast density. Results Our reconstructions of 3D numerical breast phantoms improve upon those of a conventional microwave imaging technique. The density estimates from our level set algorithm are more accurate than those of conventional microwave imaging, and the accuracy is greater than that reported for mammographic density estimation. Conclusion Our level set method leads to a feasible level of computational complexity for full 3D imaging, and reconstructs the heterogeneous dielectric properties distribution of the breast more accurately than conventional microwave imaging methods. Significance 3D microwave breast imaging using a level set method is a promising low-cost, non-ionizing alternative to current breast imaging techniques. PMID:26011863

  16. Acoustic 3D imaging of dental structures

    SciTech Connect

    Lewis, D.K.; Hume, W.R.; Douglass, G.D.

    1997-02-01

    Our goals for the first year of this three dimensional electodynamic imaging project was to determine how to combine flexible, individual addressable; preprocessing of array source signals; spectral extrapolation or received signals; acoustic tomography codes; and acoustic propagation modeling code. We investigated flexible, individually addressable acoustic array material to find the best match in power, sensitivity and cost and settled on PVDF sheet arrays and 3-1 composite material.

  17. 3D/3D registration of coronary CTA and biplane XA reconstructions for improved image guidance

    SciTech Connect

    Dibildox, Gerardo Baka, Nora; Walsum, Theo van; Punt, Mark; Aben, Jean-Paul; Schultz, Carl; Niessen, Wiro

    2014-09-15

    Purpose: The authors aim to improve image guidance during percutaneous coronary interventions of chronic total occlusions (CTO) by providing information obtained from computed tomography angiography (CTA) to the cardiac interventionist. To this end, the authors investigate a method to register a 3D CTA model to biplane reconstructions. Methods: The authors developed a method for registering preoperative coronary CTA with intraoperative biplane x-ray angiography (XA) images via 3D models of the coronary arteries. The models are extracted from the CTA and biplane XA images, and are temporally aligned based on CTA reconstruction phase and XA ECG signals. Rigid spatial alignment is achieved with a robust probabilistic point set registration approach using Gaussian mixture models (GMMs). This approach is extended by including orientation in the Gaussian mixtures and by weighting bifurcation points. The method is evaluated on retrospectively acquired coronary CTA datasets of 23 CTO patients for which biplane XA images are available. Results: The Gaussian mixture model approach achieved a median registration accuracy of 1.7 mm. The extended GMM approach including orientation was not significantly different (P > 0.1) but did improve robustness with regards to the initialization of the 3D models. Conclusions: The authors demonstrated that the GMM approach can effectively be applied to register CTA to biplane XA images for the purpose of improving image guidance in percutaneous coronary interventions.

  18. Potential Cost Savings with 3D Printing Combined With 3D Imaging and CPLM for Fleet Maintenance and Revitalization

    DTIC Science & Technology

    2014-05-01

    1 Potential Cost Savings with 3D Printing Combined With 3D Imaging and CPLM for Fleet Maintenance and Revitalization David N. Ford...2014 4. TITLE AND SUBTITLE Potential Cost Savings with 3D Printing Combined With 3D Imaging and CPLM for Fleet Maintenance and Revitalization 5a...Manufacturing ( 3D printing ) 2 Research Context Problem: Learning curve savings forecasted in SHIPMAIN maintenance initiative have not materialized

  19. Morphometrics, 3D Imaging, and Craniofacial Development

    PubMed Central

    Hallgrimsson, Benedikt; Percival, Christopher J.; Green, Rebecca; Young, Nathan M.; Mio, Washington; Marcucio, Ralph

    2017-01-01

    Recent studies have shown how volumetric imaging and morphometrics can add significantly to our understanding of morphogenesis, the developmental basis for variation and the etiology of structural birth defects. On the other hand, the complex questions and diverse imaging data in developmental biology present morphometrics with more complex challenges than applications in virtually any other field. Meeting these challenges is necessary in order to understand the mechanistic basis for variation in complex morphologies. This chapter reviews the methods and theory that enable the application of modern landmark-based morphometrics to developmental biology and craniofacial development, in particular. We discuss the theoretical foundations of morphometrics as applied to development and review the basic approaches to the quantification of morphology. Focusing on geometric morphometrics, we discuss the principal statistical methods for quantifying and comparing morphological variation and covariation structure within and among groups. Finally, we discuss the future directions for morphometrics in developmental biology that will be required for approaches that enable quantitative integration across the genotype-phenotype map. PMID:26589938

  20. Denoising portal images by means of wavelet techniques

    NASA Astrophysics Data System (ADS)

    Gonzalez Lopez, Antonio Francisco

    Portal images are used in radiotherapy for the verification of patient positioning. The distinguishing feature of this image type lies in its formation process: the same beam used for patient treatment is used for image formation. The high energy of the photons used in radiotherapy strongly limits the quality of portal images: Low contrast between tissues, low spatial resolution and low signal to noise ratio. This Thesis studies the enhancement of these images, in particular denoising of portal images. The statistical properties of portal images and noise are studied: power spectra, statistical dependencies between image and noise and marginal, joint and conditional distributions in the wavelet domain. Later, various denoising methods are applied to noisy portal images. Methods operating in the wavelet domain are the basis of this Thesis. In addition, the Wiener filter and the non local means filter (NLM), operating in the image domain, are used as a reference. Other topics studied in this Thesis are spatial resolution, wavelet processing and image processing in dosimetry in radiotherapy. In this regard, the spatial resolution of portal imaging systems is studied; a new method for determining the spatial resolution of the imaging equipments in digital radiology is presented; the calculation of the power spectrum in the wavelet domain is studied; reducing uncertainty in film dosimetry is investigated; a method for the dosimetry of small radiation fields with radiochromic film is presented; the optimal signal resolution is determined, as a function of the noise level and the quantization step, in the digitization process of films and the useful optical density range is set, as a function of the required uncertainty level, for a densitometric system. Marginal distributions of portal images are similar to those of natural images. This also applies to the statistical relationships between wavelet coefficients, intra-band and inter-band. These facts result in a better

  1. 3D quantitative phase imaging of neural networks using WDT

    NASA Astrophysics Data System (ADS)

    Kim, Taewoo; Liu, S. C.; Iyer, Raj; Gillette, Martha U.; Popescu, Gabriel

    2015-03-01

    White-light diffraction tomography (WDT) is a recently developed 3D imaging technique based on a quantitative phase imaging system called spatial light interference microscopy (SLIM). The technique has achieved a sub-micron resolution in all three directions with high sensitivity granted by the low-coherence of a white-light source. Demonstrations of the technique on single cell imaging have been presented previously; however, imaging on any larger sample, including a cluster of cells, has not been demonstrated using the technique. Neurons in an animal body form a highly complex and spatially organized 3D structure, which can be characterized by neuronal networks or circuits. Currently, the most common method of studying the 3D structure of neuron networks is by using a confocal fluorescence microscope, which requires fluorescence tagging with either transient membrane dyes or after fixation of the cells. Therefore, studies on neurons are often limited to samples that are chemically treated and/or dead. WDT presents a solution for imaging live neuron networks with a high spatial and temporal resolution, because it is a 3D imaging method that is label-free and non-invasive. Using this method, a mouse or rat hippocampal neuron culture and a mouse dorsal root ganglion (DRG) neuron culture have been imaged in order to see the extension of processes between the cells in 3D. Furthermore, the tomogram is compared with a confocal fluorescence image in order to investigate the 3D structure at synapses.

  2. Accommodation response measurements for integral 3D image

    NASA Astrophysics Data System (ADS)

    Hiura, H.; Mishina, T.; Arai, J.; Iwadate, Y.

    2014-03-01

    We measured accommodation responses under integral photography (IP), binocular stereoscopic, and real object display conditions, and viewing conditions of binocular and monocular viewing conditions. The equipment we used was an optometric device and a 3D display. We developed the 3D display for IP and binocular stereoscopic images that comprises a high-resolution liquid crystal display (LCD) and a high-density lens array. The LCD has a resolution of 468 dpi and a diagonal size of 4.8 inches. The high-density lens array comprises 106 x 69 micro lenses that have a focal length of 3 mm and diameter of 1 mm. The lenses are arranged in a honeycomb pattern. The 3D display was positioned 60 cm from an observer under IP and binocular stereoscopic display conditions. The target was presented at eight depth positions relative to the 3D display: 15, 10, and 5 cm in front of the 3D display, on the 3D display panel, and 5, 10, 15 and 30 cm behind the 3D display under the IP and binocular stereoscopic display conditions. Under the real object display condition, the target was displayed on the 3D display panel, and the 3D display was placed at the eight positions. The results suggest that the IP image induced more natural accommodation responses compared to the binocular stereoscopic image. The accommodation responses of the IP image were weaker than those of a real object; however, they showed a similar tendency with those of the real object under the two viewing conditions. Therefore, IP can induce accommodation to the depth positions of 3D images.

  3. From heuristic optimization to dictionary learning: a review and comprehensive comparison of image denoising algorithms.

    PubMed

    Shao, Ling; Yan, Ruomei; Li, Xuelong; Liu, Yan

    2014-07-01

    Image denoising is a well explored topic in the field of image processing. In the past several decades, the progress made in image denoising has benefited from the improved modeling of natural images. In this paper, we introduce a new taxonomy based on image representations for a better understanding of state-of-the-art image denoising techniques. Within each category, several representative algorithms are selected for evaluation and comparison. The experimental results are discussed and analyzed to determine the overall advantages and disadvantages of each category. In general, the nonlocal methods within each category produce better denoising results than local ones. In addition, methods based on overcomplete representations using learned dictionaries perform better than others. The comprehensive study in this paper would serve as a good reference and stimulate new research ideas in image denoising.

  4. 3D Whole Heart Imaging for Congenital Heart Disease

    PubMed Central

    Greil, Gerald; Tandon, Animesh (Aashoo); Silva Vieira, Miguel; Hussain, Tarique

    2017-01-01

    Three-dimensional (3D) whole heart techniques form a cornerstone in cardiovascular magnetic resonance imaging of congenital heart disease (CHD). It offers significant advantages over other CHD imaging modalities and techniques: no ionizing radiation; ability to be run free-breathing; ECG-gated dual-phase imaging for accurate measurements and tissue properties estimation; and higher signal-to-noise ratio and isotropic voxel resolution for multiplanar reformatting assessment. However, there are limitations, such as potentially long acquisition times with image quality degradation. Recent advances in and current applications of 3D whole heart imaging in CHD are detailed, as well as future directions. PMID:28289674

  5. Image based 3D city modeling : Comparative study

    NASA Astrophysics Data System (ADS)

    Singh, S. P.; Jain, K.; Mandla, V. R.

    2014-06-01

    3D city model is a digital representation of the Earth's surface and it's related objects such as building, tree, vegetation, and some manmade feature belonging to urban area. The demand of 3D city modeling is increasing rapidly for various engineering and non-engineering applications. Generally four main image based approaches were used for virtual 3D city models generation. In first approach, researchers were used Sketch based modeling, second method is Procedural grammar based modeling, third approach is Close range photogrammetry based modeling and fourth approach is mainly based on Computer Vision techniques. SketchUp, CityEngine, Photomodeler and Agisoft Photoscan are the main softwares to represent these approaches respectively. These softwares have different approaches & methods suitable for image based 3D city modeling. Literature study shows that till date, there is no complete such type of comparative study available to create complete 3D city model by using images. This paper gives a comparative assessment of these four image based 3D modeling approaches. This comparative study is mainly based on data acquisition methods, data processing techniques and output 3D model products. For this research work, study area is the campus of civil engineering department, Indian Institute of Technology, Roorkee (India). This 3D campus acts as a prototype for city. This study also explains various governing parameters, factors and work experiences. This research work also gives a brief introduction, strengths and weakness of these four image based techniques. Some personal comment is also given as what can do or what can't do from these softwares. At the last, this study shows; it concluded that, each and every software has some advantages and limitations. Choice of software depends on user requirements of 3D project. For normal visualization project, SketchUp software is a good option. For 3D documentation record, Photomodeler gives good result. For Large city

  6. A colour image reproduction framework for 3D colour printing

    NASA Astrophysics Data System (ADS)

    Xiao, Kaida; Sohiab, Ali; Sun, Pei-li; Yates, Julian M.; Li, Changjun; Wuerger, Sophie

    2016-10-01

    In this paper, the current technologies in full colour 3D printing technology were introduced. A framework of colour image reproduction process for 3D colour printing is proposed. A special focus was put on colour management for 3D printed objects. Two approaches, colorimetric colour reproduction and spectral based colour reproduction are proposed in order to faithfully reproduce colours in 3D objects. Two key studies, colour reproduction for soft tissue prostheses and colour uniformity correction across different orientations are described subsequently. Results are clear shown that applying proposed colour image reproduction framework, performance of colour reproduction can be significantly enhanced. With post colour corrections, a further improvement in colour process are achieved for 3D printed objects.

  7. 3-D image pre-processing algorithms for improved automated tracing of neuronal arbors.

    PubMed

    Narayanaswamy, Arunachalam; Wang, Yu; Roysam, Badrinath

    2011-09-01

    The accuracy and reliability of automated neurite tracing systems is ultimately limited by image quality as reflected in the signal-to-noise ratio, contrast, and image variability. This paper describes a novel combination of image processing methods that operate on images of neurites captured by confocal and widefield microscopy, and produce synthetic images that are better suited to automated tracing. The algorithms are based on the curvelet transform (for denoising curvilinear structures and local orientation estimation), perceptual grouping by scalar voting (for elimination of non-tubular structures and improvement of neurite continuity while preserving branch points), adaptive focus detection, and depth estimation (for handling widefield images without deconvolution). The proposed methods are fast, and capable of handling large images. Their ability to handle images of unlimited size derives from automated tiling of large images along the lateral dimension, and processing of 3-D images one optical slice at a time. Their speed derives in part from the fact that the core computations are formulated in terms of the Fast Fourier Transform (FFT), and in part from parallel computation on multi-core computers. The methods are simple to apply to new images since they require very few adjustable parameters, all of which are intuitive. Examples of pre-processing DIADEM Challenge images are used to illustrate improved automated tracing resulting from our pre-processing methods.

  8. Imaging fault zones using 3D seismic image processing techniques

    NASA Astrophysics Data System (ADS)

    Iacopini, David; Butler, Rob; Purves, Steve

    2013-04-01

    Significant advances in structural analysis of deep water structure, salt tectonic and extensional rift basin come from the descriptions of fault system geometries imaged in 3D seismic data. However, even where seismic data are excellent, in most cases the trajectory of thrust faults is highly conjectural and still significant uncertainty exists as to the patterns of deformation that develop between the main faults segments, and even of the fault architectures themselves. Moreover structural interpretations that conventionally define faults by breaks and apparent offsets of seismic reflectors are commonly conditioned by a narrow range of theoretical models of fault behavior. For example, almost all interpretations of thrust geometries on seismic data rely on theoretical "end-member" behaviors where concepts as strain localization or multilayer mechanics are simply avoided. Yet analogue outcrop studies confirm that such descriptions are commonly unsatisfactory and incomplete. In order to fill these gaps and improve the 3D visualization of deformation in the subsurface, seismic attribute methods are developed here in conjunction with conventional mapping of reflector amplitudes (Marfurt & Chopra, 2007)). These signal processing techniques recently developed and applied especially by the oil industry use variations in the amplitude and phase of the seismic wavelet. These seismic attributes improve the signal interpretation and are calculated and applied to the entire 3D seismic dataset. In this contribution we will show 3D seismic examples of fault structures from gravity-driven deep-water thrust structures and extensional basin systems to indicate how 3D seismic image processing methods can not only build better the geometrical interpretations of the faults but also begin to map both strain and damage through amplitude/phase properties of the seismic signal. This is done by quantifying and delineating the short-range anomalies on the intensity of reflector amplitudes

  9. Digital holography and 3D imaging: introduction to feature issue.

    PubMed

    Kim, Myung K; Hayasaki, Yoshio; Picart, Pascal; Rosen, Joseph

    2013-01-01

    This feature issue of Applied Optics on Digital Holography and 3D Imaging is the sixth of an approximately annual series. Forty-seven papers are presented, covering a wide range of topics in phase-shifting methods, low coherence methods, particle analysis, biomedical imaging, computer-generated holograms, integral imaging, and many others.

  10. Optical 3D watermark based digital image watermarking for telemedicine

    NASA Astrophysics Data System (ADS)

    Li, Xiao Wei; Kim, Seok Tae

    2013-12-01

    Region of interest (ROI) of a medical image is an area including important diagnostic information and must be stored without any distortion. This algorithm for application of watermarking technique for non-ROI of the medical image preserving ROI. The paper presents a 3D watermark based medical image watermarking scheme. In this paper, a 3D watermark object is first decomposed into 2D elemental image array (EIA) by a lenslet array, and then the 2D elemental image array data is embedded into the host image. The watermark extraction process is an inverse process of embedding. The extracted EIA through the computational integral imaging reconstruction (CIIR) technique, the 3D watermark can be reconstructed. Because the EIA is composed of a number of elemental images possesses their own perspectives of a 3D watermark object. Even though the embedded watermark data badly damaged, the 3D virtual watermark can be successfully reconstructed. Furthermore, using CAT with various rule number parameters, it is possible to get many channels for embedding. So our method can recover the weak point having only one transform plane in traditional watermarking methods. The effectiveness of the proposed watermarking scheme is demonstrated with the aid of experimental results.

  11. Progresses in 3D integral imaging with optical processing

    NASA Astrophysics Data System (ADS)

    Martínez-Corral, Manuel; Martínez-Cuenca, Raúl; Saavedra, Genaro; Navarro, Héctor; Pons, Amparo; Javidi, Bahram

    2008-11-01

    Integral imaging is a promising technique for the acquisition and auto-stereoscopic display of 3D scenes with full parallax and without the need of any additional devices like special glasses. First suggested by Lippmann in the beginning of the 20th century, integral imaging is based in the intersection of ray cones emitted by a collection of 2D elemental images which store the 3D information of the scene. This paper is devoted to the study, from the ray optics point of view, of the optical effects and interaction with the observer of integral imaging systems.

  12. DCT and DST Based Image Compression for 3D Reconstruction

    NASA Astrophysics Data System (ADS)

    Siddeq, Mohammed M.; Rodrigues, Marcos A.

    2017-03-01

    This paper introduces a new method for 2D image compression whose quality is demonstrated through accurate 3D reconstruction using structured light techniques and 3D reconstruction from multiple viewpoints. The method is based on two discrete transforms: (1) A one-dimensional Discrete Cosine Transform (DCT) is applied to each row of the image. (2) The output from the previous step is transformed again by a one-dimensional Discrete Sine Transform (DST), which is applied to each column of data generating new sets of high-frequency components followed by quantization of the higher frequencies. The output is then divided into two parts where the low-frequency components are compressed by arithmetic coding and the high frequency ones by an efficient minimization encoding algorithm. At decompression stage, a binary search algorithm is used to recover the original high frequency components. The technique is demonstrated by compressing 2D images up to 99% compression ratio. The decompressed images, which include images with structured light patterns for 3D reconstruction and from multiple viewpoints, are of high perceptual quality yielding accurate 3D reconstruction. Perceptual assessment and objective quality of compression are compared with JPEG and JPEG2000 through 2D and 3D RMSE. Results show that the proposed compression method is superior to both JPEG and JPEG2000 concerning 3D reconstruction, and with equivalent perceptual quality to JPEG2000.

  13. Ladar range image denoising by a nonlocal probability statistics algorithm

    NASA Astrophysics Data System (ADS)

    Xia, Zhi-Wei; Li, Qi; Xiong, Zhi-Peng; Wang, Qi

    2013-01-01

    According to the characteristic of range images of coherent ladar and the basis of nonlocal means (NLM), a nonlocal probability statistics (NLPS) algorithm is proposed in this paper. The difference is that NLM performs denoising using the mean of the conditional probability distribution function (PDF) while NLPS using the maximum of the marginal PDF. In the algorithm, similar blocks are found out by the operation of block matching and form a group. Pixels in the group are analyzed by probability statistics and the gray value with maximum probability is used as the estimated value of the current pixel. The simulated range images of coherent ladar with different carrier-to-noise ratio and real range image of coherent ladar with 8 gray-scales are denoised by this algorithm, and the results are compared with those of median filter, multitemplate order mean filter, NLM, median nonlocal mean filter and its incorporation of anatomical side information, and unsupervised information-theoretic adaptive filter. The range abnormality noise and Gaussian noise in range image of coherent ladar are effectively suppressed by NLPS.

  14. Denoising Stimulated Raman Spectroscopic Images by Total Variation Minimization

    PubMed Central

    Liao, Chien-Sheng; Choi, Joon Hee; Zhang, Delong; Chan, Stanley H.; Cheng, Ji-Xin

    2016-01-01

    High-speed coherent Raman scattering imaging is opening a new avenue to unveiling the cellular machinery by visualizing the spatio-temporal dynamics of target molecules or intracellular organelles. By extracting signals from the laser at MHz modulation frequency, current stimulated Raman scattering (SRS) microscopy has reached shot noise limited detection sensitivity. The laser-based local oscillator in SRS microscopy not only generates high levels of signal, but also delivers a large shot noise which degrades image quality and spectral fidelity. Here, we demonstrate a denoising algorithm that removes the noise in both spatial and spectral domains by total variation minimization. The signal-to-noise ratio of SRS spectroscopic images was improved by up to 57 times for diluted dimethyl sulfoxide solutions and by 15 times for biological tissues. Weak Raman peaks of target molecules originally buried in the noise were unraveled. Coupling the denoising algorithm with multivariate curve resolution allowed discrimination of fat stores from protein-rich organelles in C. elegans. Together, our method significantly improved detection sensitivity without frame averaging, which can be useful for in vivo spectroscopic imaging. PMID:26955400

  15. Quadtree structured image approximation for denoising and interpolation.

    PubMed

    Scholefield, Adam; Dragotti, Pier Luigi

    2014-03-01

    The success of many image restoration algorithms is often due to their ability to sparsely describe the original signal. Shukla proposed a compression algorithm, based on a sparse quadtree decomposition model, which could optimally represent piecewise polynomial images. In this paper, we adapt this model to the image restoration by changing the rate-distortion penalty to a description-length penalty. In addition, one of the major drawbacks of this type of approximation is the computational complexity required to find a suitable subspace for each node of the quadtree. We address this issue by searching for a suitable subspace much more efficiently using the mathematics of updating matrix factorisations. Algorithms are developed to tackle denoising and interpolation. Simulation results indicate that we beat state of the art results when the original signal is in the model (e.g., depth images) and are competitive for natural images when the degradation is high.

  16. 3D Subharmonic Ultrasound Imaging In Vitro and In Vivo

    PubMed Central

    Eisenbrey, John R.; Sridharan, Anush; Machado, Priscilla; Zhao, Hongjia; Halldorsdottir, Valgerdur G.; Dave, Jaydev K.; Liu, Ji-Bin; Park, Suhyun; Dianis, Scott; Wallace, Kirk; Thomenius, Kai E.; Forsberg, F.

    2012-01-01

    Rationale and Objectives While contrast-enhanced ultrasound imaging techniques such as harmonic imaging (HI) have evolved to reduce tissue signals using the nonlinear properties of the contrast agent, levels of background suppression have been mixed. Subharmonic imaging (SHI) offers near-complete tissue suppression by centering the receive bandwidth at half the transmitting frequency. In this work we demonstrate the feasibility of 3D SHI and compare it to 3D HI. Materials and Methods 3D HI and SHI were implemented on a Logiq 9 ultrasound scanner (GE Healthcare, Milwaukee, Wisconsin) with a 4D10L probe. Four-cycle SHI was implemented to transmit at 5.8 MHz and receive at 2.9 MHz, while 2-cycle HI was implemented to transmit at 5 MHz and receive at 10 MHz. The ultrasound contrast agent Definity (Lantheus Medical Imaging, North Billerica, MA) was imaged within a flow phantom and the lower pole of two canine kidneys in both HI and SHI modes. Contrast to tissue ratios (CTR) and rendered images were compared offline. Results SHI resulted in significant improvement in CTR levels relative to HI both in vitro (12.11±0.52 vs. 2.67±0.77, p<0.001) and in vivo (5.74±1.92 vs. 2.40±0.48, p=0.04). Rendered 3D SHI images provided better tissue suppression and a greater overall view of vessels in a flow phantom and canine renal vasculature. Conclusions The successful implementation of SHI in 3D allows imaging of vascular networks over a heterogeneous sample volume and should improve future diagnostic accuracy. Additionally, 3D SHI provides improved CTR values relative to 3D HI. PMID:22464198

  17. Low Dose, Low Energy 3d Image Guidance during Radiotherapy

    NASA Astrophysics Data System (ADS)

    Moore, C. J.; Marchant, T.; Amer, A.; Sharrock, P.; Price, P.; Burton, D.

    2006-04-01

    Patient kilo-voltage X-ray cone beam volumetric imaging for radiotherapy was first demonstrated on an Elekta Synergy mega-voltage X-ray linear accelerator. Subsequently low dose, reduced profile reconstruction imaging was shown to be practical for 3D geometric setup registration to pre-treatment planning images without compromising registration accuracy. Reconstruction from X-ray profiles gathered between treatment beam deliveries was also introduced. The innovation of zonal cone beam imaging promises significantly reduced doses to patients and improved soft tissue contrast in the tumour target zone. These developments coincided with the first dynamic 3D monitoring of continuous body topology changes in patients, at the moment of irradiation, using a laser interferometer. They signal the arrival of low dose, low energy 3D image guidance during radiotherapy itself.

  18. Automatic Denoising and Unmixing in Hyperspectral Image Processing

    NASA Astrophysics Data System (ADS)

    Peng, Honghong

    This thesis addresses two important aspects in hyperspectral image processing: automatic hyperspectral image denoising and unmixing. The first part of this thesis is devoted to a novel automatic optimized vector bilateral filter denoising algorithm, while the remainder concerns nonnegative matrix factorization with deterministic annealing for unsupervised unmixing in remote sensing hyperspectral images. The need for automatic hyperspectral image processing has been promoted by the development of potent hyperspectral systems, with hundreds of narrow contiguous bands, spanning the visible to the long wave infrared range of the electromagnetic spectrum. Due to the large volume of raw data generated by such sensors, automatic processing in the hyperspectral images processing chain is preferred to minimize human workload and achieve optimal result. Two of the mostly researched processing for such automatic effort are: hyperspectral image denoising, which is an important preprocessing step for almost all remote sensing tasks, and unsupervised unmixing, which decomposes the pixel spectra into a collection of endmember spectral signatures and their corresponding abundance fractions. Two new methodologies are introduced in this thesis to tackle the automatic processing problems described above. Vector bilateral filtering has been shown to provide good tradeoff between noise removal and edge degradation when applied to multispectral/hyperspectral image denoising. It has also been demonstrated to provide dynamic range enhancement of bands that have impaired signal to noise ratios. Typical vector bilateral filtering usage does not employ parameters that have been determined to satisfy optimality criteria. This thesis also introduces an approach for selection of the parameters of a vector bilateral filter through an optimization procedure rather than by ad hoc means. The approach is based on posing the filtering problem as one of nonlinear estimation and minimizing the Stein

  19. Accelerated 3D catheter visualization from triplanar MR projection images.

    PubMed

    Schirra, Carsten Oliver; Weiss, Steffen; Krueger, Sascha; Caulfield, Denis; Pedersen, Steen F; Razavi, Reza; Kozerke, Sebastian; Schaeffter, Tobias

    2010-07-01

    One major obstacle for MR-guided catheterizations is long acquisition times associated with visualizing interventional devices. Therefore, most techniques presented hitherto rely on single-plane imaging to visualize the catheter. Recently, accelerated three-dimensional (3D) imaging based on compressed sensing has been proposed to reduce acquisition times. However, frame rates with this technique remain low, and the 3D reconstruction problem yields a considerable computational load. In X-ray angiography, it is well understood that the shape of interventional devices can be derived in 3D space from a limited number of projection images. In this work, this fact is exploited to develop a method for 3D visualization of active catheters from multiplanar two-dimensional (2D) projection MR images. This is favorable to 3D MRI as the overall number of acquired profiles, and consequently the acquisition time, is reduced. To further reduce measurement times, compressed sensing is employed. Furthermore, a novel single-channel catheter design is presented that combines a solenoidal tip coil in series with a single-loop antenna, enabling simultaneous tip tracking and shape visualization. The tracked tip and catheter properties provide constraints for compressed sensing reconstruction and subsequent 2D/3D curve fitting. The feasibility of the method is demonstrated in phantoms and in an in vivo pig experiment.

  20. Prostate Mechanical Imaging: 3-D Image Composition and Feature Calculations

    PubMed Central

    Egorov, Vladimir; Ayrapetyan, Suren; Sarvazyan, Armen P.

    2008-01-01

    We have developed a method and a device entitled prostate mechanical imager (PMI) for the real-time imaging of prostate using a transrectal probe equipped with a pressure sensor array and position tracking sensor. PMI operation is based on measurement of the stress pattern on the rectal wall when the probe is pressed against the prostate. Temporal and spatial changes in the stress pattern provide information on the elastic structure of the gland and allow two-dimensional (2-D) and three-dimensional (3-D) reconstruction of prostate anatomy and assessment of prostate mechanical properties. The data acquired allow the calculation of prostate features such as size, shape, nodularity, consistency/hardness, and mobility. The PMI prototype has been validated in laboratory experiments on prostate phantoms and in a clinical study. The results obtained on model systems and in vivo images from patients prove that PMI has potential to become a diagnostic tool that could largely supplant DRE through its higher sensitivity, quantitative record storage, ease-of-use and inherent low cost. PMID:17024836

  1. Exposing digital image forgeries by 3D reconstruction technology

    NASA Astrophysics Data System (ADS)

    Wang, Yongqiang; Xu, Xiaojing; Li, Zhihui; Liu, Haizhen; Li, Zhigang; Huang, Wei

    2009-11-01

    Digital images are easy to tamper and edit due to availability of powerful image processing and editing software. Especially, forged images by taking from a picture of scene, because of no manipulation was made after taking, usual methods, such as digital watermarks, statistical correlation technology, can hardly detect the traces of image tampering. According to image forgery characteristics, a method, based on 3D reconstruction technology, which detect the forgeries by discriminating the dimensional relationship of each object appeared on image, is presented in this paper. This detection method includes three steps. In the first step, all the parameters of images were calibrated and each crucial object on image was chosen and matched. In the second step, the 3D coordinates of each object were calculated by bundle adjustment. In final step, the dimensional relationship of each object was analyzed. Experiments were designed to test this detection method; the 3D reconstruction and the forged image 3D reconstruction were computed independently. Test results show that the fabricating character in digital forgeries can be identified intuitively by this method.

  2. Building 3D scenes from 2D image sequences

    NASA Astrophysics Data System (ADS)

    Cristea, Paul D.

    2006-05-01

    Sequences of 2D images, taken by a single moving video receptor, can be fused to generate a 3D representation. This dynamic stereopsis exists in birds and reptiles, whereas the static binocular stereopsis is common in mammals, including humans. Most multimedia computer vision systems for stereo image capture, transmission, processing, storage and retrieval are based on the concept of binocularity. As a consequence, their main goal is to acquire, conserve and enhance pairs of 2D images able to generate a 3D visual perception in a human observer. Stereo vision in birds is based on the fusion of images captured by each eye, with previously acquired and memorized images from the same eye. The process goes on simultaneously and conjointly for both eyes and generates an almost complete all-around visual field. As a consequence, the baseline distance is no longer fixed, as in the case of binocular 3D view, but adjustable in accordance with the distance to the object of main interest, allowing a controllable depth effect. Moreover, the synthesized 3D scene can have a better resolution than each individual 2D image in the sequence. Compression of 3D scenes can be achieved, and stereo transmissions with lower bandwidth requirements can be developed.

  3. 3D thermography imaging standardization technique for inflammation diagnosis

    NASA Astrophysics Data System (ADS)

    Ju, Xiangyang; Nebel, Jean-Christophe; Siebert, J. Paul

    2005-01-01

    We develop a 3D thermography imaging standardization technique to allow quantitative data analysis. Medical Digital Infrared Thermal Imaging is very sensitive and reliable mean of graphically mapping and display skin surface temperature. It allows doctors to visualise in colour and quantify temperature changes in skin surface. The spectrum of colours indicates both hot and cold responses which may co-exist if the pain associate with an inflammatory focus excites an increase in sympathetic activity. However, due to thermograph provides only qualitative diagnosis information, it has not gained acceptance in the medical and veterinary communities as a necessary or effective tool in inflammation and tumor detection. Here, our technique is based on the combination of visual 3D imaging technique and thermal imaging technique, which maps the 2D thermography images on to 3D anatomical model. Then we rectify the 3D thermogram into a view independent thermogram and conform it a standard shape template. The combination of these imaging facilities allows the generation of combined 3D and thermal data from which thermal signatures can be quantified.

  4. Simultaneous Denoising, Deconvolution, and Demixing of Calcium Imaging Data

    PubMed Central

    Pnevmatikakis, Eftychios A.; Soudry, Daniel; Gao, Yuanjun; Machado, Timothy A.; Merel, Josh; Pfau, David; Reardon, Thomas; Mu, Yu; Lacefield, Clay; Yang, Weijian; Ahrens, Misha; Bruno, Randy; Jessell, Thomas M.; Peterka, Darcy S.; Yuste, Rafael; Paninski, Liam

    2016-01-01

    SUMMARY We present a modular approach for analyzing calcium imaging recordings of large neuronal ensembles. Our goal is to simultaneously identify the locations of the neurons, demix spatially overlapping components, and denoise and deconvolve the spiking activity from the slow dynamics of the calcium indicator. Our approach relies on a constrained nonnegative matrix factorization that expresses the spatiotemporal fluorescence activity as the product of a spatial matrix that encodes the spatial footprint of each neuron in the optical field and a temporal matrix that characterizes the calcium concentration of each neuron over time. This framework is combined with a novel constrained deconvolution approach that extracts estimates of neural activity from fluorescence traces, to create a spatiotemporal processing algorithm that requires minimal parameter tuning. We demonstrate the general applicability of our method by applying it to in vitro and in vivo multineuronal imaging data, whole-brain light-sheet imaging data, and dendritic imaging data. PMID:26774160

  5. Simultaneous Denoising, Deconvolution, and Demixing of Calcium Imaging Data.

    PubMed

    Pnevmatikakis, Eftychios A; Soudry, Daniel; Gao, Yuanjun; Machado, Timothy A; Merel, Josh; Pfau, David; Reardon, Thomas; Mu, Yu; Lacefield, Clay; Yang, Weijian; Ahrens, Misha; Bruno, Randy; Jessell, Thomas M; Peterka, Darcy S; Yuste, Rafael; Paninski, Liam

    2016-01-20

    We present a modular approach for analyzing calcium imaging recordings of large neuronal ensembles. Our goal is to simultaneously identify the locations of the neurons, demix spatially overlapping components, and denoise and deconvolve the spiking activity from the slow dynamics of the calcium indicator. Our approach relies on a constrained nonnegative matrix factorization that expresses the spatiotemporal fluorescence activity as the product of a spatial matrix that encodes the spatial footprint of each neuron in the optical field and a temporal matrix that characterizes the calcium concentration of each neuron over time. This framework is combined with a novel constrained deconvolution approach that extracts estimates of neural activity from fluorescence traces, to create a spatiotemporal processing algorithm that requires minimal parameter tuning. We demonstrate the general applicability of our method by applying it to in vitro and in vivo multi-neuronal imaging data, whole-brain light-sheet imaging data, and dendritic imaging data.

  6. Locally adaptive bilateral clustering for universal image denoising

    NASA Astrophysics Data System (ADS)

    Toh, K. K. V.; Mat Isa, N. A.

    2012-12-01

    This paper presents a novel and efficient locally adaptive denoising method based on clustering of pixels into regions of similar geometric and radiometric structures. Clustering is performed by adaptively segmenting pixels in the local kernel based on their augmented variational series. Then, noise pixels are restored by selectively considering the radiometric and spatial properties of every pixel in the formed clusters. The proposed method is exceedingly robust in conveying reliable local structural information even in the presence of noise. As a result, the proposed method substantially outperforms other state-of-the-art methods in terms of image restoration and computational cost. We support our claims with ample simulated and real data experiments. The relatively fast runtime from extensive simulations also suggests that the proposed method is suitable for a variety of image-based products — either embedded in image capturing devices or applied as image enhancement software.

  7. Developing an efficient technique for satellite image denoising and resolution enhancement for improving classification accuracy

    NASA Astrophysics Data System (ADS)

    Thangaswamy, Sree Sharmila; Kadarkarai, Ramar; Thangaswamy, Sree Renga Raja

    2013-01-01

    Satellite images are corrupted by noise during image acquisition and transmission. The removal of noise from the image by attenuating the high-frequency image components removes important details as well. In order to retain the useful information, improve the visual appearance, and accurately classify an image, an effective denoising technique is required. We discuss three important steps such as image denoising, resolution enhancement, and classification for improving accuracy in a noisy image. An effective denoising technique, hybrid directional lifting, is proposed to retain the important details of the images and improve visual appearance. The discrete wavelet transform based interpolation is developed for enhancing the resolution of the denoised image. The image is then classified using a support vector machine, which is superior to other neural network classifiers. The quantitative performance measures such as peak signal to noise ratio and classification accuracy show the significance of the proposed techniques.

  8. A 3D surface imaging system for assessing human obesity

    NASA Astrophysics Data System (ADS)

    Xu, B.; Yu, W.; Yao, M.; Yao, X.; Li, Q.; Pepper, M. R.; Freeland-Graves, J. H.

    2009-08-01

    The increasing prevalence of obesity suggests a need to develop a convenient, reliable and economical tool for assessment of this condition. Three-dimensional (3D) body surface imaging has emerged as an exciting technology for estimation of body composition. This paper presents a new 3D body imaging system, which was designed for enhanced portability, affordability, and functionality. In this system, stereo vision technology was used to satisfy the requirements for a simple hardware setup and fast image acquisitions. The portability of the system was created via a two-stand configuration, and the accuracy of body volume measurements was improved by customizing stereo matching and surface reconstruction algorithms that target specific problems in 3D body imaging. Body measurement functions dedicated to body composition assessment also were developed. The overall performance of the system was evaluated in human subjects by comparison to other conventional anthropometric methods, as well as air displacement plethysmography, for body fat assessment.

  9. De-noising of digital image correlation based on stationary wavelet transform

    NASA Astrophysics Data System (ADS)

    Guo, Xiang; Li, Yulong; Suo, Tao; Liang, Jin

    2017-03-01

    In this paper, a stationary wavelet transform (SWT) based method is proposed to de-noise the digital image with the light noise, and the SWT de-noise algorithm is presented after the analyzing of the light noise. By using the de-noise algorithm, the method was demonstrated to be capable of providing accurate DIC measurements in the light noise environment. The verification, comparative and realistic experiments were conducted using this method. The result indicate that the de-noise method can be applied to the full-field strain measurement under the light interference with a high accuracy and stability.

  10. Visualization and analysis of 3D microscopic images.

    PubMed

    Long, Fuhui; Zhou, Jianlong; Peng, Hanchuan

    2012-01-01

    In a wide range of biological studies, it is highly desirable to visualize and analyze three-dimensional (3D) microscopic images. In this primer, we first introduce several major methods for visualizing typical 3D images and related multi-scale, multi-time-point, multi-color data sets. Then, we discuss three key categories of image analysis tasks, namely segmentation, registration, and annotation. We demonstrate how to pipeline these visualization and analysis modules using examples of profiling the single-cell gene-expression of C. elegans and constructing a map of stereotyped neurite tracts in a fruit fly brain.

  11. Visualization and Analysis of 3D Microscopic Images

    PubMed Central

    Long, Fuhui; Zhou, Jianlong; Peng, Hanchuan

    2012-01-01

    In a wide range of biological studies, it is highly desirable to visualize and analyze three-dimensional (3D) microscopic images. In this primer, we first introduce several major methods for visualizing typical 3D images and related multi-scale, multi-time-point, multi-color data sets. Then, we discuss three key categories of image analysis tasks, namely segmentation, registration, and annotation. We demonstrate how to pipeline these visualization and analysis modules using examples of profiling the single-cell gene-expression of C. elegans and constructing a map of stereotyped neurite tracts in a fruit fly brain. PMID:22719236

  12. 3D Image Reconstruction: Determination of Pattern Orientation

    SciTech Connect

    Blankenbecler, Richard

    2003-03-13

    The problem of determining the euler angles of a randomly oriented 3-D object from its 2-D Fraunhofer diffraction patterns is discussed. This problem arises in the reconstruction of a positive semi-definite 3-D object using oversampling techniques. In such a problem, the data consists of a measured set of magnitudes from 2-D tomographic images of the object at several unknown orientations. After the orientation angles are determined, the object itself can then be reconstructed by a variety of methods using oversampling, the magnitude data from the 2-D images, physical constraints on the image and then iteration to determine the phases.

  13. Accuracy of 3D Imaging Software in Cephalometric Analysis

    DTIC Science & Technology

    2013-06-21

    Imaging and Communication in Medicine ( DICOM ) files into personal computer-based software to enable 3D reconstruction of the craniofacial skeleton. These...tissue profile. CBCT data can be imported as DICOM files into personal computer–based software to provide 3D reconstruction of the craniofacial...been acquired for the three pig models. The CBCT data were exported into DICOM multi-file format. They will be imported into a proprietary

  14. 3D Image Display Courses for Information Media Students.

    PubMed

    Yanaka, Kazuhisa; Yamanouchi, Toshiaki

    2016-01-01

    Three-dimensional displays are used extensively in movies and games. These displays are also essential in mixed reality, where virtual and real spaces overlap. Therefore, engineers and creators should be trained to master 3D display technologies. For this reason, the Department of Information Media at the Kanagawa Institute of Technology has launched two 3D image display courses specifically designed for students who aim to become information media engineers and creators.

  15. 3D image analysis of abdominal aortic aneurysm

    NASA Astrophysics Data System (ADS)

    Subasic, Marko; Loncaric, Sven; Sorantin, Erich

    2001-07-01

    In this paper we propose a technique for 3-D segmentation of abdominal aortic aneurysm (AAA) from computed tomography angiography (CTA) images. Output data (3-D model) form the proposed method can be used for measurement of aortic shape and dimensions. Knowledge of aortic shape and size is very important in planning of minimally invasive procedure that is for selection of appropriate stent graft device for treatment of AAA. The technique is based on a 3-D deformable model and utilizes the level-set algorithm for implementation of the method. The method performs 3-D segmentation of CTA images and extracts a 3-D model of aortic wall. Once the 3-D model of aortic wall is available it is easy to perform all required measurements for appropriate stent graft selection. The method proposed in this paper uses the level-set algorithm for deformable models, instead of the classical snake algorithm. The main advantage of the level set algorithm is that it enables easy segmentation of complex structures, surpassing most of the drawbacks of the classical approach. We have extended the deformable model to incorporate the a priori knowledge about the shape of the AAA. This helps direct the evolution of the deformable model to correctly segment the aorta. The algorithm has been implemented in IDL and C languages. Experiments have been performed using real patient CTA images and have shown good results.

  16. Gastric Contraction Imaging System Using a 3-D Endoscope.

    PubMed

    Yoshimoto, Kayo; Yamada, Kenji; Watabe, Kenji; Takeda, Maki; Nishimura, Takahiro; Kido, Michiko; Nagakura, Toshiaki; Takahashi, Hideya; Nishida, Tsutomu; Iijima, Hideki; Tsujii, Masahiko; Takehara, Tetsuo; Ohno, Yuko

    2014-01-01

    This paper presents a gastric contraction imaging system for assessment of gastric motility using a 3-D endoscope. Gastrointestinal diseases are mainly based on morphological abnormalities. However, gastrointestinal symptoms are sometimes apparent without visible abnormalities. One of the major factors for these diseases is abnormal gastrointestinal motility. For assessment of gastric motility, a gastric motility imaging system is needed. To assess the dynamic motility of the stomach, the proposed system measures 3-D gastric contractions derived from a 3-D profile of the stomach wall obtained with a developed 3-D endoscope. After obtaining contraction waves, their frequency, amplitude, and speed of propagation can be calculated using a Gaussian function. The proposed system was evaluated for 3-D measurements of several objects with known geometries. The results showed that the surface profiles could be obtained with an error of [Formula: see text] of the distance between two different points on images. Subsequently, we evaluated the validity of a prototype system using a wave simulated model. In the experiment, the amplitude and position of waves could be measured with 1-mm accuracy. The present results suggest that the proposed system can measure the speed and amplitude of contractions. This system has low invasiveness and can assess the motility of the stomach wall directly in a 3-D manner. Our method can be used for examination of gastric morphological and functional abnormalities.

  17. 2D/3D Image Registration using Regression Learning

    PubMed Central

    Chou, Chen-Rui; Frederick, Brandon; Mageras, Gig; Chang, Sha; Pizer, Stephen

    2013-01-01

    In computer vision and image analysis, image registration between 2D projections and a 3D image that achieves high accuracy and near real-time computation is challenging. In this paper, we propose a novel method that can rapidly detect an object’s 3D rigid motion or deformation from a 2D projection image or a small set thereof. The method is called CLARET (Correction via Limited-Angle Residues in External Beam Therapy) and consists of two stages: registration preceded by shape space and regression learning. In the registration stage, linear operators are used to iteratively estimate the motion/deformation parameters based on the current intensity residue between the target projec-tion(s) and the digitally reconstructed radiograph(s) (DRRs) of the estimated 3D image. The method determines the linear operators via a two-step learning process. First, it builds a low-order parametric model of the image region’s motion/deformation shape space from its prior 3D images. Second, using learning-time samples produced from the 3D images, it formulates the relationships between the model parameters and the co-varying 2D projection intensity residues by multi-scale linear regressions. The calculated multi-scale regression matrices yield the coarse-to-fine linear operators used in estimating the model parameters from the 2D projection intensity residues in the registration. The method’s application to Image-guided Radiation Therapy (IGRT) requires only a few seconds and yields good results in localizing a tumor under rigid motion in the head and neck and under respiratory deformation in the lung, using one treatment-time imaging 2D projection or a small set thereof. PMID:24058278

  18. Adaptively wavelet-based image denoising algorithm with edge preserving

    NASA Astrophysics Data System (ADS)

    Tan, Yihua; Tian, Jinwen; Liu, Jian

    2006-02-01

    A new wavelet-based image denoising algorithm, which exploits the edge information hidden in the corrupted image, is presented. Firstly, a canny-like edge detector identifies the edges in each subband. Secondly, multiplying the wavelet coefficients in neighboring scales is implemented to suppress the noise while magnifying the edge information, and the result is utilized to exclude the fake edges. The isolated edge pixel is also identified as noise. Unlike the thresholding method, after that we use local window filter in the wavelet domain to remove noise in which the variance estimation is elaborated to utilize the edge information. This method is adaptive to local image details, and can achieve better performance than the methods of state of the art.

  19. 3D image analysis of abdominal aortic aneurysm

    NASA Astrophysics Data System (ADS)

    Subasic, Marko; Loncaric, Sven; Sorantin, Erich

    2002-05-01

    This paper presents a method for 3-D segmentation of abdominal aortic aneurysm from computed tomography angiography images. The proposed method is automatic and requires minimal user assistance. Segmentation is performed in two steps. First inner and then outer aortic border is segmented. Those two steps are different due to different image conditions on two aortic borders. Outputs of these two segmentations give a complete 3-D model of abdominal aorta. Such a 3-D model is used in measurements of aneurysm area. The deformable model is implemented using the level-set algorithm due to its ability to describe complex shapes in natural manner which frequently occur in pathology. In segmentation of outer aortic boundary we introduced some knowledge based preprocessing to enhance and reconstruct low contrast aortic boundary. The method has been implemented in IDL and C languages. Experiments have been performed using real patient CTA images and have shown good results.

  20. 3D quantitative analysis of brain SPECT images

    NASA Astrophysics Data System (ADS)

    Loncaric, Sven; Ceskovic, Ivan; Petrovic, Ratimir; Loncaric, Srecko

    2001-07-01

    The main purpose of this work is to develop a computer-based technique for quantitative analysis of 3-D brain images obtained by single photon emission computed tomography (SPECT). In particular, the volume and location of ischemic lesion and penumbra is important for early diagnosis and treatment of infracted regions of the brain. SPECT imaging is typically used as diagnostic tool to assess the size and location of the ischemic lesion. The segmentation method presented in this paper utilizes a 3-D deformable model in order to determine size and location of the regions of interest. The evolution of the model is computed using a level-set implementation of the algorithm. In addition to 3-D deformable model the method utilizes edge detection and region growing for realization of a pre-processing. Initial experimental results have shown that the method is useful for SPECT image analysis.

  1. Computerized analysis of pelvic incidence from 3D images

    NASA Astrophysics Data System (ADS)

    Vrtovec, Tomaž; Janssen, Michiel M. A.; Pernuš, Franjo; Castelein, René M.; Viergever, Max A.

    2012-02-01

    The sagittal alignment of the pelvis can be evaluated by the angle of pelvic incidence (PI), which is constant for an arbitrary subject position and orientation and can be therefore compared among subjects in standing, sitting or supine position. In this study, PI was measured from three-dimensional (3D) computed tomography (CT) images of normal subjects that were acquired in supine position. A novel computerized method, based on image processing techniques, was developed to automatically determine the anatomical references required to measure PI, i.e. the centers of the femoral heads in 3D, and the center and inclination of the sacral endplate in 3D. Multiplanar image reformation was applied to obtain perfect sagittal views with all anatomical structures completely in line with the hip axis, from which PI was calculated. The resulting PI (mean+/-standard deviation) was equal to 46.6°+/-9.2° for male subjects (N = 189), 47.6°+/-10.7° for female subjects (N = 181), and 47.1°+/-10.0° for all subjects (N = 370). The obtained measurements of PI from 3D images were not biased by acquisition projection or structure orientation, because all anatomical structures were completely in line with the hip axis. The performed measurements in 3D therefore represent PI according to the actual geometrical relationships among anatomical structures of the sacrum, pelvis and hips, as observed from the perfect sagittal views.

  2. Interactive visualization of multiresolution image stacks in 3D.

    PubMed

    Trotts, Issac; Mikula, Shawn; Jones, Edward G

    2007-04-15

    Conventional microscopy, electron microscopy, and imaging techniques such as MRI and PET commonly generate large stacks of images of the sectioned brain. In other domains, such as neurophysiology, variables such as space or time are also varied along a stack axis. Digital image sizes have been progressively increasing and in virtual microscopy, it is now common to work with individual image sizes that are several hundred megapixels and several gigabytes in size. The interactive visualization of these high-resolution, multiresolution images in 2D has been addressed previously [Sullivan, G., and Baker, R., 1994. Efficient quad-tree coding of images and video. IEEE Trans. Image Process. 3 (3), 327-331]. Here, we describe a method for interactive visualization of multiresolution image stacks in 3D. The method, characterized as quad-tree based multiresolution image stack interactive visualization using a texel projection based criterion, relies on accessing and projecting image tiles from multiresolution image stacks in such a way that, from the observer's perspective, image tiles all appear approximately the same size even though they are accessed from different tiers within the images comprising the stack. This method enables efficient navigation of high-resolution image stacks. We implement this method in a program called StackVis, which is a Windows-based, interactive 3D multiresolution image stack visualization system written in C++ and using OpenGL. It is freely available at http://brainmaps.org.

  3. Episcopic 3D Imaging Methods: Tools for Researching Gene Function

    PubMed Central

    Weninger, Wolfgang J; Geyer, Stefan H

    2008-01-01

    This work aims at describing episcopic 3D imaging methods and at discussing how these methods can contribute to researching the genetic mechanisms driving embryogenesis and tissue remodelling, and the genesis of pathologies. Several episcopic 3D imaging methods exist. The most advanced are capable of generating high-resolution volume data (voxel sizes from 0.5x0.5x1 µm upwards) of small to large embryos of model organisms and tissue samples. Beside anatomy and tissue architecture, gene expression and gene product patterns can be three dimensionally analyzed in their precise anatomical and histological context with the aid of whole mount in situ hybridization or whole mount immunohistochemical staining techniques. Episcopic 3D imaging techniques were and are employed for analyzing the precise morphological phenotype of experimentally malformed, randomly produced, or genetically engineered embryos of biomedical model organisms. It has been shown that episcopic 3D imaging also fits for describing the spatial distribution of genes and gene products during embryogenesis, and that it can be used for analyzing tissue samples of adult model animals and humans. The latter offers the possibility to use episcopic 3D imaging techniques for researching the causality and treatment of pathologies or for staging cancer. Such applications, however, are not yet routine and currently only preliminary results are available. We conclude that, although episcopic 3D imaging is in its very beginnings, it represents an upcoming methodology, which in short terms will become an indispensable tool for researching the genetic regulation of embryo development as well as the genesis of malformations and diseases. PMID:19452045

  4. Proposed traceable structural resolution protocols for 3D imaging systems

    NASA Astrophysics Data System (ADS)

    MacKinnon, David; Beraldin, J.-Angelo; Cournoyer, Luc; Carrier, Benjamin; Blais, François

    2009-08-01

    A protocol for determining structural resolution using a potentially-traceable reference material is proposed. Where possible, terminology was selected to conform to those published in ISO JCGM 200:2008 (VIM) and ASTM E 2544-08 documents. The concepts of resolvability and edge width are introduced to more completely describe the ability of an optical non-contact 3D imaging system to resolve small features. A distinction is made between 3D range cameras, that obtain spatial data from the total field of view at once, and 3D range scanners, that accumulate spatial data for the total field of view over time. The protocol is presented through the evaluation of a 3D laser line range scanner.

  5. Image quality enhancement and computation acceleration of 3D holographic display using a symmetrical 3D GS algorithm.

    PubMed

    Zhou, Pengcheng; Bi, Yong; Sun, Minyuan; Wang, Hao; Li, Fang; Qi, Yan

    2014-09-20

    The 3D Gerchberg-Saxton (GS) algorithm can be used to compute a computer-generated hologram (CGH) to produce a 3D holographic display. But, using the 3D GS method, there exists a serious distortion in reconstructions of binary input images. We have eliminated the distortion and improved the image quality of the reconstructions by a maximum of 486%, using a symmetrical 3D GS algorithm that is developed based on a traditional 3D GS algorithm. In addition, the hologram computation speed has been accelerated by 9.28 times, which is significant for real-time holographic displays.

  6. Image denoising using principal component analysis in the wavelet domain

    NASA Astrophysics Data System (ADS)

    Bacchelli, Silvia; Papi, Serena

    2006-05-01

    In this work we describe a method for removing Gaussian noise from digital images, based on the combination of the wavelet packet transform and the principal component analysis. In particular, since the aim of denoising is to retain the energy of the signal while discarding the energy of the noise, our basic idea is to construct powerful tailored filters by applying the Karhunen-Loeve transform in the wavelet packet domain, thus obtaining a compaction of the signal energy into a few principal components, while the noise is spread over all the transformed coefficients. This allows us to act with a suitable shrinkage function on these new coefficients, removing the noise without blurring the edges and the important characteristics of the images. The results of a large numerical experimentation encourage us to keep going in this direction with our studies.

  7. 3D EFT imaging with planar electrode array: Numerical simulation

    NASA Astrophysics Data System (ADS)

    Tuykin, T.; Korjenevsky, A.

    2010-04-01

    Electric field tomography (EFT) is the new modality of the quasistatic electromagnetic sounding of conductive media recently investigated theoretically and realized experimentally. The demonstrated results pertain to 2D imaging with circular or linear arrays of electrodes (and the linear array provides quite poor quality of imaging). In many applications 3D imaging is essential or can increase value of the investigation significantly. In this report we present the first results of numerical simulation of the EFT imaging system with planar array of electrodes which allows 3D visualization of the subsurface conductivity distribution. The geometry of the system is similar to the geometry of our EIT breast imaging system providing 3D conductivity imaging in form of cross-sections set with different depth from the surface. The EFT principle of operation and reconstruction approach differs from the EIT system significantly. So the results of numerical simulation are important to estimate if comparable quality of imaging is possible with the new contactless method. The EFT forward problem is solved using finite difference time domain (FDTD) method for the 8×8 square electrodes array. The calculated results of measurements are used then to reconstruct conductivity distributions by the filtered backprojections along electric field lines. The reconstructed images of the simple test objects are presented.

  8. 3-D Display Of Magnetic Resonance Imaging Of The Spine

    NASA Astrophysics Data System (ADS)

    Nelson, Alan C.; Kim, Yongmin; Haralick, Robert M.; Anderson, Paul A.; Johnson, Roger H.; DeSoto, Larry A.

    1988-06-01

    The original data is produced through standard magnetic resonance imaging (MRI) procedures with a surface coil applied to the lower back of a normal human subject. The 3-D spine image data consists of twenty-six contiguous slices with 256 x 256 pixels per slice. Two methods for visualization of the 3-D spine are explored. One method utilizes a verifocal mirror system which creates a true 3-D virtual picture of the object. Another method uses a standard high resolution monitor to simultaneously show the three orthogonal sections which intersect at any user-selected point within the object volume. We discuss the application of these systems in assessment of low back pain.

  9. Hyperspectral image denoising using the robust low-rank tensor recovery.

    PubMed

    Li, Chang; Ma, Yong; Huang, Jun; Mei, Xiaoguang; Ma, Jiayi

    2015-09-01

    Denoising is an important preprocessing step to further analyze the hyperspectral image (HSI), and many denoising methods have been used for the denoising of the HSI data cube. However, the traditional denoising methods are sensitive to outliers and non-Gaussian noise. In this paper, by utilizing the underlying low-rank tensor property of the clean HSI data and the sparsity property of the outliers and non-Gaussian noise, we propose a new model based on the robust low-rank tensor recovery, which can preserve the global structure of HSI and simultaneously remove the outliers and different types of noise: Gaussian noise, impulse noise, dead lines, and so on. The proposed model can be solved by the inexact augmented Lagrangian method, and experiments on simulated and real hyperspectral images demonstrate that the proposed method is efficient for HSI denoising.

  10. Automated curved planar reformation of 3D spine images

    NASA Astrophysics Data System (ADS)

    Vrtovec, Tomaz; Likar, Bostjan; Pernus, Franjo

    2005-10-01

    Traditional techniques for visualizing anatomical structures are based on planar cross-sections from volume images, such as images obtained by computed tomography (CT) or magnetic resonance imaging (MRI). However, planar cross-sections taken in the coordinate system of the 3D image often do not provide sufficient or qualitative enough diagnostic information, because planar cross-sections cannot follow curved anatomical structures (e.g. arteries, colon, spine, etc). Therefore, not all of the important details can be shown simultaneously in any planar cross-section. To overcome this problem, reformatted images in the coordinate system of the inspected structure must be created. This operation is usually referred to as curved planar reformation (CPR). In this paper we propose an automated method for CPR of 3D spine images, which is based on the image transformation from the standard image-based to a novel spine-based coordinate system. The axes of the proposed spine-based coordinate system are determined on the curve that represents the vertebral column, and the rotation of the vertebrae around the spine curve, both of which are described by polynomial models. The optimal polynomial parameters are obtained in an image analysis based optimization framework. The proposed method was qualitatively and quantitatively evaluated on five CT spine images. The method performed well on both normal and pathological cases and was consistent with manually obtained ground truth data. The proposed spine-based CPR benefits from reduced structural complexity in favour of improved feature perception of the spine. The reformatted images are diagnostically valuable and enable easier navigation, manipulation and orientation in 3D space. Moreover, reformatted images may prove useful for segmentation and other image analysis tasks.

  11. 3D imaging lidar for lunar robotic exploration

    NASA Astrophysics Data System (ADS)

    Hussein, Marwan W.; Tripp, Jeffrey W.

    2009-05-01

    Part of the requirements of the future Constellation program is to optimize lunar surface operations and reduce hazards to astronauts. Toward this end, many robotic platforms, rovers in specific, are being sought to carry out a multitude of missions involving potential EVA sites survey, surface reconnaissance, path planning and obstacle detection and classification. 3D imaging lidar technology provides an enabling capability that allows fast, accurate and detailed collection of three-dimensional information about the rover's environment. The lidar images the region of interest by scanning a laser beam and measuring the pulse time-of-flight and the bearing. The accumulated set of laser ranges and bearings constitutes the threedimensional image. As part of the ongoing NASA Ames research center activities in lunar robotics, the utility of 3D imaging lidar was evaluated by testing Optech's ILRIS-3D lidar on board the K-10 Red rover during the recent Human - Robotics Systems (HRS) field trails in Lake Moses, WA. This paper examines the results of the ILRIS-3D trials, presents the data obtained and discusses its application in lunar surface robotic surveying and scouting.

  12. 3D FaceCam: a fast and accurate 3D facial imaging device for biometrics applications

    NASA Astrophysics Data System (ADS)

    Geng, Jason; Zhuang, Ping; May, Patrick; Yi, Steven; Tunnell, David

    2004-08-01

    Human faces are fundamentally three-dimensional (3D) objects, and each face has its unique 3D geometric profile. The 3D geometric features of a human face can be used, together with its 2D texture, for rapid and accurate face recognition purposes. Due to the lack of low-cost and robust 3D sensors and effective 3D facial recognition (FR) algorithms, almost all existing FR systems use 2D face images. Genex has developed 3D solutions that overcome the inherent problems in 2D while also addressing limitations in other 3D alternatives. One important aspect of our solution is a unique 3D camera (the 3D FaceCam) that combines multiple imaging sensors within a single compact device to provide instantaneous, ear-to-ear coverage of a human face. This 3D camera uses three high-resolution CCD sensors and a color encoded pattern projection system. The RGB color information from each pixel is used to compute the range data and generate an accurate 3D surface map. The imaging system uses no moving parts and combines multiple 3D views to provide detailed and complete 3D coverage of the entire face. Images are captured within a fraction of a second and full-frame 3D data is produced within a few seconds. This described method provides much better data coverage and accuracy in feature areas with sharp features or details (such as the nose and eyes). Using this 3D data, we have been able to demonstrate that a 3D approach can significantly improve the performance of facial recognition. We have conducted tests in which we have varied the lighting conditions and angle of image acquisition in the "field." These tests have shown that the matching results are significantly improved when enrolling a 3D image rather than a single 2D image. With its 3D solutions, Genex is working toward unlocking the promise of powerful 3D FR and transferring FR from a lab technology into a real-world biometric solution.

  13. Self-adaptive image denoising based on bidimensional empirical mode decomposition (BEMD).

    PubMed

    Guo, Song; Luan, Fangjun; Song, Xiaoyu; Li, Changyou

    2014-01-01

    To better analyze images with the Gaussian white noise, it is necessary to remove the noise before image processing. In this paper, we propose a self-adaptive image denoising method based on bidimensional empirical mode decomposition (BEMD). Firstly, normal probability plot confirms that 2D-IMF of Gaussian white noise images decomposed by BEMD follow the normal distribution. Secondly, energy estimation equation of the ith 2D-IMF (i=2,3,4,......) is proposed referencing that of ith IMF (i=2,3,4,......) obtained by empirical mode decomposition (EMD). Thirdly, the self-adaptive threshold of each 2D-IMF is calculated. Eventually, the algorithm of the self-adaptive image denoising method based on BEMD is described. From the practical perspective, this is applied for denoising of the magnetic resonance images (MRI) of the brain. And the results show it has a better denoising performance compared with other methods.

  14. Integration of real-time 3D image acquisition and multiview 3D display

    NASA Astrophysics Data System (ADS)

    Zhang, Zhaoxing; Geng, Zheng; Li, Tuotuo; Li, Wei; Wang, Jingyi; Liu, Yongchun

    2014-03-01

    Seamless integration of 3D acquisition and 3D display systems offers enhanced experience in 3D visualization of the real world objects or scenes. The vivid representation of captured 3D objects displayed on a glasses-free 3D display screen could bring the realistic viewing experience to viewers as if they are viewing real-world scene. Although the technologies in 3D acquisition and 3D display have advanced rapidly in recent years, effort is lacking in studying the seamless integration of these two different aspects of 3D technologies. In this paper, we describe our recent progress on integrating a light-field 3D acquisition system and an autostereoscopic multiview 3D display for real-time light field capture and display. This paper focuses on both the architecture design and the implementation of the hardware and the software of this integrated 3D system. A prototype of the integrated 3D system is built to demonstrate the real-time 3D acquisition and 3D display capability of our proposed system.

  15. Practical pseudo-3D registration for large tomographic images

    NASA Astrophysics Data System (ADS)

    Liu, Xuan; Laperre, Kjell; Sasov, Alexander

    2014-09-01

    Image registration is a powerful tool in various tomographic applications. Our main focus is on microCT applications in which samples/animals can be scanned multiple times under different conditions or at different time points. For this purpose, a registration tool capable of handling fairly large volumes has been developed, using a novel pseudo-3D method to achieve fast and interactive registration with simultaneous 3D visualization. To reduce computation complexity in 3D registration, we decompose it into several 2D registrations, which are applied to the orthogonal views (transaxial, sagittal and coronal) sequentially and iteratively. After registration in each view, the next view is retrieved with the new transformation matrix for registration. This reduces the computation complexity significantly. For rigid transform, we only need to search for 3 parameters (2 shifts, 1 rotation) in each of the 3 orthogonal views instead of 6 (3 shifts, 3 rotations) for full 3D volume. In addition, the amount of voxels involved is also significantly reduced. For the proposed pseudo-3D method, image-based registration is employed, with Sum of Square Difference (SSD) as the similarity measure. The searching engine is Powell's conjugate direction method. In this paper, only rigid transform is used. However, it can be extended to affine transform by adding scaling and possibly shearing to the transform model. We have noticed that more information can be used in the 2D registration if Maximum Intensity Projections (MIP) or Parallel Projections (PP) is used instead of the orthogonal views. Also, other similarity measures, such as covariance or mutual information, can be easily incorporated. The initial evaluation on microCT data shows very promising results. Two application examples are shown: dental samples before and after treatment and structural changes in materials before and after compression. Evaluation on registration accuracy between pseudo-3D method and true 3D method has

  16. Optimizing 3D image quality and performance for stereoscopic gaming

    NASA Astrophysics Data System (ADS)

    Flack, Julien; Sanderson, Hugh; Pegg, Steven; Kwok, Simon; Paterson, Daniel

    2009-02-01

    The successful introduction of stereoscopic TV systems, such as Samsung's 3D Ready Plasma, requires high quality 3D content to be commercially available to the consumer. Console and PC games provide the most readily accessible source of high quality 3D content. This paper describes innovative developments in a generic, PC-based game driver architecture that addresses the two key issues affecting 3D gaming: quality and speed. At the heart of the quality issue are the same considerations that studios face producing stereoscopic renders from CG movies: how best to perform the mapping from a geometric CG environment into the stereoscopic display volume. The major difference being that for game drivers this mapping cannot be choreographed by hand but must be automatically calculated in real-time without significant impact on performance. Performance is a critical issue when dealing with gaming. Stereoscopic gaming has traditionally meant rendering the scene twice with the associated performance overhead. An alternative approach is to render the scene from one virtual camera position and use information from the z-buffer to generate a stereo pair using Depth-Image-Based Rendering (DIBR). We analyze this trade-off in more detail and provide some results relating to both 3D image quality and render performance.

  17. A Fast Algorithm for Denoising Magnitude Diffusion-Weighted Images with Rank and Edge Constraints

    PubMed Central

    Lam, Fan; Liu, Ding; Song, Zhuang; Schuff, Norbert; Liang, Zhi-Pei

    2015-01-01

    Purpose To accelerate denoising of magnitude diffusion-weighted images subject to joint rank and edge constraints. Methods We extend a previously proposed majorize-minimize (MM) method for statistical estimation that involves noncentral χ distributions and joint rank and edge constraints. A new algorithm is derived which decomposes the constrained noncentral χ denoising problem into a series of constrained Gaussian denoising problems each of which is then solved using an efficient alternating minimization scheme. Results The performance of the proposed algorithm has been evaluated using both simulated and experimental data. Results from simulations based on ex vivo data show that the new algorithm achieves about a factor of 10 speed up over the original Quasi-Newton based algorithm. This improvement in computational efficiency enabled denoising of large data sets containing many diffusion-encoding directions. The denoising performance of the new efficient algorithm is found to be comparable to or even better than that of the original slow algorithm. For an in vivo high-resolution Q-ball acquisition, comparison of fiber tracking results around hippocampus region before and after denoising will also be shown to demonstrate the denoising effects of the new algorithm. Conclusion The optimization problem associated with denoising noncentral χ distributed diffusion-weighted images subject to joint rank and edge constraints can be solved efficiently using an MM-based algorithm. PMID:25733066

  18. Simultaneous Fusion and Denoising of Panchromatic and Multispectral Satellite Images

    NASA Astrophysics Data System (ADS)

    Ragheb, Amr M.; Osman, Heba; Abbas, Alaa M.; Elkaffas, Saleh M.; El-Tobely, Tarek A.; Khamis, S.; Elhalawany, Mohamed E.; Nasr, Mohamed E.; Dessouky, Moawad I.; Al-Nuaimy, Waleed; Abd El-Samie, Fathi E.

    2012-12-01

    To identify objects in satellite images, multispectral (MS) images with high spectral resolution and low spatial resolution, and panchromatic (Pan) images with high spatial resolution and low spectral resolution need to be fused. Several fusion methods such as the intensity-hue-saturation (IHS), the discrete wavelet transform, the discrete wavelet frame transform (DWFT), and the principal component analysis have been proposed in recent years to obtain images with both high spectral and spatial resolutions. In this paper, a hybrid fusion method for satellite images comprising both the IHS transform and the DWFT is proposed. This method tries to achieve the highest possible spectral and spatial resolutions with as small distortion in the fused image as possible. A comparison study between the proposed hybrid method and the traditional methods is presented in this paper. Different MS and Pan images from Landsat-5, Spot, Landsat-7, and IKONOS satellites are used in this comparison. The effect of noise on the proposed hybrid fusion method as well as the traditional fusion methods is studied. Experimental results show the superiority of the proposed hybrid method to the traditional methods. The results show also that a wavelet denoising step is required when fusion is performed at low signal-to-noise ratios.

  19. 3-D object-oriented image analysis of geophysical data

    NASA Astrophysics Data System (ADS)

    Fadel, I.; Kerle, N.; van der Meijde, M.

    2014-07-01

    Geophysical data are the main source of information about the subsurface. Geophysical techniques are, however, highly non-unique in determining specific physical parameters and boundaries of subsurface objects. To obtain actual physical information, an inversion process is often applied, in which measurements at or above the Earth surface are inverted into a 2- or 3-D subsurface spatial distribution of the physical property. Interpreting these models into structural objects, related to physical processes, requires a priori knowledge and expert analysis which is susceptible to subjective choices and is therefore often non-repeatable. In this research, we implemented a recently introduced object-based approach to interpret the 3-D inversion results of a single geophysical technique using the available a priori information and the physical and geometrical characteristics of the interpreted objects. The introduced methodology is semi-automatic and repeatable, and allows the extraction of subsurface structures using 3-D object-oriented image analysis (3-D OOA) in an objective knowledge-based classification scheme. The approach allows for a semi-objective setting of thresholds that can be tested and, if necessary, changed in a very fast and efficient way. These changes require only changing the thresholds used in a so-called ruleset, which is composed of algorithms that extract objects from a 3-D data cube. The approach is tested on a synthetic model, which is based on a priori knowledge on objects present in the study area (Tanzania). Object characteristics and thresholds were well defined in a 3-D histogram of velocity versus depth, and objects were fully retrieved. The real model results showed how 3-D OOA can deal with realistic 3-D subsurface conditions in which the boundaries become fuzzy, the object extensions become unclear and the model characteristics vary with depth due to the different physical conditions. As expected, the 3-D histogram of the real data was

  20. Noninvasive computational imaging of cardiac electrophysiology for 3-D infarct.

    PubMed

    Wang, Linwei; Wong, Ken C L; Zhang, Heye; Liu, Huafeng; Shi, Pengcheng

    2011-04-01

    Myocardial infarction (MI) creates electrophysiologically altered substrates that are responsible for ventricular arrhythmias, such as tachycardia and fibrillation. The presence, size, location, and composition of infarct scar bear significant prognostic and therapeutic implications for individual subjects. We have developed a statistical physiological model-constrained framework that uses noninvasive body-surface-potential data and tomographic images to estimate subject-specific transmembrane-potential (TMP) dynamics inside the 3-D myocardium. In this paper, we adapt this framework for the purpose of noninvasive imaging, detection, and quantification of 3-D scar mass for postMI patients: the framework requires no prior knowledge of MI and converges to final subject-specific TMP estimates after several passes of estimation with intermediate feedback; based on the primary features of the estimated spatiotemporal TMP dynamics, we provide 3-D imaging of scar tissue and quantitative evaluation of scar location and extent. Phantom experiments were performed on a computational model of realistic heart-torso geometry, considering 87 transmural infarct scars of different sizes and locations inside the myocardium, and 12 compact infarct scars (extent between 10% and 30%) at different transmural depths. Real-data experiments were carried out on BSP and magnetic resonance imaging (MRI) data from four postMI patients, validated by gold standards and existing results. This framework shows unique advantage of noninvasive, quantitative, computational imaging of subject-specific TMP dynamics and infarct mass of the 3-D myocardium, with the potential to reflect details in the spatial structure and tissue composition/heterogeneity of 3-D infarct scar.

  1. Refraction Correction in 3D Transcranial Ultrasound Imaging

    PubMed Central

    Lindsey, Brooks D.; Smith, Stephen W.

    2014-01-01

    We present the first correction of refraction in three-dimensional (3D) ultrasound imaging using an iterative approach that traces propagation paths through a two-layer planar tissue model, applying Snell’s law in 3D. This approach is applied to real-time 3D transcranial ultrasound imaging by precomputing delays offline for several skull thicknesses, allowing the user to switch between three sets of delays for phased array imaging at the push of a button. Simulations indicate that refraction correction may be expected to increase sensitivity, reduce beam steering errors, and partially restore lost spatial resolution, with the greatest improvements occurring at the largest steering angles. Distorted images of cylindrical lesions were created by imaging through an acrylic plate in a tissue-mimicking phantom. As a result of correcting for refraction, lesions were restored to 93.6% of their original diameter in the lateral direction and 98.1% of their original shape along the long axis of the cylinders. In imaging two healthy volunteers, the mean brightness increased by 8.3% and showed no spatial dependency. PMID:24275538

  2. 3D Imaging of Density Gradients Using Plenoptic BOS

    NASA Astrophysics Data System (ADS)

    Klemkowsky, Jenna; Clifford, Chris; Fahringer, Timothy; Thurow, Brian

    2016-11-01

    The combination of background oriented schlieren (BOS) and a plenoptic camera, termed Plenoptic BOS, is explored through two proof-of-concept experiments. The motivation of this work is to provide a 3D technique capable of observing density disturbances. BOS uses the relationship between density and refractive index gradients to observe an apparent shift in a patterned background through image comparison. Conventional BOS systems acquire a single line-of-sight measurement, and require complex configurations to obtain 3D measurements, which are not always conducive to experimental facilities. Plenoptic BOS exploits the plenoptic camera's ability to generate multiple perspective views and refocused images from a single raw plenoptic image during post processing. Using such capabilities, with regards to BOS, provides multiple line-of-sight measurements of density disturbances, which can be collectively used to generate refocused BOS images. Such refocused images allow the position of density disturbances to be qualitatively and quantitatively determined. The image that provides the sharpest density gradient signature corresponds to a specific depth. These results offer motivation to advance Plenoptic BOS with an ultimate goal of reconstructing a 3D density field.

  3. An automated 3D reconstruction method of UAV images

    NASA Astrophysics Data System (ADS)

    Liu, Jun; Wang, He; Liu, Xiaoyang; Li, Feng; Sun, Guangtong; Song, Ping

    2015-10-01

    In this paper a novel fully automated 3D reconstruction approach based on low-altitude unmanned aerial vehicle system (UAVs) images will be presented, which does not require previous camera calibration or any other external prior knowledge. Dense 3D point clouds are generated by integrating orderly feature extraction, image matching, structure from motion (SfM) and multi-view stereo (MVS) algorithms, overcoming many of the cost, time limitations of rigorous photogrammetry techniques. An image topology analysis strategy is introduced to speed up large scene reconstruction by taking advantage of the flight-control data acquired by UAV. Image topology map can significantly reduce the running time of feature matching by limiting the combination of images. A high-resolution digital surface model of the study area is produced base on UAV point clouds by constructing the triangular irregular network. Experimental results show that the proposed approach is robust and feasible for automatic 3D reconstruction of low-altitude UAV images, and has great potential for the acquisition of spatial information at large scales mapping, especially suitable for rapid response and precise modelling in disaster emergency.

  4. Denoising and 4D visualization of OCT images

    PubMed Central

    Gargesha, Madhusudhana; Jenkins, Michael W.; Rollins, Andrew M.; Wilson, David L.

    2009-01-01

    We are using Optical Coherence Tomography (OCT) to image structure and function of the developing embryonic heart in avian models. Fast OCT imaging produces very large 3D (2D + time) and 4D (3D volumes + time) data sets, which greatly challenge ones ability to visualize results. Noise in OCT images poses additional challenges. We created an algorithm with a quick, data set specific optimization for reduction of both shot and speckle noise and applied it to 3D visualization and image segmentation in OCT. When compared to baseline algorithms (median, Wiener, orthogonal wavelet, basic non-orthogonal wavelet), a panel of experts judged the new algorithm to give much improved volume renderings concerning both noise and 3D visualization. Specifically, the algorithm provided a better visualization of the myocardial and endocardial surfaces, and the interaction of the embryonic heart tube with surrounding tissue. Quantitative evaluation using an image quality figure of merit also indicated superiority of the new algorithm. Noise reduction aided semi-automatic 2D image segmentation, as quantitatively evaluated using a contour distance measure with respect to an expert segmented contour. In conclusion, the noise reduction algorithm should be quite useful for visualization and quantitative measurements (e.g., heart volume, stroke volume, contraction velocity, etc.) in OCT embryo images. With its semi-automatic, data set specific optimization, we believe that the algorithm can be applied to OCT images from other applications. PMID:18679509

  5. Dual tree complex wavelet transform based denoising of optical microscopy images.

    PubMed

    Bal, Ufuk

    2012-12-01

    Photon shot noise is the main noise source of optical microscopy images and can be modeled by a Poisson process. Several discrete wavelet transform based methods have been proposed in the literature for denoising images corrupted by Poisson noise. However, the discrete wavelet transform (DWT) has disadvantages such as shift variance, aliasing, and lack of directional selectivity. To overcome these problems, a dual tree complex wavelet transform is used in our proposed denoising algorithm. Our denoising algorithm is based on the assumption that for the Poisson noise case threshold values for wavelet coefficients can be estimated from the approximation coefficients. Our proposed method was compared with one of the state of the art denoising algorithms. Better results were obtained by using the proposed algorithm in terms of image quality metrics. Furthermore, the contrast enhancement effect of the proposed method on collagen fıber images is examined. Our method allows fast and efficient enhancement of images obtained under low light intensity conditions.

  6. 1024 pixels single photon imaging array for 3D ranging

    NASA Astrophysics Data System (ADS)

    Bellisai, S.; Guerrieri, F.; Tisa, S.; Zappa, F.; Tosi, A.; Giudice, A.

    2011-01-01

    Three dimensions (3D) acquisition systems are driving applications in many research field. Nowadays 3D acquiring systems are used in a lot of applications, such as cinema industry or in automotive (for active security systems). Depending on the application, systems present different features, for example color sensitivity, bi-dimensional image resolution, distance measurement accuracy and acquisition frame rate. The system we developed acquires 3D movie using indirect Time of Flight (iTOF), starting from phase delay measurement of a sinusoidally modulated light. The system acquires live movie with a frame rate up to 50frame/s in a range distance between 10 cm up to 7.5 m.

  7. Large distance 3D imaging of hidden objects

    NASA Astrophysics Data System (ADS)

    Rozban, Daniel; Aharon Akram, Avihai; Kopeika, N. S.; Abramovich, A.; Levanon, Assaf

    2014-06-01

    Imaging systems in millimeter waves are required for applications in medicine, communications, homeland security, and space technology. This is because there is no known ionization hazard for biological tissue, and atmospheric attenuation in this range of the spectrum is low compared to that of infrared and optical rays. The lack of an inexpensive room temperature detector makes it difficult to give a suitable real time implement for the above applications. A 3D MMW imaging system based on chirp radar was studied previously using a scanning imaging system of a single detector. The system presented here proposes to employ a chirp radar method with Glow Discharge Detector (GDD) Focal Plane Array (FPA of plasma based detectors) using heterodyne detection. The intensity at each pixel in the GDD FPA yields the usual 2D image. The value of the I-F frequency yields the range information at each pixel. This will enable 3D MMW imaging. In this work we experimentally demonstrate the feasibility of implementing an imaging system based on radar principles and FPA of inexpensive detectors. This imaging system is shown to be capable of imaging objects from distances of at least 10 meters.

  8. Interactive 2D to 3D stereoscopic image synthesis

    NASA Astrophysics Data System (ADS)

    Feldman, Mark H.; Lipton, Lenny

    2005-03-01

    Advances in stereoscopic display technologies, graphic card devices, and digital imaging algorithms have opened up new possibilities in synthesizing stereoscopic images. The power of today"s DirectX/OpenGL optimized graphics cards together with adapting new and creative imaging tools found in software products such as Adobe Photoshop, provide a powerful environment for converting planar drawings and photographs into stereoscopic images. The basis for such a creative process is the focus of this paper. This article presents a novel technique, which uses advanced imaging features and custom Windows-based software that utilizes the Direct X 9 API to provide the user with an interactive stereo image synthesizer. By creating an accurate and interactive world scene with moveable and flexible depth map altered textured surfaces, perspective stereoscopic cameras with both visible frustums and zero parallax planes, a user can precisely model a virtual three-dimensional representation of a real-world scene. Current versions of Adobe Photoshop provide a creative user with a rich assortment of tools needed to highlight elements of a 2D image, simulate hidden areas, and creatively shape them for a 3D scene representation. The technique described has been implemented as a Photoshop plug-in and thus allows for a seamless transition of these 2D image elements into 3D surfaces, which are subsequently rendered to create stereoscopic views.

  9. Automated reconstruction of 3D scenes from sequences of images

    NASA Astrophysics Data System (ADS)

    Pollefeys, M.; Koch, R.; Vergauwen, M.; Van Gool, L.

    Modelling of 3D objects from image sequences is a challenging problem and has been an important research topic in the areas of photogrammetry and computer vision for many years. In this paper, a system is presented which automatically extracts a textured 3D surface model from a sequence of images of a scene. The system can deal with unknown camera settings. In addition, the parameters of this camera are allowed to change during acquisition (e.g., by zooming or focusing). No prior knowledge about the scene is necessary to build the 3D models. Therefore, this system offers a high degree of flexibility. The system is based on state-of-the-art algorithms recently developed in computer vision. The 3D modelling task is decomposed into a number of successive steps. Gradually, more knowledge of the scene and the camera setup is retrieved. At this point, the obtained accuracy is not yet at the level required for most metrology applications, but the visual quality is very convincing. This system has been applied to a number of applications in archaeology. The Roman site of Sagalassos (southwest Turkey) was used as a test case to illustrate the potential of this new approach.

  10. 3D imaging of the mesospheric emissive layer

    NASA Astrophysics Data System (ADS)

    Nadjib Kouahla, Mohamed; Faivre, Michael; Moreels, Guy; Clairemidi, Jacques; Mougin-Sisini, Davy; Meriwether, John W.; Lehmacher, Gerald A.; Vidal, Erick; Veliz, Oskar

    A new and original stereo-imaging method is introduced to measure the altitude of the OH airglow layer and provide a 3D map of the altitude of the layer centroid. Near-IR photographs of the layer are taken at two sites distant of 645 km. Each photograph is processed in order to invert the perspective effect and provide a satellite-type view of the layer. When superposed, the two views present a common diamond-shaped area. Pairs of matched points that correspond to a physical emissive point in the common area are identified in calculating a normalized crosscorrelation coefficient. This method is suitable for obtaining 3D representations in the case of low-contrast objects. An observational campaign was conducted in July 2006 in Peru. The images were taken simultaneously at Cerro Cosmos (12° 09' 08.2" S, 75° 33' 49.3" W, altitude 4630 m) close to Huancayo and Cerro Verde Tellolo (16° 33' 17.6" S, 71° 39' 59.4" W, altitude 2330 m) close to Arequipa. 3D maps of the layer surface are retrieved. They are compared with pseudo-relief intensity maps of the same region. The mean altitude of the emission barycenter is located at 87.1 km on July 26 and 89.5 km on July 28. Comparable relief wavy features appear in the 3D and intensity maps.

  11. Combined registration of 3D tibia and femur implant models in 3D magnetic resonance images

    NASA Astrophysics Data System (ADS)

    Englmeier, Karl-Hans; Siebert, Markus; von Eisenhart-Rothe, Ruediger; Graichen, Heiko

    2008-03-01

    The most frequent reasons for revision of total knee arthroplasty are loosening and abnormal axial alignment leading to an unphysiological kinematic of the knee implant. To get an idea about the postoperative kinematic of the implant, it is essential to determine the position and orientation of the tibial and femoral prosthesis. Therefore we developed a registration method for fitting 3D CAD-models of knee joint prostheses into an 3D MR image. This rigid registration is the basis for a quantitative analysis of the kinematics of knee implants. Firstly the surface data of the prostheses models are converted into a voxel representation; a recursive algorithm determines all boundary voxels of the original triangular surface data. Secondly an initial preconfiguration of the implants by the user is still necessary for the following step: The user has to perform a rough preconfiguration of both remaining prostheses models, so that the fine matching process gets a reasonable starting point. After that an automated gradient-based fine matching process determines the best absolute position and orientation: This iterative process changes all 6 parameters (3 rotational- and 3 translational parameters) of a model by a minimal amount until a maximum value of the matching function is reached. To examine the spread of the final solutions of the registration, the interobserver variability was measured in a group of testers. This variability, calculated by the relative standard deviation, improved from about 50% (pure manual registration) to 0.5% (rough manual preconfiguration and subsequent fine registration with the automatic fine matching process).

  12. Linear tracking for 3-D medical ultrasound imaging.

    PubMed

    Huang, Qing-Hua; Yang, Zhao; Hu, Wei; Jin, Lian-Wen; Wei, Gang; Li, Xuelong

    2013-12-01

    As the clinical application grows, there is a rapid technical development of 3-D ultrasound imaging. Compared with 2-D ultrasound imaging, 3-D ultrasound imaging can provide improved qualitative and quantitative information for various clinical applications. In this paper, we proposed a novel tracking method for a freehand 3-D ultrasound imaging system with improved portability, reduced degree of freedom, and cost. We designed a sliding track with a linear position sensor attached, and it transmitted positional data via a wireless communication module based on Bluetooth, resulting in a wireless spatial tracking modality. A traditional 2-D ultrasound probe fixed to the position sensor on the sliding track was used to obtain real-time B-scans, and the positions of the B-scans were simultaneously acquired when moving the probe along the track in a freehand manner. In the experiments, the proposed method was applied to ultrasound phantoms and real human tissues. The results demonstrated that the new system outperformed a previously developed freehand system based on a traditional six-degree-of-freedom spatial sensor in phantom and in vivo studies, indicating its merit in clinical applications for human tissues and organs.

  13. 3D imaging: how to achieve highest accuracy

    NASA Astrophysics Data System (ADS)

    Luhmann, Thomas

    2011-07-01

    The generation of 3D information from images is a key technology in many different areas, e.g. in 3D modeling and representation of architectural or heritage objects, in human body motion tracking and scanning, in 3D scene analysis of traffic scenes, in industrial applications and many more. The basic concepts rely on mathematical representations of central perspective viewing as they are widely known from photogrammetry or computer vision approaches. The objectives of these methods differ, more or less, from high precision and well-structured measurements in (industrial) photogrammetry to fully-automated non-structured applications in computer vision. Accuracy and precision is a critical issue for the 3D measurement of industrial, engineering or medical objects. As state of the art, photogrammetric multi-view measurements achieve relative precisions in the order of 1:100000 to 1:200000, and relative accuracies with respect to retraceable lengths in the order of 1:50000 to 1:100000 of the largest object diameter. In order to obtain these figures a number of influencing parameters have to be optimized. These are, besides others: physical representation of object surface (targets, texture), illumination and light sources, imaging sensors, cameras and lenses, calibration strategies (camera model), orientation strategies (bundle adjustment), image processing of homologue features (target measurement, stereo and multi-image matching), representation of object or workpiece coordinate systems and object scale. The paper discusses the above mentioned parameters and offers strategies for obtaining highest accuracy in object space. Practical examples of high-quality stereo camera measurements and multi-image applications are used to prove the relevance of high accuracy in different applications, ranging from medical navigation to static and dynamic industrial measurements. In addition, standards for accuracy verifications are presented and demonstrated by practical examples

  14. Image Appraisal for 2D and 3D Electromagnetic Inversion

    SciTech Connect

    Alumbaugh, D.L.; Newman, G.A.

    1999-01-28

    Linearized methods are presented for appraising image resolution and parameter accuracy in images generated with two and three dimensional non-linear electromagnetic inversion schemes. When direct matrix inversion is employed, the model resolution and posterior model covariance matrices can be directly calculated. A method to examine how the horizontal and vertical resolution varies spatially within the electromagnetic property image is developed by examining the columns of the model resolution matrix. Plotting the square root of the diagonal of the model covariance matrix yields an estimate of how errors in the inversion process such as data noise and incorrect a priori assumptions about the imaged model map into parameter error. This type of image is shown to be useful in analyzing spatial variations in the image sensitivity to the data. A method is analyzed for statistically estimating the model covariance matrix when the conjugate gradient method is employed rather than a direct inversion technique (for example in 3D inversion). A method for calculating individual columns of the model resolution matrix using the conjugate gradient method is also developed. Examples of the image analysis techniques are provided on 2D and 3D synthetic cross well EM data sets, as well as a field data set collected at the Lost Hills Oil Field in Central California.

  15. Validation of 3D ultrasound: CT registration of prostate images

    NASA Astrophysics Data System (ADS)

    Firle, Evelyn A.; Wesarg, Stefan; Karangelis, Grigoris; Dold, Christian

    2003-05-01

    All over the world 20% of men are expected to develop prostate cancer sometime in his life. In addition to surgery - being the traditional treatment for cancer - the radiation treatment is getting more popular. The most interesting radiation treatment regarding prostate cancer is Brachytherapy radiation procedure. For the safe delivery of that therapy imaging is critically important. In several cases where a CT device is available a combination of the information provided by CT and 3D Ultrasound (U/S) images offers advantages in recognizing the borders of the lesion and delineating the region of treatment. For these applications the CT and U/S scans should be registered and fused in a multi-modal dataset. Purpose of the present development is a registration tool (registration, fusion and validation) for available CT volumes with 3D U/S images of the same anatomical region, i.e. the prostate. The combination of these two imaging modalities interlinks the advantages of the high-resolution CT imaging and low cost real-time U/S imaging and offers a multi-modality imaging environment for further target and anatomy delineation. This tool has been integrated into the visualization software "InViVo" which has been developed over several years in Fraunhofer IGD in Darmstadt.

  16. Exploiting the self-similarity in ERP images by nonlocal means for single-trial denoising.

    PubMed

    Strauss, Daniel J; Teuber, Tanja; Steidl, Gabriele; Corona-Strauss, Farah I

    2013-07-01

    Event related potentials (ERPs) represent a noninvasive and widely available means to analyze neural correlates of sensory and cognitive processing. Recent developments in neural and cognitive engineering proposed completely new application fields of this well-established measurement technique when using an advanced single-trial processing. We have recently shown that 2-D diffusion filtering methods from image processing can be used for the denoising of ERP single-trials in matrix representations, also called ERP images. In contrast to conventional 1-D transient ERP denoising techniques, the 2-D restoration of ERP images allows for an integration of regularities over multiple stimulations into the denoising process. Advanced anisotropic image restoration methods may require directional information for the ERP denoising process. This is especially true if there is a lack of a priori knowledge about possible traces in ERP images. However due to the use of event related experimental paradigms, ERP images are characterized by a high degree of self-similarity over the individual trials. In this paper, we propose the simple and easy to apply nonlocal means method for ERP image denoising in order to exploit this self-similarity rather than focusing on the edge-based extraction of directional information. Using measured and simulated ERP data, we compare our method to conventional approaches in ERP denoising. It is concluded that the self-similarity in ERP images can be exploited for single-trial ERP denoising by the proposed approach. This method might be promising for a variety of evoked and event-related potential applications, including nonstationary paradigms such as changing exogeneous stimulus characteristics or endogenous states during the experiment. As presented, the proposed approach is for the a posteriori denoising of single-trial sequences.

  17. Application of improved homogeneity similarity-based denoising in optical coherence tomography retinal images.

    PubMed

    Chen, Qiang; de Sisternes, Luis; Leng, Theodore; Rubin, Daniel L

    2015-06-01

    Image denoising is a fundamental preprocessing step of image processing in many applications developed for optical coherence tomography (OCT) retinal imaging--a high-resolution modality for evaluating disease in the eye. To make a homogeneity similarity-based image denoising method more suitable for OCT image removal, we improve it by considering the noise and retinal characteristics of OCT images in two respects: (1) median filtering preprocessing is used to make the noise distribution of OCT images more suitable for patch-based methods; (2) a rectangle neighborhood and region restriction are adopted to accommodate the horizontal stretching of retinal structures when observed in OCT images. As a performance measurement of the proposed technique, we tested the method on real and synthetic noisy retinal OCT images and compared the results with other well-known spatial denoising methods, including bilateral filtering, five partial differential equation (PDE)-based methods, and three patch-based methods. Our results indicate that our proposed method seems suitable for retinal OCT imaging denoising, and that, in general, patch-based methods can achieve better visual denoising results than point-based methods in this type of imaging, because the image patch can better represent the structured information in the images than a single pixel. However, the time complexity of the patch-based methods is substantially higher than that of the others.

  18. Getting in touch--3D printing in forensic imaging.

    PubMed

    Ebert, Lars Chr; Thali, Michael J; Ross, Steffen

    2011-09-10

    With the increasing use of medical imaging in forensics, as well as the technological advances in rapid prototyping, we suggest combining these techniques to generate displays of forensic findings. We used computed tomography (CT), CT angiography, magnetic resonance imaging (MRI) and surface scanning with photogrammetry in conjunction with segmentation techniques to generate 3D polygon meshes. Based on these data sets, a 3D printer created colored models of the anatomical structures. Using this technique, we could create models of bone fractures, vessels, cardiac infarctions, ruptured organs as well as bitemark wounds. The final models are anatomically accurate, fully colored representations of bones, vessels and soft tissue, and they demonstrate radiologically visible pathologies. The models are more easily understood by laypersons than volume rendering or 2D reconstructions. Therefore, they are suitable for presentations in courtrooms and for educational purposes.

  19. Automated Recognition of 3D Features in GPIR Images

    NASA Technical Reports Server (NTRS)

    Park, Han; Stough, Timothy; Fijany, Amir

    2007-01-01

    A method of automated recognition of three-dimensional (3D) features in images generated by ground-penetrating imaging radar (GPIR) is undergoing development. GPIR 3D images can be analyzed to detect and identify such subsurface features as pipes and other utility conduits. Until now, much of the analysis of GPIR images has been performed manually by expert operators who must visually identify and track each feature. The present method is intended to satisfy a need for more efficient and accurate analysis by means of algorithms that can automatically identify and track subsurface features, with minimal supervision by human operators. In this method, data from multiple sources (for example, data on different features extracted by different algorithms) are fused together for identifying subsurface objects. The algorithms of this method can be classified in several different ways. In one classification, the algorithms fall into three classes: (1) image-processing algorithms, (2) feature- extraction algorithms, and (3) a multiaxis data-fusion/pattern-recognition algorithm that includes a combination of machine-learning, pattern-recognition, and object-linking algorithms. The image-processing class includes preprocessing algorithms for reducing noise and enhancing target features for pattern recognition. The feature-extraction algorithms operate on preprocessed data to extract such specific features in images as two-dimensional (2D) slices of a pipe. Then the multiaxis data-fusion/ pattern-recognition algorithm identifies, classifies, and reconstructs 3D objects from the extracted features. In this process, multiple 2D features extracted by use of different algorithms and representing views along different directions are used to identify and reconstruct 3D objects. In object linking, which is an essential part of this process, features identified in successive 2D slices and located within a threshold radius of identical features in adjacent slices are linked in a

  20. 3D scene reconstruction based on 3D laser point cloud combining UAV images

    NASA Astrophysics Data System (ADS)

    Liu, Huiyun; Yan, Yangyang; Zhang, Xitong; Wu, Zhenzhen

    2016-03-01

    It is a big challenge capturing and modeling 3D information of the built environment. A number of techniques and technologies are now in use. These include GPS, and photogrammetric application and also remote sensing applications. The experiment uses multi-source data fusion technology for 3D scene reconstruction based on the principle of 3D laser scanning technology, which uses the laser point cloud data as the basis and Digital Ortho-photo Map as an auxiliary, uses 3DsMAX software as a basic tool for building three-dimensional scene reconstruction. The article includes data acquisition, data preprocessing, 3D scene construction. The results show that the 3D scene has better truthfulness, and the accuracy of the scene meet the need of 3D scene construction.

  1. Image analysis for denoising full-field frequency-domain fluorescence lifetime images.

    PubMed

    Spring, B Q; Clegg, R M

    2009-08-01

    Video-rate fluorescence lifetime-resolved imaging microscopy (FLIM) is a quantitative imaging technique for measuring dynamic processes in biological specimens. FLIM offers valuable information in addition to simple fluorescence intensity imaging; for instance, the fluorescence lifetime is sensitive to the microenvironment of the fluorophore allowing reliable differentiation between concentration differences and dynamic quenching. Homodyne FLIM is a full-field frequency-domain technique for imaging fluorescence lifetimes at every pixel of a fluorescence image simultaneously. If a single modulation frequency is used, video-rate image acquisition is possible. Homodyne FLIM uses a gain-modulated image intensified charge-coupled device (ICCD) detector, which unfortunately is a major contribution to the noise of the measurement. Here we introduce image analysis for denoising homodyne FLIM data. The denoising routine is fast, improves the extraction of the fluorescence lifetime value(s) and increases the sensitivity and fluorescence lifetime resolving power of the FLIM instrument. The spatial resolution (especially the high spatial frequencies not related to noise) of the FLIM image is preserved, because the denoising routine does not blur or smooth the image. By eliminating the random noise known to be specific to photon noise and from the intensifier amplification, the fidelity of the spatial resolution is improved. The polar plot projection, a rapid FLIM analysis method, is used to demonstrate the effectiveness of the denoising routine with exemplary data from both physical and complex biological samples. We also suggest broader impacts of the image analysis for other fluorescence microscopy techniques (e.g. super-resolution imaging).

  2. Joint calibration of 3D resist image and CDSEM

    NASA Astrophysics Data System (ADS)

    Chou, C. S.; He, Y. Y.; Tang, Y. P.; Chang, Y. T.; Huang, W. C.; Liu, R. G.; Gau, T. S.

    2013-04-01

    Traditionally, an optical proximity correction model is to evaluate the resist image at a specific depth within the photoresist and then extract the resist contours from the image. Calibration is generally implemented by comparing resist contours with the critical dimensions (CD). The wafer CD is usually collected by a scanning electron microscope (SEM), which evaluates the CD based on some criterion that is a function of gray level, differential signal, threshold or other parameters set by the SEM. However, the criterion does not reveal which depth the CD is obtained at. This depth inconsistency between modeling and SEM makes the model calibration difficult for low k1 images. In this paper, the vertical resist profile is obtained by modifying the model from planar (2D) to quasi-3D approach and comparing the CD from this new model with SEM CD. For this quasi-3D model, the photoresist diffusion along the depth of the resist is considered and the 3D photoresist contours are evaluated. The performance of this new model is studied and is better than the 2D model.

  3. Digital acquisition system for high-speed 3-D imaging

    NASA Astrophysics Data System (ADS)

    Yafuso, Eiji

    1997-11-01

    High-speed digital three-dimensional (3-D) imagery is possible using multiple independent charge-coupled device (CCD) cameras with sequentially triggered acquisition and individual field storage capability. The system described here utilizes sixteen independent cameras, providing versatility in configuration and image acquisition. By aligning the cameras in nearly coincident lines-of-sight, a sixteen frame two-dimensional (2-D) sequence can be captured. The delays can be individually adjusted lo yield a greater number of acquired frames during the more rapid segments of the event. Additionally, individual integration periods may be adjusted to ensure adequate radiometric response while minimizing image blur. An alternative alignment and triggering scheme arranges the cameras into two angularly separated banks of eight cameras each. By simultaneously triggering correlated stereo pairs, an eight-frame sequence of stereo images may be captured. In the first alignment scheme the camera lines-of-sight cannot be made precisely coincident. Thus representation of the data as a monocular sequence introduces the issue of independent camera coordinate registration with the real scene. This issue arises more significantly using the stereo pair method to reconstruct quantitative 3-D spatial information of the event as a function of time. The principal development here will be the derivation and evaluation of a solution transform and its inverse for the digital data which will yield a 3-D spatial mapping as a function of time.

  4. 3D tongue motion from tagged and cine MR images.

    PubMed

    Xing, Fangxu; Woo, Jonghye; Murano, Emi Z; Lee, Junghoon; Stone, Maureen; Prince, Jerry L

    2013-01-01

    Understanding the deformation of the tongue during human speech is important for head and neck surgeons and speech and language scientists. Tagged magnetic resonance (MR) imaging can be used to image 2D motion, and data from multiple image planes can be combined via post-processing to yield estimates of 3D motion. However, lacking boundary information, this approach suffers from inaccurate estimates near the tongue surface. This paper describes a method that combines two sources of information to yield improved estimation of 3D tongue motion. The method uses the harmonic phase (HARP) algorithm to extract motion from tags and diffeomorphic demons to provide surface deformation. It then uses an incompressible deformation estimation algorithm to incorporate both sources of displacement information to form an estimate of the 3D whole tongue motion. Experimental results show that use of combined information improves motion estimation near the tongue surface, a problem that has previously been reported as problematic in HARP analysis, while preserving accurate internal motion estimates. Results on both normal and abnormal tongue motions are shown.

  5. Discrete Method of Images for 3D Radio Propagation Modeling

    NASA Astrophysics Data System (ADS)

    Novak, Roman

    2016-09-01

    Discretization by rasterization is introduced into the method of images (MI) in the context of 3D deterministic radio propagation modeling as a way to exploit spatial coherence of electromagnetic propagation for fine-grained parallelism. Traditional algebraic treatment of bounding regions and surfaces is replaced by computer graphics rendering of 3D reflections and double refractions while building the image tree. The visibility of reception points and surfaces is also resolved by shader programs. The proposed rasterization is shown to be of comparable run time to that of the fundamentally parallel shooting and bouncing rays. The rasterization does not affect the signal evaluation backtracking step, thus preserving its advantage over the brute force ray-tracing methods in terms of accuracy. Moreover, the rendering resolution may be scaled back for a given level of scenario detail with only marginal impact on the image tree size. This allows selection of scene optimized execution parameters for faster execution, giving the method a competitive edge. The proposed variant of MI can be run on any GPU that supports real-time 3D graphics.

  6. Validation of image processing tools for 3-D fluorescence microscopy.

    PubMed

    Dieterlen, Alain; Xu, Chengqi; Gramain, Marie-Pierre; Haeberlé, Olivier; Colicchio, Bruno; Cudel, Christophe; Jacquey, Serge; Ginglinger, Emanuelle; Jung, Georges; Jeandidier, Eric

    2002-04-01

    3-D optical fluorescent microscopy becomes nowadays an efficient tool for volumic investigation of living biological samples. Using optical sectioning technique, a stack of 2-D images is obtained. However, due to the nature of the system optical transfer function and non-optimal experimental conditions, acquired raw data usually suffer from some distortions. In order to carry out biological analysis, raw data have to be restored by deconvolution. The system identification by the point-spread function is useful to obtain the knowledge of the actual system and experimental parameters, which is necessary to restore raw data. It is furthermore helpful to precise the experimental protocol. In order to facilitate the use of image processing techniques, a multi-platform-compatible software package called VIEW3D has been developed. It integrates a set of tools for the analysis of fluorescence images from 3-D wide-field or confocal microscopy. A number of regularisation parameters for data restoration are determined automatically. Common geometrical measurements and morphological descriptors of fluorescent sites are also implemented to facilitate the characterisation of biological samples. An example of this method concerning cytogenetics is presented.

  7. Automated spatial alignment of 3D torso images.

    PubMed

    Bose, Arijit; Shah, Shishir K; Reece, Gregory P; Crosby, Melissa A; Beahm, Elisabeth K; Fingeret, Michelle C; Markey, Mia K; Merchant, Fatima A

    2011-01-01

    This paper describes an algorithm for automated spatial alignment of three-dimensional (3D) surface images in order to achieve a pre-defined orientation. Surface images of the torso are acquired from breast cancer patients undergoing reconstructive surgery to facilitate objective evaluation of breast morphology pre-operatively (for treatment planning) and/or post-operatively (for outcome assessment). Based on the viewing angle of the multiple cameras used for stereophotography, the orientation of the acquired torso in the images may vary from the normal upright position. Consequently, when translating this data into a standard 3D framework for visualization and analysis, the co-ordinate geometry differs from the upright position making robust and standardized comparison of images impractical. Moreover, manual manipulation and navigation of images to the desired upright position is subject to user bias. Automating the process of alignment and orientation removes operator bias and permits robust and repeatable adjustment of surface images to a pre-defined or desired spatial geometry.

  8. Fast 3D fluid registration of brain magnetic resonance images

    NASA Astrophysics Data System (ADS)

    Leporé, Natasha; Chou, Yi-Yu; Lopez, Oscar L.; Aizenstein, Howard J.; Becker, James T.; Toga, Arthur W.; Thompson, Paul M.

    2008-03-01

    Fluid registration is widely used in medical imaging to track anatomical changes, to correct image distortions, and to integrate multi-modality data. Fluid mappings guarantee that the template image deforms smoothly into the target, without tearing or folding, even when large deformations are required for accurate matching. Here we implemented an intensity-based fluid registration algorithm, accelerated by using a filter designed by Bro-Nielsen and Gramkow. We validated the algorithm on 2D and 3D geometric phantoms using the mean square difference between the final registered image and target as a measure of the accuracy of the registration. In tests on phantom images with different levels of overlap, varying amounts of Gaussian noise, and different intensity gradients, the fluid method outperformed a more commonly used elastic registration method, both in terms of accuracy and in avoiding topological errors during deformation. We also studied the effect of varying the viscosity coefficients in the viscous fluid equation, to optimize registration accuracy. Finally, we applied the fluid registration algorithm to a dataset of 2D binary corpus callosum images and 3D volumetric brain MRIs from 14 healthy individuals to assess its accuracy and robustness.

  9. Integral imaging based 3D display of holographic data.

    PubMed

    Yöntem, Ali Özgür; Onural, Levent

    2012-10-22

    We propose a method and present applications of this method that converts a diffraction pattern into an elemental image set in order to display them on an integral imaging based display setup. We generate elemental images based on diffraction calculations as an alternative to commonly used ray tracing methods. Ray tracing methods do not accommodate the interference and diffraction phenomena. Our proposed method enables us to obtain elemental images from a holographic recording of a 3D object/scene. The diffraction pattern can be either numerically generated data or digitally acquired optical data. The method shows the connection between a hologram (diffraction pattern) and an elemental image set of the same 3D object. We showed three examples, one of which is the digitally captured optical diffraction tomography data of an epithelium cell. We obtained optical reconstructions with our integral imaging display setup where we used a digital lenslet array. We also obtained numerical reconstructions, again by using the diffraction calculations, for comparison. The digital and optical reconstruction results are in good agreement.

  10. A hybrid framework for 3D medical image segmentation.

    PubMed

    Chen, Ting; Metaxas, Dimitris

    2005-12-01

    In this paper we propose a novel hybrid 3D segmentation framework which combines Gibbs models, marching cubes and deformable models. In the framework, first we construct a new Gibbs model whose energy function is defined on a high order clique system. The new model includes both region and boundary information during segmentation. Next we improve the original marching cubes method to construct 3D meshes from Gibbs models' output. The 3D mesh serves as the initial geometry of the deformable model. Then we deform the deformable model using external image forces so that the model converges to the object surface. We run the Gibbs model and the deformable model recursively by updating the Gibbs model's parameters using the region and boundary information in the deformable model segmentation result. In our approach, the hybrid combination of region-based methods and boundary-based methods results in improved segmentations of complex structures. The benefit of the methodology is that it produces high quality segmentations of 3D structures using little prior information and minimal user intervention. The modules in this segmentation methodology are developed within the context of the Insight ToolKit (ITK). We present experimental segmentation results of brain tumors and evaluate our method by comparing experimental results with expert manual segmentations. The evaluation results show that the methodology achieves high quality segmentation results with computational efficiency. We also present segmentation results of other clinical objects to illustrate the strength of the methodology as a generic segmentation framework.

  11. Pavement cracking measurements using 3D laser-scan images

    NASA Astrophysics Data System (ADS)

    Ouyang, W.; Xu, B.

    2013-10-01

    Pavement condition surveying is vital for pavement maintenance programs that ensure ride quality and traffic safety. This paper first introduces an automated pavement inspection system which uses a three-dimensional (3D) camera and a structured laser light to acquire dense transverse profiles of a pavement lane surface when it carries a moving vehicle. After the calibration, the 3D system can yield a depth resolution of 0.5 mm and a transverse resolution of 1.56 mm pixel-1 at 1.4 m camera height from the ground. The scanning rate of the camera can be set to its maximum at 5000 lines s-1, allowing the density of scanned profiles to vary with the vehicle's speed. The paper then illustrates the algorithms that utilize 3D information to detect pavement distress, such as transverse, longitudinal and alligator cracking, and presents the field tests on the system's repeatability when scanning a sample pavement in multiple runs at the same vehicle speed, at different vehicle speeds and under different weather conditions. The results show that this dedicated 3D system can capture accurate pavement images that detail surface distress, and obtain consistent crack measurements in repeated tests and under different driving and lighting conditions.

  12. Objective breast symmetry evaluation using 3-D surface imaging.

    PubMed

    Eder, Maximilian; Waldenfels, Fee V; Swobodnik, Alexandra; Klöppel, Markus; Pape, Ann-Kathrin; Schuster, Tibor; Raith, Stefan; Kitzler, Elena; Papadopulos, Nikolaos A; Machens, Hans-Günther; Kovacs, Laszlo

    2012-04-01

    This study develops an objective breast symmetry evaluation using 3-D surface imaging (Konica-Minolta V910(®) scanner) by superimposing the mirrored left breast over the right and objectively determining the mean 3-D contour difference between the 2 breast surfaces. 3 observers analyzed the evaluation protocol precision using 2 dummy models (n = 60), 10 test subjects (n = 300), clinically tested it on 30 patients (n = 900) and compared it to established 2-D measurements on 23 breast reconstructive patients using the BCCT.core software (n = 690). Mean 3-D evaluation precision, expressed as the coefficient of variation (VC), was 3.54 ± 0.18 for all human subjects without significant intra- and inter-observer differences (p > 0.05). The 3-D breast symmetry evaluation is observer independent, significantly more precise (p < 0.001) than the BCCT.core software (VC = 6.92 ± 0.88) and may play a part in an objective surgical outcome analysis after incorporation into clinical practice.

  13. Hybrid regularizers-based adaptive anisotropic diffusion for image denoising.

    PubMed

    Liu, Kui; Tan, Jieqing; Ai, Liefu

    2016-01-01

    To eliminate the staircasing effect for total variation filter and synchronously avoid the edges blurring for fourth-order PDE filter, a hybrid regularizers-based adaptive anisotropic diffusion is proposed for image denoising. In the proposed model, the [Formula: see text]-norm is considered as the fidelity term and the regularization term is composed of a total variation regularization and a fourth-order filter. The two filters can be adaptively selected according to the diffusion function. When the pixels locate at the edges, the total variation filter is selected to filter the image, which can preserve the edges. When the pixels belong to the flat regions, the fourth-order filter is adopted to smooth the image, which can eliminate the staircase artifacts. In addition, the split Bregman and relaxation approach are employed in our numerical algorithm to speed up the computation. Experimental results demonstrate that our proposed model outperforms the state-of-the-art models cited in the paper in both the qualitative and quantitative evaluations.

  14. Virtual image display as a backlight for 3D.

    PubMed

    Travis, Adrian; MacCrann, Niall; Emerton, Neil; Kollin, Joel; Georgiou, Andreas; Lanier, Jaron; Bathiche, Stephen

    2013-07-29

    We describe a device which has the potential to be used both as a virtual image display and as a backlight. The pupil of the emitted light fills the device approximately to its periphery and the collimated emission can be scanned both horizontally and vertically in the manner needed to illuminate an eye in any position. The aim is to reduce the power needed to illuminate a liquid crystal panel but also to enable a smooth transition from 3D to a virtual image as the user nears the screen.

  15. Automatic structural matching of 3D image data

    NASA Astrophysics Data System (ADS)

    Ponomarev, Svjatoslav; Lutsiv, Vadim; Malyshev, Igor

    2015-10-01

    A new image matching technique is described. It is implemented as an object-independent hierarchical structural juxtaposition algorithm based on an alphabet of simple object-independent contour structural elements. The structural matching applied implements an optimized method of walking through a truncated tree of all possible juxtapositions of two sets of structural elements. The algorithm was initially developed for dealing with 2D images such as the aerospace photographs, and it turned out to be sufficiently robust and reliable for matching successfully the pictures of natural landscapes taken in differing seasons from differing aspect angles by differing sensors (the visible optical, IR, and SAR pictures, as well as the depth maps and geographical vector-type maps). At present (in the reported version), the algorithm is enhanced based on additional use of information on third spatial coordinates of observed points of object surfaces. Thus, it is now capable of matching the images of 3D scenes in the tasks of automatic navigation of extremely low flying unmanned vehicles or autonomous terrestrial robots. The basic principles of 3D structural description and matching of images are described, and the examples of image matching are presented.

  16. Underwater 3d Modeling: Image Enhancement and Point Cloud Filtering

    NASA Astrophysics Data System (ADS)

    Sarakinou, I.; Papadimitriou, K.; Georgoula, O.; Patias, P.

    2016-06-01

    This paper examines the results of image enhancement and point cloud filtering on the visual and geometric quality of 3D models for the representation of underwater features. Specifically it evaluates the combination of effects from the manual editing of images' radiometry (captured at shallow depths) and the selection of parameters for point cloud definition and mesh building (processed in 3D modeling software). Such datasets, are usually collected by divers, handled by scientists and used for geovisualization purposes. In the presented study, have been created 3D models from three sets of images (seafloor, part of a wreck and a small boat's wreck) captured at three different depths (3.5m, 10m and 14m respectively). Four models have been created from the first dataset (seafloor) in order to evaluate the results from the application of image enhancement techniques and point cloud filtering. The main process for this preliminary study included a) the definition of parameters for the point cloud filtering and the creation of a reference model, b) the radiometric editing of images, followed by the creation of three improved models and c) the assessment of results by comparing the visual and the geometric quality of improved models versus the reference one. Finally, the selected technique is tested on two other data sets in order to examine its appropriateness for different depths (at 10m and 14m) and different objects (part of a wreck and a small boat's wreck) in the context of an ongoing research in the Laboratory of Photogrammetry and Remote Sensing.

  17. An Optimal Partial Differential Equations-based Stopping Criterion for Medical Image Denoising.

    PubMed

    Khanian, Maryam; Feizi, Awat; Davari, Ali

    2014-01-01

    Improving the quality of medical images at pre- and post-surgery operations are necessary for beginning and speeding up the recovery process. Partial differential equations-based models have become a powerful and well-known tool in different areas of image processing such as denoising, multiscale image analysis, edge detection and other fields of image processing and computer vision. In this paper, an algorithm for medical image denoising using anisotropic diffusion filter with a convenient stopping criterion is presented. In this regard, the current paper introduces two strategies: utilizing the efficient explicit method due to its advantages with presenting impressive software technique to effectively solve the anisotropic diffusion filter which is mathematically unstable, proposing an automatic stopping criterion, that takes into consideration just input image, as opposed to other stopping criteria, besides the quality of denoised image, easiness and time. Various medical images are examined to confirm the claim.

  18. Feature detection on 3D images of dental imprints

    NASA Astrophysics Data System (ADS)

    Mokhtari, Marielle; Laurendeau, Denis

    1994-09-01

    A computer vision approach for the extraction of feature points on 3D images of dental imprints is presented. The position of feature points are needed for the measurement of a set of parameters for automatic diagnosis of malocclusion problems in orthodontics. The system for the acquisition of the 3D profile of the imprint, the procedure for the detection of the interstices between teeth, and the approach for the identification of the type of tooth are described, as well as the algorithm for the reconstruction of the surface of each type of tooth. A new approach for the detection of feature points, called the watershed algorithm, is described in detail. The algorithm is a two-stage procedure which tracks the position of local minima at four different scales and produces a final map of the position of the minima. Experimental results of the application of the watershed algorithm on actual 3D images of dental imprints are presented for molars, premolars and canines. The segmentation approach for the analysis of the shape of incisors is also described in detail.

  19. Quantification of thyroid volume using 3-D ultrasound imaging.

    PubMed

    Kollorz, E K; Hahn, D A; Linke, R; Goecke, T W; Hornegger, J; Kuwert, T

    2008-04-01

    Ultrasound (US) is among the most popular diagnostic techniques today. It is non-invasive, fast, comparably cheap, and does not require ionizing radiation. US is commonly used to examine the size, and structure of the thyroid gland. In clinical routine, thyroid imaging is usually performed by means of 2-D US. Conventional approaches for measuring the volume of the thyroid gland or its nodules may therefore be inaccurate due to the lack of 3-D information. This work reports a semi-automatic segmentation approach for the classification, and analysis of the thyroid gland based on 3-D US data. The images are scanned in 3-D, pre-processed, and segmented. Several pre-processing methods, and an extension of a commonly used geodesic active contour level set formulation are discussed in detail. The results obtained by this approach are compared to manual interactive segmentations by a medical expert in five representative patients. Our work proposes a novel framework for the volumetric quantification of thyroid gland lobes, which may also be expanded to other parenchymatous organs.

  20. 3D imaging of biological specimen using MS.

    PubMed

    Fletcher, John S

    2015-01-01

    Imaging MS can provide unique information about the distribution of native and non-native compounds in biological specimen. MALDI MS and secondary ion MS are the two most commonly applied imaging MS techniques and can provide complementary information about a sample. MALDI offers access to high mass species such as proteins while secondary ion MS can operate at higher spatial resolution and provide information about lower mass species including elemental signals. Imaging MS is not limited to two dimensions and different approaches have been developed that allow 3D molecular images to be generated of chemicals in whole organs down to single cells. Resolution in the z-dimension is often higher than in x and y, so such analysis offers the potential for probing the distribution of drug molecules and studying drug action by MS with a much higher precision - possibly even organelle level.

  1. 3D Gabor wavelet based vessel filtering of photoacoustic images.

    PubMed

    Haq, Israr Ul; Nagoaka, Ryo; Makino, Takahiro; Tabata, Takuya; Saijo, Yoshifumi

    2016-08-01

    Filtering and segmentation of vasculature is an important issue in medical imaging. The visualization of vasculature is crucial for the early diagnosis and therapy in numerous medical applications. This paper investigates the use of Gabor wavelet to enhance the effect of vasculature while eliminating the noise due to size, sensitivity and aperture of the detector in 3D Optical Resolution Photoacoustic Microscopy (OR-PAM). A detailed multi-scale analysis of wavelet filtering and Hessian based method is analyzed for extracting vessels of different sizes since the blood vessels usually vary with in a range of radii. The proposed algorithm first enhances the vasculature in the image and then tubular structures are classified by eigenvalue decomposition of the local Hessian matrix at each voxel in the image. The algorithm is tested on non-invasive experiments, which shows appreciable results to enhance vasculature in photo-acoustic images.

  2. 3D Lunar Terrain Reconstruction from Apollo Images

    NASA Technical Reports Server (NTRS)

    Broxton, Michael J.; Nefian, Ara V.; Moratto, Zachary; Kim, Taemin; Lundy, Michael; Segal, Alkeksandr V.

    2009-01-01

    Generating accurate three dimensional planetary models is becoming increasingly important as NASA plans manned missions to return to the Moon in the next decade. This paper describes a 3D surface reconstruction system called the Ames Stereo Pipeline that is designed to produce such models automatically by processing orbital stereo imagery. We discuss two important core aspects of this system: (1) refinement of satellite station positions and pose estimates through least squares bundle adjustment; and (2) a stochastic plane fitting algorithm that generalizes the Lucas-Kanade method for optimal matching between stereo pair images.. These techniques allow us to automatically produce seamless, highly accurate digital elevation models from multiple stereo image pairs while significantly reducing the influence of image noise. Our technique is demonstrated on a set of 71 high resolution scanned images from the Apollo 15 mission

  3. Phase Sensitive Cueing for 3D Objects in Overhead Images

    SciTech Connect

    Paglieroni, D W; Eppler, W G; Poland, D N

    2005-02-18

    A 3D solid model-aided object cueing method that matches phase angles of directional derivative vectors at image pixels to phase angles of vectors normal to projected model edges is described. It is intended for finding specific types of objects at arbitrary position and orientation in overhead images, independent of spatial resolution, obliqueness, acquisition conditions, and type of imaging sensor. It is shown that the phase similarity measure can be efficiently evaluated over all combinations of model position and orientation using the FFT. The highest degree of similarity over all model orientations is captured in a match surface of similarity values vs. model position. Unambiguous peaks in this surface are sorted in descending order of similarity value, and the small image thumbnails that contain them are presented to human analysts for inspection in sorted order.

  4. Evaluation of Kinect 3D Sensor for Healthcare Imaging.

    PubMed

    Pöhlmann, Stefanie T L; Harkness, Elaine F; Taylor, Christopher J; Astley, Susan M

    2016-01-01

    Microsoft Kinect is a three-dimensional (3D) sensor originally designed for gaming that has received growing interest as a cost-effective and safe device for healthcare imaging. Recent applications of Kinect in health monitoring, screening, rehabilitation, assistance systems, and intervention support are reviewed here. The suitability of available technologies for healthcare imaging applications is assessed. The performance of Kinect I, based on structured light technology, is compared with that of the more recent Kinect II, which uses time-of-flight measurement, under conditions relevant to healthcare applications. The accuracy, precision, and resolution of 3D images generated with Kinect I and Kinect II are evaluated using flat cardboard models representing different skin colors (pale, medium, and dark) at distances ranging from 0.5 to 1.2 m and measurement angles of up to 75°. Both sensors demonstrated high accuracy (majority of measurements <2 mm) and precision (mean point to plane error <2 mm) at an average resolution of at least 390 points per cm(2). Kinect I is capable of imaging at shorter measurement distances, but Kinect II enables structures angled at over 60° to be evaluated. Kinect II showed significantly higher precision and Kinect I showed significantly higher resolution (both p < 0.001). The choice of object color can influence measurement range and precision. Although Kinect is not a medical imaging device, both sensor generations show performance adequate for a range of healthcare imaging applications. Kinect I is more appropriate for short-range imaging and Kinect II is more appropriate for imaging highly curved surfaces such as the face or breast.

  5. The 3D model control of image processing

    NASA Technical Reports Server (NTRS)

    Nguyen, An H.; Stark, Lawrence

    1989-01-01

    Telerobotics studies remote control of distant robots by a human operator using supervisory or direct control. Even if the robot manipulators has vision or other senses, problems arise involving control, communications, and delay. The communication delays that may be expected with telerobots working in space stations while being controlled from an Earth lab have led to a number of experiments attempting to circumvent the problem. This delay in communication is a main motivating factor in moving from well understood instantaneous hands-on manual control to less well understood supervisory control; the ultimate step would be the realization of a fully autonomous robot. The 3-D model control plays a crucial role in resolving many conflicting image processing problems that are inherent in resolving in the bottom-up approach of most current machine vision processes. The 3-D model control approach is also capable of providing the necessary visual feedback information for both the control algorithms and for the human operator.

  6. 3D Imaging of the OH mesospheric emissive layer

    NASA Astrophysics Data System (ADS)

    Kouahla, M. N.; Moreels, G.; Faivre, M.; Clairemidi, J.; Meriwether, J. W.; Lehmacher, G. A.; Vidal, E.; Veliz, O.

    2010-01-01

    A new and original stereo imaging method is introduced to measure the altitude of the OH nightglow layer and provide a 3D perspective map of the altitude of the layer centroid. Near-IR photographs of the OH layer are taken at two sites separated by a 645 km distance. Each photograph is processed in order to provide a satellite view of the layer. When superposed, the two views present a common diamond-shaped area. Pairs of matched points that correspond to a physical emissive point in the common area are identified in calculating a normalized cross-correlation coefficient (NCC). This method is suitable for obtaining 3D representations in the case of low-contrast objects. An observational campaign was conducted in July 2006 in Peru. The images were taken simultaneously at Cerro Cosmos (12°09‧08.2″ S, 75°33‧49.3″ W, altitude 4630 m) close to Huancayo and Cerro Verde Tellolo (16°33‧17.6″ S, 71°39‧59.4″ W, altitude 2272 m) close to Arequipa. 3D maps of the layer surface were retrieved and compared with pseudo-relief intensity maps of the same region. The mean altitude of the emission barycenter is located at 86.3 km on July 26. Comparable relief wavy features appear in the 3D and intensity maps. It is shown that the vertical amplitude of the wave system varies as exp (Δz/2H) within the altitude range Δz = 83.5-88.0 km, H being the scale height. The oscillatory kinetic energy at the altitude of the OH layer is comprised between 3 × 10-4 and 5.4 × 10-4 J/m3, which is 2-3 times smaller than the values derived from partial radio wave at 52°N latitude.

  7. 3D seismic imaging on massively parallel computers

    SciTech Connect

    Womble, D.E.; Ober, C.C.; Oldfield, R.

    1997-02-01

    The ability to image complex geologies such as salt domes in the Gulf of Mexico and thrusts in mountainous regions is a key to reducing the risk and cost associated with oil and gas exploration. Imaging these structures, however, is computationally expensive. Datasets can be terabytes in size, and the processing time required for the multiple iterations needed to produce a velocity model can take months, even with the massively parallel computers available today. Some algorithms, such as 3D, finite-difference, prestack, depth migration remain beyond the capacity of production seismic processing. Massively parallel processors (MPPs) and algorithms research are the tools that will enable this project to provide new seismic processing capabilities to the oil and gas industry. The goals of this work are to (1) develop finite-difference algorithms for 3D, prestack, depth migration; (2) develop efficient computational approaches for seismic imaging and for processing terabyte datasets on massively parallel computers; and (3) develop a modular, portable, seismic imaging code.

  8. Non parametric denoising methods based on wavelets: Application to electron microscopy images in low exposure time

    SciTech Connect

    Soumia, Sid Ahmed; Messali, Zoubeida; Ouahabi, Abdeldjalil; Trepout, Sylvain E-mail: cedric.messaoudi@curie.fr Messaoudi, Cedric E-mail: cedric.messaoudi@curie.fr Marco, Sergio E-mail: cedric.messaoudi@curie.fr

    2015-01-13

    The 3D reconstruction of the Cryo-Transmission Electron Microscopy (Cryo-TEM) and Energy Filtering TEM images (EFTEM) hampered by the noisy nature of these images, so that their alignment becomes so difficult. This noise refers to the collision between the frozen hydrated biological samples and the electrons beam, where the specimen is exposed to the radiation with a high exposure time. This sensitivity to the electrons beam led specialists to obtain the specimen projection images at very low exposure time, which resulting the emergence of a new problem, an extremely low signal-to-noise ratio (SNR). This paper investigates the problem of TEM images denoising when they are acquired at very low exposure time. So, our main objective is to enhance the quality of TEM images to improve the alignment process which will in turn improve the three dimensional tomography reconstructions. We have done multiple tests on special TEM images acquired at different exposure time 0.5s, 0.2s, 0.1s and 1s (i.e. with different values of SNR)) and equipped by Golding beads for helping us in the assessment step. We herein, propose a structure to combine multiple noisy copies of the TEM images. The structure is based on four different denoising methods, to combine the multiple noisy TEM images copies. Namely, the four different methods are Soft, the Hard as Wavelet-Thresholding methods, Bilateral Filter as a non-linear technique able to maintain the edges neatly, and the Bayesian approach in the wavelet domain, in which context modeling is used to estimate the parameter for each coefficient. To ensure getting a high signal-to-noise ratio, we have guaranteed that we are using the appropriate wavelet family at the appropriate level. So we have chosen âĂIJsym8âĂİ wavelet at level 3 as the most appropriate parameter. Whereas, for the bilateral filtering many tests are done in order to determine the proper filter parameters represented by the size of the filter, the range parameter and the

  9. Non parametric denoising methods based on wavelets: Application to electron microscopy images in low exposure time

    NASA Astrophysics Data System (ADS)

    Soumia, Sid Ahmed; Messali, Zoubeida; Ouahabi, Abdeldjalil; Trepout, Sylvain; Messaoudi, Cedric; Marco, Sergio

    2015-01-01

    The 3D reconstruction of the Cryo-Transmission Electron Microscopy (Cryo-TEM) and Energy Filtering TEM images (EFTEM) hampered by the noisy nature of these images, so that their alignment becomes so difficult. This noise refers to the collision between the frozen hydrated biological samples and the electrons beam, where the specimen is exposed to the radiation with a high exposure time. This sensitivity to the electrons beam led specialists to obtain the specimen projection images at very low exposure time, which resulting the emergence of a new problem, an extremely low signal-to-noise ratio (SNR). This paper investigates the problem of TEM images denoising when they are acquired at very low exposure time. So, our main objective is to enhance the quality of TEM images to improve the alignment process which will in turn improve the three dimensional tomography reconstructions. We have done multiple tests on special TEM images acquired at different exposure time 0.5s, 0.2s, 0.1s and 1s (i.e. with different values of SNR)) and equipped by Golding beads for helping us in the assessment step. We herein, propose a structure to combine multiple noisy copies of the TEM images. The structure is based on four different denoising methods, to combine the multiple noisy TEM images copies. Namely, the four different methods are Soft, the Hard as Wavelet-Thresholding methods, Bilateral Filter as a non-linear technique able to maintain the edges neatly, and the Bayesian approach in the wavelet domain, in which context modeling is used to estimate the parameter for each coefficient. To ensure getting a high signal-to-noise ratio, we have guaranteed that we are using the appropriate wavelet family at the appropriate level. So we have chosen âĂIJsym8âĂİ wavelet at level 3 as the most appropriate parameter. Whereas, for the bilateral filtering many tests are done in order to determine the proper filter parameters represented by the size of the filter, the range parameter and the

  10. Improving 3D Wavelet-Based Compression of Hyperspectral Images

    NASA Technical Reports Server (NTRS)

    Klimesh, Matthew; Kiely, Aaron; Xie, Hua; Aranki, Nazeeh

    2009-01-01

    Two methods of increasing the effectiveness of three-dimensional (3D) wavelet-based compression of hyperspectral images have been developed. (As used here, images signifies both images and digital data representing images.) The methods are oriented toward reducing or eliminating detrimental effects of a phenomenon, referred to as spectral ringing, that is described below. In 3D wavelet-based compression, an image is represented by a multiresolution wavelet decomposition consisting of several subbands obtained by applying wavelet transforms in the two spatial dimensions corresponding to the two spatial coordinate axes of the image plane, and by applying wavelet transforms in the spectral dimension. Spectral ringing is named after the more familiar spatial ringing (spurious spatial oscillations) that can be seen parallel to and near edges in ordinary images reconstructed from compressed data. These ringing phenomena are attributable to effects of quantization. In hyperspectral data, the individual spectral bands play the role of edges, causing spurious oscillations to occur in the spectral dimension. In the absence of such corrective measures as the present two methods, spectral ringing can manifest itself as systematic biases in some reconstructed spectral bands and can reduce the effectiveness of compression of spatially-low-pass subbands. One of the two methods is denoted mean subtraction. The basic idea of this method is to subtract mean values from spatial planes of spatially low-pass subbands prior to encoding, because (a) such spatial planes often have mean values that are far from zero and (b) zero-mean data are better suited for compression by methods that are effective for subbands of two-dimensional (2D) images. In this method, after the 3D wavelet decomposition is performed, mean values are computed for and subtracted from each spatial plane of each spatially-low-pass subband. The resulting data are converted to sign-magnitude form and compressed in a

  11. 3D geometry-based quantification of colocalizations in multichannel 3D microscopy images of human soft tissue tumors.

    PubMed

    Wörz, Stefan; Sander, Petra; Pfannmöller, Martin; Rieker, Ralf J; Joos, Stefan; Mechtersheimer, Gunhild; Boukamp, Petra; Lichter, Peter; Rohr, Karl

    2010-08-01

    We introduce a new model-based approach for automatic quantification of colocalizations in multichannel 3D microscopy images. The approach uses different 3D parametric intensity models in conjunction with a model fitting scheme to localize and quantify subcellular structures with high accuracy. The central idea is to determine colocalizations between different channels based on the estimated geometry of the subcellular structures as well as to differentiate between different types of colocalizations. A statistical analysis was performed to assess the significance of the determined colocalizations. This approach was used to successfully analyze about 500 three-channel 3D microscopy images of human soft tissue tumors and controls.

  12. Multispectral Photoacoustic Imaging Artifact Removal and Denoising Using Time Series Model-Based Spectral Noise Estimation.

    PubMed

    Kazakeviciute, Agne; Ho, Chris Jun Hui; Olivo, Malini

    2016-09-01

    The aim of this study is to solve a problem of denoising and artifact removal from in vivo multispectral photoacoustic imaging when the level of noise is not known a priori. The study analyzes Wiener filtering in Fourier domain when a family of anisotropic shape filters is considered. The unknown noise and signal power spectral densities are estimated using spectral information of images and the autoregressive of the power 1 ( AR(1)) model. Edge preservation is achieved by detecting image edges in the original and the denoised image and superimposing a weighted contribution of the two edge images to the resulting denoised image. The method is tested on multispectral photoacoustic images from simulations, a tissue-mimicking phantom, as well as in vivo imaging of the mouse, with its performance compared against that of the standard Wiener filtering in Fourier domain. The results reveal better denoising and fine details preservation capabilities of the proposed method when compared to that of the standard Wiener filtering in Fourier domain, suggesting that this could be a useful denoising technique for other multispectral photoacoustic studies.

  13. Image segmentation to inspect 3-D object sizes

    NASA Astrophysics Data System (ADS)

    Hsu, Jui-Pin; Fuh, Chiou-Shann

    1996-01-01

    Object size inspection is an important task and has various applications in computer vision. For example, the automatic control of stone-breaking machines, which perform better if the sizes of the stones to be broken can be predicted. An algorithm is proposed for image segmentation in size inspection for almost round stones with high or low texture. Although our experiments are focused on stones, the algorithm can be applied to other 3-D objects. We use one fixed camera and four light sources at four different positions one at a time, to take four images. Then we compute the image differences and binarize them to extract edges. We explain, step by step, the photographing, the edge extraction, the noise removal, and the edge gap filling. Experimental results are presented.

  14. The Diagnostic Radiological Utilization Of 3-D Display Images

    NASA Astrophysics Data System (ADS)

    Cook, Larry T.; Dwyer, Samuel J.; Preston, David F.; Batnitzky, Solomon; Lee, Kyo R.

    1984-10-01

    In the practice of radiology, computer graphics systems have become an integral part of the use of computed tomography (CT), nuclear medicine (NM), magnetic resonance imaging (MRI), digital subtraction angiography (DSA) and ultrasound. Gray scale computerized display systems are used to display, manipulate, and record scans in all of these modalities. As the use of these imaging systems has spread, various applications involving digital image manipulation have also been widely accepted in the radiological community. We discuss one of the more esoteric of such applications, namely, the reconstruction of 3-D structures from plane section data, such as CT scans. Our technique is based on the acquisition of contour data from successive sections, the definition of the implicit surface defined by such contours, and the application of the appropriate computer graphics hardware and software to present reasonably pleasing pictures.

  15. Density-tapered spiral arrays for ultrasound 3-D imaging.

    PubMed

    Ramalli, Alessandro; Boni, Enrico; Savoia, Alessandro Stuart; Tortoli, Piero

    2015-08-01

    The current high interest in 3-D ultrasound imaging is pushing the development of 2-D probes with a challenging number of active elements. The most popular approach to limit this number is the sparse array technique, which designs the array layout by means of complex optimization algorithms. These algorithms are typically constrained by a few steering conditions, and, as such, cannot guarantee uniform side-lobe performance at all angles. The performance may be improved by the ungridded extensions of the sparse array technique, but this result is achieved at the expense of a further complication of the optimization process. In this paper, a method to design the layout of large circular arrays with a limited number of elements according to Fermat's spiral seeds and spatial density modulation is proposed and shown to be suitable for application to 3-D ultrasound imaging. This deterministic, aperiodic, and balanced positioning procedure attempts to guarantee uniform performance over a wide range of steering angles. The capabilities of the method are demonstrated by simulating and comparing the performance of spiral and dense arrays. A good trade-off for small vessel imaging is found, e.g., in the 60λ spiral array with 1.0λ elements and Blackman density tapering window. Here, the grating lobe level is -16 dB, the lateral resolution is lower than 6λ the depth of field is 120λ and, the average contrast is 10.3 dB, while the sensitivity remains in a 5 dB range for a wide selection of steering angles. The simulation results may represent a reference guide to the design of spiral sparse array probes for different application fields.

  16. Low cost 3D scanning process using digital image processing

    NASA Astrophysics Data System (ADS)

    Aguilar, David; Romero, Carlos; Martínez, Fernando

    2017-02-01

    This paper shows the design and building of a low cost 3D scanner, able to digitize solid objects through contactless data acquisition, using active object reflection. 3D scanners are used in different applications such as: science, engineering, entertainment, etc; these are classified in: contact scanners and contactless ones, where the last ones are often the most used but they are expensive. This low-cost prototype is done through a vertical scanning of the object using a fixed camera and a mobile horizontal laser light, which is deformed depending on the 3-dimensional surface of the solid. Using digital image processing an analysis of the deformation detected by the camera was done; it allows determining the 3D coordinates using triangulation. The obtained information is processed by a Matlab script, which gives to the user a point cloud corresponding to each horizontal scanning done. The obtained results show an acceptable quality and significant details of digitalized objects, making this prototype (built on LEGO Mindstorms NXT kit) a versatile and cheap tool, which can be used for many applications, mainly by engineering students.

  17. 3-D imaging and illustration of mouse intestinal neurovascular complex.

    PubMed

    Fu, Ya-Yuan; Peng, Shih-Jung; Lin, Hsin-Yao; Pasricha, Pankaj J; Tang, Shiue-Cheng

    2013-01-01

    Because of the dispersed nature of nerves and blood vessels, standard histology cannot provide a global and associated observation of the enteric nervous system (ENS) and vascular network. We prepared transparent mouse intestine and combined vessel painting and three-dimensional (3-D) neurohistology for joint visualization of the ENS and vasculature. Cardiac perfusion of the fluorescent wheat germ agglutinin (vessel painting) was used to label the ileal blood vessels. The pan-neuronal marker PGP9.5, sympathetic neuronal marker tyrosine hydroxylase (TH), serotonin, and glial markers S100B and GFAP were used as the immunostaining targets of neural tissues. The fluorescently labeled specimens were immersed in the optical clearing solution to improve photon penetration for 3-D confocal microscopy. Notably, we simultaneously revealed the ileal microstructure, vasculature, and innervation with micrometer-level resolution. Four examples are given: 1) the morphology of the TH-labeled sympathetic nerves: sparse in epithelium, perivascular at the submucosa, and intraganglionic at myenteric plexus; 2) distinct patterns of the extrinsic perivascular and intrinsic pericryptic innervation at the submucosal-mucosal interface; 3) different associations of serotonin cells with the mucosal neurovascular elements in the villi and crypts; and 4) the periganglionic capillary network at the myenteric plexus and its contact with glial fibers. Our 3-D imaging approach provides a useful tool to simultaneously reveal the nerves and blood vessels in a space continuum for panoramic illustration and analysis of the neurovascular complex to better understand the intestinal physiology and diseases.

  18. Effective classification of 3D image data using partitioning methods

    NASA Astrophysics Data System (ADS)

    Megalooikonomou, Vasileios; Pokrajac, Dragoljub; Lazarevic, Aleksandar; Obradovic, Zoran

    2002-03-01

    We propose partitioning-based methods to facilitate the classification of 3-D binary image data sets of regions of interest (ROIs) with highly non-uniform distributions. The first method is based on recursive dynamic partitioning of a 3-D volume into a number of 3-D hyper-rectangles. For each hyper-rectangle, we consider, as a potential attribute, the number of voxels (volume elements) that belong to ROIs. A hyper-rectangle is partitioned only if the corresponding attribute does not have high discriminative power, determined by statistical tests, but it is still sufficiently large for further splitting. The final discriminative hyper-rectangles form new attributes that are further employed in neural network classification models. The second method is based on maximum likelihood employing non-spatial (k-means) and spatial DBSCAN clustering algorithms to estimate the parameters of the underlying distributions. The proposed methods were experimentally evaluated on mixtures of Gaussian distributions, on realistic lesion-deficit data generated by a simulator conforming to a clinical study, and on synthetic fractal data. Both proposed methods have provided good classification on Gaussian mixtures and on realistic data. However, the experimental results on fractal data indicated that the clustering-based methods were only slightly better than random guess, while the recursive partitioning provided significantly better classification accuracy.

  19. 3D-LZ helicopter ladar imaging system

    NASA Astrophysics Data System (ADS)

    Savage, James; Harrington, Walter; McKinley, R. Andrew; Burns, H. N.; Braddom, Steven; Szoboszlay, Zoltan

    2010-04-01

    A joint-service team led by the Air Force Research Laboratory's Munitions and Sensors Directorates completed a successful flight test demonstration of the 3D-LZ Helicopter LADAR Imaging System. This was a milestone demonstration in the development of technology solutions for a problem known as "helicopter brownout", the loss of situational awareness caused by swirling sand during approach and landing. The 3D-LZ LADAR was developed by H.N. Burns Engineering and integrated with the US Army Aeroflightdynamics Directorate's Brown-Out Symbology System aircraft state symbology aboard a US Army EH-60 Black Hawk helicopter. The combination of these systems provided an integrated degraded visual environment landing solution with landing zone situational awareness as well as aircraft guidance and obstacle avoidance information. Pilots from the U.S. Army, Air Force, Navy, and Marine Corps achieved a 77% landing rate in full brownout conditions at a test range at Yuma Proving Ground, Arizona. This paper will focus on the LADAR technology used in 3D-LZ and the results of this milestone demonstration.

  20. 3D imaging reconstruction and impacted third molars: case reports

    PubMed Central

    Tuzi, Andrea; Di Bari, Roberto; Cicconetti, Andrea

    2012-01-01

    Summary There is a debate in the literature about the need for Computed Tomagraphy (CT) before removing third molars, even if positive radiographic signs are present. In few cases, the third molar is so close to the inferior alveolar nerve that its extraction might expose patients to the risk of post-operative neuro-sensitive alterations of the skin and the mucosa of the homolateral lower lip and chin. Thus, the injury of the inferior alveolar nerve may represent a serious, though infrequent, neurologic complication in the surgery of the third molars rendering necessary a careful pre-operative evaluation of their anatomical relationship with the inferior alveolar nerve by means of radiographic imaging techniques. This contribution presents two case reports showing positive radiographic signs, which are the hallmarks of a possible close relationship between the inferior alveolar nerve and the third molars. We aim at better defining the relationship between third molars and the mandibular canal using Dental CT Scan, DICOM image acquisition and 3D reconstruction with a dedicated software. By our study we deduce that 3D images are not indispensable, but they can provide a very agreeable assistance in the most complicated cases. PMID:23386934

  1. Precise 3D image alignment in micro-axial tomography.

    PubMed

    Matula, P; Kozubek, M; Staier, F; Hausmann, M

    2003-02-01

    Micro (micro-) axial tomography is a challenging technique in microscopy which improves quantitative imaging especially in cytogenetic applications by means of defined sample rotation under the microscope objective. The advantage of micro-axial tomography is an effective improvement of the precision of distance measurements between point-like objects. Under certain circumstances, the effective (3D) resolution can be improved by optimized acquisition depending on subsequent, multi-perspective image recording of the same objects followed by reconstruction methods. This requires, however, a very precise alignment of the tilted views. We present a novel feature-based image alignment method with a precision better than the full width at half maximum of the point spread function. The features are the positions (centres of gravity) of all fluorescent objects observed in the images (e.g. cell nuclei, fluorescent signals inside cell nuclei, fluorescent beads, etc.). Thus, real alignment precision depends on the localization precision of these objects. The method automatically determines the corresponding objects in subsequently tilted perspectives using a weighted bipartite graph. The optimum transformation function is computed in a least squares manner based on the coordinates of the centres of gravity of the matched objects. The theoretically feasible precision of the method was calculated using computer-generated data and confirmed by tests on real image series obtained from data sets of 200 nm fluorescent nano-particles. The advantages of the proposed algorithm are its speed and accuracy, which means that if enough objects are included, the real alignment precision is better than the axial localization precision of a single object. The alignment precision can be assessed directly from the algorithm's output. Thus, the method can be applied not only for image alignment and object matching in tilted view series in order to reconstruct (3D) images, but also to validate the

  2. A comparison of filtering techniques on denoising terahertz coaxial digital holography image

    NASA Astrophysics Data System (ADS)

    Cui, Shan-shan; Li, Qi

    2016-10-01

    In the process of recording terahertz digital hologram, the hologram is easy to be contaminated by speckle noise, which leads to lower resolution in imaging system and affects the reconstruction results seriously. Thus, the study of filtering algorithms applicable for de-speckling terahertz digital holography image has important practical values. In this paper, non-local means filtering and guided bilateral filtering were brought to process the real image reconstructed from continuous-wave terahertz coaxial digital hologram. For comparison, median filtering, bilateral filtering, and robust bilateral filtering, were introduced as conventional methods to denoise the real image. Then, all the denoising results were evaluated. The comparison indicates that the guided bilateral filter manifests the optimal denoising effect for the terahertz digital holography image, both significantly suppressing speckle noise, and effectively preserving the useful information on the reconstructed image.

  3. 3D laser optoacoustic ultrasonic imaging system for preclinical research

    NASA Astrophysics Data System (ADS)

    Ermilov, Sergey A.; Conjusteau, André; Hernandez, Travis; Su, Richard; Nadvoretskiy, Vyacheslav; Tsyboulski, Dmitri; Anis, Fatima; Anastasio, Mark A.; Oraevsky, Alexander A.

    2013-03-01

    In this work, we introduce a novel three-dimensional imaging system for in vivo high-resolution anatomical and functional whole-body visualization of small animal models developed for preclinical or other type of biomedical research. The system (LOUIS-3DM) combines a multi-wavelength optoacoustic and ultrawide-band laser ultrasound tomographies to obtain coregistered maps of tissue optical absorption and acoustic properties, displayed within the skin outline of the studied animal. The most promising applications of the LOUIS-3DM include 3D angiography, cancer research, and longitudinal studies of biological distribution of optoacoustic contrast agents (carbon nanotubes, metal plasmonic nanoparticles, etc.).

  4. 3D Multispectral Light Propagation Model For Subcutaneous Veins Imaging

    SciTech Connect

    Paquit, Vincent C; Price, Jeffery R; Meriaudeau, Fabrice; Tobin Jr, Kenneth William

    2008-01-01

    In this paper, we describe a new 3D light propagation model aimed at understanding the effects of various physiological properties on subcutaneous vein imaging. In particular, we build upon the well known MCML (Monte Carlo Multi Layer) code and present a tissue model that improves upon the current state-of-the-art by: incorporating physiological variation, such as melanin concentration, fat content, and layer thickness; including veins of varying depth and diameter; using curved surfaces from real arm shapes; and modeling the vessel wall interface. We describe our model, present results from the Monte Carlo modeling, and compare these results with those obtained with other Monte Carlo methods.

  5. 3D imaging of neutron tracks using confocal microscopy

    NASA Astrophysics Data System (ADS)

    Gillmore, Gavin; Wertheim, David; Flowers, Alan

    2016-04-01

    Neutron detection and neutron flux assessment are important aspects in monitoring nuclear energy production. Neutron flux measurements can also provide information on potential biological damage from exposure. In addition to the applications for neutron measurement in nuclear energy, neutron detection has been proposed as a method of enhancing neutrino detectors and cosmic ray flux has also been assessed using ground-level neutron detectors. Solid State Nuclear Track Detectors (or SSNTDs) have been used extensively to examine cosmic rays, long-lived radioactive elements, radon concentrations in buildings and the age of geological samples. Passive SSNTDs consisting of a CR-39 plastic are commonly used to measure radon because they respond to incident charged particles such as alpha particles from radon gas in air. They have a large dynamic range and a linear flux response. We have previously applied confocal microscopy to obtain 3D images of alpha particle tracks in SSNTDs from radon track monitoring (1). As a charged particle traverses through the polymer it creates an ionisation trail along its path. The trail or track is normally enhanced by chemical etching to better expose radiation damage, as the damaged area is more sensitive to the etchant than the bulk material. Particle tracks in CR-39 are usually assessed using 2D optical microscopy. In this study 6 detectors were examined using an Olympus OLS4100 LEXT 3D laser scanning confocal microscope (Olympus Corporation, Japan). The detectors had been etched for 2 hours 50 minutes at 85 °C in 6.25M NaOH. Post etch the plastics had been treated with a 10 minute immersion in a 2% acetic acid stop bath, followed by rinsing in deionised water. The detectors examined had been irradiated with a 2mSv neutron dose from an Am(Be) neutron source (producing roughly 20 tracks per mm2). We were able to successfully acquire 3D images of neutron tracks in the detectors studied. The range of track diameter observed was between 4

  6. 3-D Imaging of Partly Concealed Targets by Laser Radar

    DTIC Science & Technology

    2005-10-01

    laser in the green wavelength region was used for illumination. 3-D Imaging of Partly Concealed Targets by Laser Radar 11 - 8 RTO-MP-SET-094...acknowledge Marie Carlsson and Ann Charlotte Gustavsson for their assistance in some of the experiments. 7.0 REFERENCES [1] U. Söderman, S. Ahlberg...SPIE Vol. 3707, pp. 432-448, USA, 1999. [14] D. Letalick, H. Larsson, M. Carlsson, and A.-C. Gustavsson , “Laser sensors for urban warfare,” FOI

  7. [Multispectral remote sensing image denoising based on non-local means].

    PubMed

    Liu, Peng; Liu, Ding-Sheng; Li, Guo-Qing; Liu, Zhi-Wen

    2011-11-01

    The non-local mean denoising (NLM) exploits the fact that similar neighborhoods can occur anywhere in the image and can contribute to denoising. However, these current NLM methods do not aim at multichannel remote sensing image. Smoothing every band image separately will seriously damage the spectral information of the multispectral image. Then the authors promote the NLM from two aspects. Firstly, for multispectral image denoising, a weight value should be related to all channels but not only one channel. So for the kth band image, the authors use sum of smoothing kernel in all bands instead of one band. Secondly, for the patch whose spectral feature is similar to the spectral feature of the central patch, its weight should be larger. Bringing the two changes into the traditional non-local mean, a new multispectral non-local mean denoising method is proposed. In the experiments, different satellite images containing both urban and rural parts are used. For better evaluating the performance of the different method, ERGAS and SAM as quality index are used. And some other methods are compared with the proposed method. The proposed method shows better performance not only in ERGAS but also in SAM. Especially the spectral feature is better reserved in proposed NLM denoising.

  8. Quantitative 3D Optical Imaging: Applications in Dosimetry and Biophysics

    NASA Astrophysics Data System (ADS)

    Thomas, Andrew Stephen

    Optical-CT has been shown to be a potentially useful imaging tool for the two very different spheres of biologists and radiation therapy physicists, but it has yet to live up to that potential. In radiation therapy, researchers have used optical-CT for the readout of 3D dosimeters, but it is yet to be a clinically relevant tool as the technology is too slow to be considered practical. Biologists have used the technique for structural imaging, but have struggled with emission tomography as the reality of photon attenuation for both excitation and emission have made the images quantitatively irrelevant. Dosimetry. The DLOS (Duke Large field of view Optical-CT Scanner) was designed and constructed to make 3D dosimetry utilizing optical-CT a fast and practical tool while maintaining the accuracy of readout of the previous, slower readout technologies. Upon construction/optimization/implementation of several components including a diffuser, band pass filter, registration mount & fluid filtration system the dosimetry system provides high quality data comparable to or exceeding that of commercial products. In addition, a stray light correction algorithm was tested and implemented. The DLOS in combination with the 3D dosimeter it was designed for, PREAGETM, then underwent rigorous commissioning and benchmarking tests validating its performance against gold standard data including a set of 6 irradiations. DLOS commissioning tests resulted in sub-mm isotropic spatial resolution (MTF >0.5 for frequencies of 1.5lp/mm) and a dynamic range of ˜60dB. Flood field uniformity was 10% and stable after 45minutes. Stray light proved to be small, due to telecentricity, but even the residual can be removed through deconvolution. Benchmarking tests showed the mean 3D passing gamma rate (3%, 3mm, 5% dose threshold) over the 6 benchmark data sets was 97.3% +/- 0.6% (range 96%-98%) scans totaling ˜10 minutes, indicating excellent ability to perform 3D dosimetry while improving the speed of

  9. 3D painting documentation: evaluation of conservation conditions with 3D imaging and ranging techniques

    NASA Astrophysics Data System (ADS)

    Abate, D.; Menna, F.; Remondino, F.; Gattari, M. G.

    2014-06-01

    The monitoring of paintings, both on canvas and wooden support, is a crucial issue for the preservation and conservation of this kind of artworks. Many environmental factors (e.g. humidity, temperature, illumination, etc.), as well as bad conservation practices (e.g. wrong restorations, inappropriate locations, etc.), can compromise the material conditions over time and deteriorate an artwork. The article presents an on-going project realized by a multidisciplinary team composed by the ENEA UTICT 3D GraphLab, the 3D Optical Metrology Unit of the Bruno Kessler Foundation and the Soprintendenza per i Beni Storico Artistici ed Etnoantropologici of Bologna (Italy). The goal of the project is the multi-temporal 3D documentation and monitoring of paintings - at the moment in bad conservation's situation - and the provision of some metrics to quantify the deformations and damages.

  10. 3D Wavelet-Based Filter and Method

    DOEpatents

    Moss, William C.; Haase, Sebastian; Sedat, John W.

    2008-08-12

    A 3D wavelet-based filter for visualizing and locating structural features of a user-specified linear size in 2D or 3D image data. The only input parameter is a characteristic linear size of the feature of interest, and the filter output contains only those regions that are correlated with the characteristic size, thus denoising the image.

  11. Image denoising using nonsubsampled shearlet transform and twin support vector machines.

    PubMed

    Yang, Hong-Ying; Wang, Xiang-Yang; Niu, Pan-Pan; Liu, Yang-Cheng

    2014-09-01

    Denoising of images is one of the most basic tasks of image processing. It is a challenging work to design a edge/texture-preserving image denoising scheme. Nonsubsampled shearlet transform (NSST) is an effective multi-scale and multi-direction analysis method, it not only can exactly compute the shearlet coefficients based on a multiresolution analysis, but also can provide nearly optimal approximation for a piecewise smooth function. Based on NSST, a new edge/texture-preserving image denoising using twin support vector machines (TSVMs) is proposed in this paper. Firstly, the noisy image is decomposed into different subbands of frequency and orientation responses using the NSST. Secondly, the feature vector for a pixel in a noisy image is formed by the spatial geometric regularity in NSST domain, and the TSVMs model is obtained by training. Then the NSST detail coefficients are divided into information-related coefficients and noise-related ones by TSVMs training model. Finally, the detail subbands of NSST coefficients are denoised by using the adaptive threshold. Extensive experimental results demonstrate that our method can obtain better performances in terms of both subjective and objective evaluations than those state-of-the-art denoising techniques. Especially, the proposed method can preserve edges and textures very well while removing noise.

  12. Recent progress in 3-D imaging of sea freight containers

    SciTech Connect

    Fuchs, Theobald Schön, Tobias Sukowski, Frank; Dittmann, Jonas; Hanke, Randolf

    2015-03-31

    The inspection of very large objects like sea freight containers with X-ray Computed Tomography (CT) is an emerging technology. A complete 3-D CT scan of a see-freight container takes several hours. Of course, this is too slow to apply it to a large number of containers. However, the benefits of a 3-D CT for sealed freight are obvious: detection of potential threats or illicit cargo without being confronted with legal complications or high time consumption and risks for the security personnel during a manual inspection. Recently distinct progress was made in the field of reconstruction of projections with only a relatively low number of angular positions. Instead of today’s 500 to 1000 rotational steps, as needed for conventional CT reconstruction techniques, this new class of algorithms provides the potential to reduce the number of projection angles approximately by a factor of 10. The main drawback of these advanced iterative methods is the high consumption for numerical processing. But as computational power is getting steadily cheaper, there will be practical applications of these complex algorithms in a foreseeable future. In this paper, we discuss the properties of iterative image reconstruction algorithms and show results of their application to CT of extremely large objects scanning a sea-freight container. A specific test specimen is used to quantitatively evaluate the image quality in terms of spatial and contrast resolution and depending on different number of projections.

  13. Imaging Shallow Salt With 3D Refraction Migration

    NASA Astrophysics Data System (ADS)

    Vanschuyver, C. J.; Hilterman, F. J.

    2005-05-01

    In offshore West Africa, numerous salt walls are within 200 m of sea level. Because of the shallowness of these salt walls, reflections from the salt top can be difficult to map, making it impossible to build an accurate velocity model for subsequent pre-stack depth migration. An accurate definition of salt boundaries is critical to any depth model where salt is present. Unfortunately, when a salt body is very shallow, the reflection from the upper interface can be obscured due to large offsets between the source and near receivers and also due to the interference from multiples and other near-surface noise events. A new method is described using 3D migration of the refraction waveforms which is simplified because of several constraints in the model definition. The azimuth and dip of the refractor is found by imaging with Kirchhoff theory. A Kirchhoff migration is performed where the traveltime values are adjusted to use the CMP refraction traveltime equation. I assume the sediment and salt velocities to be known such that once the image time is specified, then the dip and azimuth of the refraction path can be found. The resulting 3D refraction migrations are in excellent depth agreement with available well control. In addition, the refraction migration time picks of deeper salt events are in agreement with time picks of the same events on the reflection migration.

  14. 3-D visualization and animation technologies in anatomical imaging.

    PubMed

    McGhee, John

    2010-02-01

    This paper explores a 3-D computer artist's approach to the creation of three-dimensional computer-generated imagery (CGI) derived from clinical scan data. Interpretation of scientific imagery, such as magnetic resonance imaging (MRI), is restricted to the eye of the trained medical practitioner in a clinical or scientific context. In the research work described here, MRI data are visualized and interpreted by a 3-D computer artist using the tools of the digital animator to navigate image complexity and widen interaction. In this process, the artefact moves across disciplines; it is no longer tethered to its diagnostic origins. It becomes an object that has visual attributes such as light, texture and composition, and a visual aesthetic of its own. The introduction of these visual attributes provides a platform for improved accessibility by a lay audience. The paper argues that this more artisan approach to clinical data visualization has a potential real-world application as a communicative tool for clinicians and patients during consultation.

  15. 3-D visualization and animation technologies in anatomical imaging

    PubMed Central

    McGhee, John

    2010-01-01

    This paper explores a 3-D computer artist’s approach to the creation of three-dimensional computer-generated imagery (CGI) derived from clinical scan data. Interpretation of scientific imagery, such as magnetic resonance imaging (MRI), is restricted to the eye of the trained medical practitioner in a clinical or scientific context. In the research work described here, MRI data are visualized and interpreted by a 3-D computer artist using the tools of the digital animator to navigate image complexity and widen interaction. In this process, the artefact moves across disciplines; it is no longer tethered to its diagnostic origins. It becomes an object that has visual attributes such as light, texture and composition, and a visual aesthetic of its own. The introduction of these visual attributes provides a platform for improved accessibility by a lay audience. The paper argues that this more artisan approach to clinical data visualization has a potential real-world application as a communicative tool for clinicians and patients during consultation. PMID:20002229

  16. 3-D Imaging and Simulation for Nephron Sparing Surgical Training.

    PubMed

    Ahmadi, Hamed; Liu, Jen-Jane

    2016-08-01

    Minimally invasive partial nephrectomy (MIPN) is now considered the procedure of choice for small renal masses largely based on functional advantages over traditional open surgery. Lack of haptic feedback, the need for spatial understanding of tumor borders, and advanced operative techniques to minimize ischemia time or achieve zero-ischemia PN are among factors that make MIPN a technically demanding operation with a steep learning curve for inexperienced surgeons. Surgical simulation has emerged as a useful training adjunct in residency programs to facilitate the acquisition of these complex operative skills in the setting of restricted work hours and limited operating room time and autonomy. However, the majority of available surgical simulators focus on basic surgical skills, and procedure-specific simulation is needed for optimal surgical training. Advances in 3-dimensional (3-D) imaging have also enhanced the surgeon's ability to localize tumors intraoperatively. This article focuses on recent procedure-specific simulation models for laparoscopic and robotic-assisted PN and advanced 3-D imaging techniques as part of pre- and some cases, intraoperative surgical planning.

  17. Experiments on terahertz 3D scanning microscopic imaging

    NASA Astrophysics Data System (ADS)

    Zhou, Yi; Li, Qi

    2016-10-01

    Compared with the visible light and infrared, terahertz (THz) radiation can penetrate nonpolar and nonmetallic materials. There are many studies on the THz coaxial transmission confocal microscopy currently. But few researches on the THz dual-axis reflective confocal microscopy were reported. In this paper, we utilized a dual-axis reflective confocal scanning microscope working at 2.52 THz. In contrast with the THz coaxial transmission confocal microscope, the microscope adopted in this paper can attain higher axial resolution at the expense of reduced lateral resolution, revealing more satisfying 3D imaging capability. Objects such as Chinese characters "Zhong-Hua" written in paper with a pencil and a combined sheet metal which has three layers were scanned. The experimental results indicate that the system can extract two Chinese characters "Zhong," "Hua" or three layers of the combined sheet metal. It can be predicted that the microscope can be applied to biology, medicine and other fields in the future due to its favorable 3D imaging capability.

  18. Abdominal aortic aneurysm imaging with 3-D ultrasound: 3-D-based maximum diameter measurement and volume quantification.

    PubMed

    Long, A; Rouet, L; Debreuve, A; Ardon, R; Barbe, C; Becquemin, J P; Allaire, E

    2013-08-01

    The clinical reliability of 3-D ultrasound imaging (3-DUS) in quantification of abdominal aortic aneurysm (AAA) was evaluated. B-mode and 3-DUS images of AAAs were acquired for 42 patients. AAAs were segmented. A 3-D-based maximum diameter (Max3-D) and partial volume (Vol30) were defined and quantified. Comparisons between 2-D (Max2-D) and 3-D diameters and between orthogonal acquisitions were performed. Intra- and inter-observer reproducibility was evaluated. Intra- and inter-observer coefficients of repeatability (CRs) were less than 5.18 mm for Max3-D. Intra-observer and inter-observer CRs were respectively less than 6.16 and 8.71 mL for Vol30. The mean of normalized errors of Vol30 was around 7%. Correlation between Max2-D and Max3-D was 0.988 (p < 0.0001). Max3-D and Vol30 were not influenced by a probe rotation of 90°. Use of 3-DUS to quantify AAA is a new approach in clinical practice. The present study proposed and evaluated dedicated parameters. Their reproducibility makes the technique clinically reliable.

  19. Object Segmentation and Ground Truth in 3D Embryonic Imaging

    PubMed Central

    Rajasekaran, Bhavna; Uriu, Koichiro; Valentin, Guillaume; Tinevez, Jean-Yves; Oates, Andrew C.

    2016-01-01

    Many questions in developmental biology depend on measuring the position and movement of individual cells within developing embryos. Yet, tools that provide this data are often challenged by high cell density and their accuracy is difficult to measure. Here, we present a three-step procedure to address this problem. Step one is a novel segmentation algorithm based on image derivatives that, in combination with selective post-processing, reliably and automatically segments cell nuclei from images of densely packed tissue. Step two is a quantitative validation using synthetic images to ascertain the efficiency of the algorithm with respect to signal-to-noise ratio and object density. Finally, we propose an original method to generate reliable and experimentally faithful ground truth datasets: Sparse-dense dual-labeled embryo chimeras are used to unambiguously measure segmentation errors within experimental data. Together, the three steps outlined here establish a robust, iterative procedure to fine-tune image analysis algorithms and microscopy settings associated with embryonic 3D image data sets. PMID:27332860

  20. Object Segmentation and Ground Truth in 3D Embryonic Imaging.

    PubMed

    Rajasekaran, Bhavna; Uriu, Koichiro; Valentin, Guillaume; Tinevez, Jean-Yves; Oates, Andrew C

    2016-01-01

    Many questions in developmental biology depend on measuring the position and movement of individual cells within developing embryos. Yet, tools that provide this data are often challenged by high cell density and their accuracy is difficult to measure. Here, we present a three-step procedure to address this problem. Step one is a novel segmentation algorithm based on image derivatives that, in combination with selective post-processing, reliably and automatically segments cell nuclei from images of densely packed tissue. Step two is a quantitative validation using synthetic images to ascertain the efficiency of the algorithm with respect to signal-to-noise ratio and object density. Finally, we propose an original method to generate reliable and experimentally faithful ground truth datasets: Sparse-dense dual-labeled embryo chimeras are used to unambiguously measure segmentation errors within experimental data. Together, the three steps outlined here establish a robust, iterative procedure to fine-tune image analysis algorithms and microscopy settings associated with embryonic 3D image data sets.

  1. High Resolution 3D Radar Imaging of Comet Interiors

    NASA Astrophysics Data System (ADS)

    Asphaug, E. I.; Gim, Y.; Belton, M.; Brophy, J.; Weissman, P. R.; Heggy, E.

    2012-12-01

    Knowing the interiors of comets and other primitive bodies is fundamental to our understanding of how planets formed. We have developed a Discovery-class mission formulation, Comet Radar Explorer (CORE), based on the use of previously flown planetary radar sounding techniques, with the goal of obtaining high resolution 3D images of the interior of a small primitive body. We focus on the Jupiter-Family Comets (JFCs) as these are among the most primitive bodies reachable by spacecraft. Scattered in from far beyond Neptune, they are ultimate targets of a cryogenic sample return mission according to the Decadal Survey. Other suitable targets include primitive NEOs, Main Belt Comets, and Jupiter Trojans. The approach is optimal for small icy bodies ~3-20 km diameter with spin periods faster than about 12 hours, since (a) navigation is relatively easy, (b) radar penetration is global for decameter wavelengths, and (c) repeated overlapping ground tracks are obtained. The science mission can be as short as ~1 month for a fast-rotating JFC. Bodies smaller than ~1 km can be globally imaged, but the navigation solutions are less accurate and the relative resolution is coarse. Larger comets are more interesting, but radar signal is unlikely to be reflected from depths greater than ~10 km. So, JFCs are excellent targets for a variety of reasons. We furthermore focus on the use of Solar Electric Propulsion (SEP) to rendezvous shortly after the comet's perihelion. This approach leaves us with ample power for science operations under dormant conditions beyond ~2-3 AU. This leads to a natural mission approach of distant observation, followed by closer inspection, terminated by a dedicated radar mapping orbit. Radar reflections are obtained from a polar orbit about the icy nucleus, which spins underneath. Echoes are obtained from a sounder operating at dual frequencies 5 and 15 MHz, with 1 and 10 MHz bandwidths respectively. The dense network of echoes is used to obtain global 3D

  2. 3D Image Analysis of Geomaterials using Confocal Microscopy

    NASA Astrophysics Data System (ADS)

    Mulukutla, G.; Proussevitch, A.; Sahagian, D.

    2009-05-01

    Confocal microscopy is one of the most significant advances in optical microscopy of the last century. It is widely used in biological sciences but its application to geomaterials lingers due to a number of technical problems. Potentially the technique can perform non-invasive testing on a laser illuminated sample that fluoresces using a unique optical sectioning capability that rejects out-of-focus light reaching the confocal aperture. Fluorescence in geomaterials is commonly induced using epoxy doped with a fluorochrome that is impregnated into the sample to enable discrimination of various features such as void space or material boundaries. However, for many geomaterials, this method cannot be used because they do not naturally fluoresce and because epoxy cannot be impregnated into inaccessible parts of the sample due to lack of permeability. As a result, the confocal images of most geomaterials that have not been pre-processed with extensive sample preparation techniques are of poor quality and lack the necessary image and edge contrast necessary to apply any commonly used segmentation techniques to conduct any quantitative study of its features such as vesicularity, internal structure, etc. In our present work, we are developing a methodology to conduct a quantitative 3D analysis of images of geomaterials collected using a confocal microscope with minimal amount of prior sample preparation and no addition of fluorescence. Two sample geomaterials, a volcanic melt sample and a crystal chip containing fluid inclusions are used to assess the feasibility of the method. A step-by-step process of image analysis includes application of image filtration to enhance the edges or material interfaces and is based on two segmentation techniques: geodesic active contours and region competition. Both techniques have been applied extensively to the analysis of medical MRI images to segment anatomical structures. Preliminary analysis suggests that there is distortion in the

  3. A new adaptive algorithm for image denoising based on curvelet transform

    NASA Astrophysics Data System (ADS)

    Chen, Musheng; Cai, Zhishan

    2013-10-01

    The purpose of this paper is to study a method of denoising images corrupted with additive white Gaussian noise. In this paper, the application of the time invariant discrete curvelet transform for noise reduction is considered. In curvelet transform, the frame elements are indexed by scale, orientation and location parameters. It is designed to represent edges and the singularities along curved paths more efficiently than the wavelet transform. Therefore, curvelet transform can get better results than wavelet method in image denoising. In general, image denoising imposes a compromise between noise reduction and preserving significant image details. To achieve a good performance in this respect, an efficient and adaptive image denoising method based on curvelet transform is presented in this paper. Firstly, the noisy image is decomposed into many levels to obtain different frequency sub-bands by curvelet transform. Secondly, efficient and adaptive threshold estimation based on generalized Gaussian distribution modeling of sub-band coefficients is used to remove the noisy coefficients. The choice of the threshold estimation is carried out by analyzing the standard deviation and threshold. Ultimately, invert the multi-scale decomposition to reconstruct the denoised image. Here, to prove the performance of the proposed method, the results are compared with other existent algorithms such as hard and soft threshold based on wavelet. The simulation results on several testing images indicate that the proposed method outperforms the other methods in peak signal to noise ratio and keeps better visual in edges information reservation as well. The results also suggest that curvelet transform can achieve a better performance than the wavelet transform in image denoising.

  4. Complex Resistivity 3D Imaging for Ground Reinforcement Site

    NASA Astrophysics Data System (ADS)

    Son, J.; Kim, J.; Park, S.

    2012-12-01

    Induced polarization (IP) method is used for mineral exploration and generally classified into two categories, time and frequency domain method. IP method in frequency domain measures amplitude and absolute phase to the transmitted currents, and is often called spectral induced polarization (SIP) when measurement is made for the wide-band frequencies. Our research group has been studying the modeling and inversion algorithms of complex resistivity method since several years ago and recently started to apply this method for various field applications. We already completed the development of 2/3D modeling and inversion program and developing another algorithm to use wide-band data altogether. Until now complex resistivity (CR) method was mainly used for the surface or tomographic survey of mineral exploration. Through the experience, we can find that the resistivity section from CR method is very similar with that of conventional resistivity method. Interpretation of the phase section is generally well matched with the geological information of survey area. But because most of survey area has very touch and complex terrain, 2D survey and interpretation are used generally. In this study, the case study of 3D CR survey conducted for the site where ground reinforcement was done to prevent the subsidence will be introduced. Data was acquired with the Zeta system, the complex resistivity measurement system produced by Zonge Co. using 8 frequencies from 0.125 to 16 Hz. 2D survey was conducted for total 6 lines with 5 m dipole spacing and 20 electrodes. Line length is 95 meter for every line. Among these 8 frequency data, data below 1 Hz was used considering its quality. With the 6 line data, 3D inversion was conducted. Firstly 2D interpretation was made with acquired data and its results were compared with those of resistivity survey. Resulting resistivity image sections of CR and resistivity method were very similar. Anomalies in phase image section showed good agreement

  5. Dual-wavelength retinal images denoising algorithm for improving the accuracy of oxygen saturation calculation

    NASA Astrophysics Data System (ADS)

    Xian, Yong-Li; Dai, Yun; Gao, Chun-Ming; Du, Rui

    2017-01-01

    Noninvasive measurement of hemoglobin oxygen saturation (SO2) in retinal vessels is based on spectrophotometry and spectral absorption characteristics of tissue. Retinal images at 570 and 600 nm are simultaneously captured by dual-wavelength retinal oximetry based on fundus camera. SO2 is finally measured after vessel segmentation, image registration, and calculation of optical density ratio of two images. However, image noise can dramatically affect subsequent image processing and SO2 calculation accuracy. The aforementioned problem remains to be addressed. The purpose of this study was to improve image quality and SO2 calculation accuracy by noise analysis and denoising algorithm for dual-wavelength images. First, noise parameters were estimated by mixed Poisson-Gaussian (MPG) noise model. Second, an MPG denoising algorithm which we called variance stabilizing transform (VST) + dual-domain image denoising (DDID) was proposed based on VST and improved dual-domain filter. The results show that VST + DDID is able to effectively remove MPG noise and preserve image edge details. VST + DDID is better than VST + block-matching and three-dimensional filtering, especially in preserving low-contrast details. The following simulation and analysis indicate that MPG noise in the retinal images can lead to erroneously low measurement for SO2, and the denoised images can provide more accurate grayscale values for retinal oximetry.

  6. [Curvelet denoising algorithm for medical ultrasound image based on adaptive threshold].

    PubMed

    Zhuang, Zhemin; Yao, Weike; Yang, Jinyao; Li, FenLan; Yuan, Ye

    2014-11-01

    The traditional denoising algorithm for ultrasound images would lost a lot of details and weak edge information when suppressing speckle noise. A new denoising algorithm of adaptive threshold based on curvelet transform is proposed in this paper. The algorithm utilizes differences of coefficients' local variance between texture and smooth region in each layer of ultrasound image to define fuzzy regions and membership functions. In the end, using the adaptive threshold that determine by the membership function to denoise the ultrasound image. The experimental text shows that the algorithm can reduce the speckle noise effectively and retain the detail information of original image at the same time, thus it can greatly enhance the performance of B ultrasound instrument.

  7. Low-dose computed tomography image denoising based on joint wavelet and sparse representation.

    PubMed

    Ghadrdan, Samira; Alirezaie, Javad; Dillenseger, Jean-Louis; Babyn, Paul

    2014-01-01

    Image denoising and signal enhancement are the most challenging issues in low dose computed tomography (CT) imaging. Sparse representational methods have shown initial promise for these applications. In this work we present a wavelet based sparse representation denoising technique utilizing dictionary learning and clustering. By using wavelets we extract the most suitable features in the images to obtain accurate dictionary atoms for the denoising algorithm. To achieve improved results we also lower the number of clusters which reduces computational complexity. In addition, a single image noise level estimation is developed to update the cluster centers in higher PSNRs. Our results along with the computational efficiency of the proposed algorithm clearly demonstrates the improvement of the proposed algorithm over other clustering based sparse representation (CSR) and K-SVD methods.

  8. High Time Resolution Photon Counting 3D Imaging Sensors

    NASA Astrophysics Data System (ADS)

    Siegmund, O.; Ertley, C.; Vallerga, J.

    2016-09-01

    Novel sealed tube microchannel plate (MCP) detectors using next generation cross strip (XS) anode readouts and high performance electronics have been developed to provide photon counting imaging sensors for Astronomy and high time resolution 3D remote sensing. 18 mm aperture sealed tubes with MCPs and high efficiency Super-GenII or GaAs photocathodes have been implemented to access the visible/NIR regimes for ground based research, astronomical and space sensing applications. The cross strip anode readouts in combination with PXS-II high speed event processing electronics can process high single photon counting event rates at >5 MHz ( 80 ns dead-time per event), and time stamp events to better than 25 ps. Furthermore, we are developing a high speed ASIC version of the electronics for low power/low mass spaceflight applications. For a GaAs tube the peak quantum efficiency has degraded from 30% (at 560 - 850 nm) to 25% over 4 years, but for Super-GenII tubes the peak quantum efficiency of 17% (peak at 550 nm) has remained unchanged for over 7 years. The Super-GenII tubes have a uniform spatial resolution of <30 μm FWHM ( 1 x106 gain) and single event timing resolution of 100 ps (FWHM). The relatively low MCP gain photon counting operation also permits longer overall sensor lifetimes and high local counting rates. Using the high timing resolution, we have demonstrated 3D object imaging with laser pulse (630 nm 45 ps jitter Pilas laser) reflections in single photon counting mode with spatial and depth sensitivity of the order of a few millimeters. A 50 mm Planacon sealed tube was also constructed, using atomic layer deposited microchannel plates which potentially offer better overall sealed tube lifetime, quantum efficiency and gain stability. This tube achieves standard bialkali quantum efficiency levels, is stable, and has been coupled to the PXS-II electronics and used to detect and image fast laser pulse signals.

  9. MIMO based 3D imaging system at 360 GHz

    NASA Astrophysics Data System (ADS)

    Herschel, R.; Nowok, S.; Zimmermann, R.; Lang, S. A.; Pohl, N.

    2016-05-01

    A MIMO radar imaging system at 360 GHz is presented as a part of the comprehensive approach of the European FP7 project TeraSCREEN, using multiple frequency bands for active and passive imaging. The MIMO system consists of 16 transmitter and 16 receiver antennas within one single array. Using a bandwidth of 30 GHz, a range resolution up to 5 mm is obtained. With the 16×16 MIMO system 256 different azimuth bins can be distinguished. Mechanical beam steering is used to measure 130 different elevation angles where the angular resolution is obtained by a focusing elliptical mirror. With this system a high resolution 3D image can be generated with 4 frames per second, each containing 16 million points. The principle of the system is presented starting from the functional structure, covering the hardware design and including the digital image generation. This is supported by simulated data and discussed using experimental results from a preliminary 90 GHz system underlining the feasibility of the approach.

  10. Research of Fast 3D Imaging Based on Multiple Mode

    NASA Astrophysics Data System (ADS)

    Chen, Shibing; Yan, Huimin; Ni, Xuxiang; Zhang, Xiuda; Wang, Yu

    2016-02-01

    Three-dimensional (3D) imaging has received increasingly extensive attention and has been widely used currently. Lots of efforts have been put on three-dimensional imaging method and system study, in order to meet fast and high accurate requirement. In this article, we realize a fast and high quality stereo matching algorithm on field programmable gate array (FPGA) using the combination of time-of-flight (TOF) camera and binocular camera. Images captured from the two cameras own a same spatial resolution, letting us use the depth maps taken by the TOF camera to figure initial disparity. Under the constraint of the depth map as the stereo pairs when comes to stereo matching, expected disparity of each pixel is limited within a narrow search range. In the meanwhile, using field programmable gate array (FPGA, altera cyclone IV series) concurrent computing we can configure multi core image matching system, thus doing stereo matching on embedded system. The simulation results demonstrate that it can speed up the process of stereo matching and increase matching reliability and stability, realize embedded calculation, expand application range.

  11. Fast 3-d tomographic microwave imaging for breast cancer detection.

    PubMed

    Grzegorczyk, Tomasz M; Meaney, Paul M; Kaufman, Peter A; diFlorio-Alexander, Roberta M; Paulsen, Keith D

    2012-08-01

    Microwave breast imaging (using electromagnetic waves of frequencies around 1 GHz) has mostly remained at the research level for the past decade, gaining little clinical acceptance. The major hurdles limiting patient use are both at the hardware level (challenges in collecting accurate and noncorrupted data) and software level (often plagued by unrealistic reconstruction times in the tens of hours). In this paper we report improvements that address both issues. First, the hardware is able to measure signals down to levels compatible with sub-centimeter image resolution while keeping an exam time under 2 min. Second, the software overcomes the enormous time burden and produces similarly accurate images in less than 20 min. The combination of the new hardware and software allows us to produce and report here the first clinical 3-D microwave tomographic images of the breast. Two clinical examples are selected out of 400+ exams conducted at the Dartmouth Hitchcock Medical Center (Lebanon, NH). The first example demonstrates the potential usefulness of our system for breast cancer screening while the second example focuses on therapy monitoring.

  12. Fast 3D subsurface imaging with stepped-frequency GPR

    NASA Astrophysics Data System (ADS)

    Masarik, Matthew P.; Burns, Joseph; Thelen, Brian T.; Sutter, Lena

    2015-05-01

    This paper investigates an algorithm for forming 3D images of the subsurface using stepped-frequency GPR data. The algorithm is specifically designed for a handheld GPR and therefore accounts for the irregular sampling pattern in the data and the spatially-variant air-ground interface by estimating an effective "ground-plane" and then registering the data to the plane. The algorithm efficiently solves the 4th-order polynomial for the Snell reflection points using a fully vectorized iterative scheme. The forward operator is implemented efficiently using an accelerated nonuniform FFT (Greengard and Lee, 2004); the adjoint operator is implemented efficiently using an interpolation step coupled with an upsampled FFT. The imaging is done as a linearized version of the full inverse problem, which is regularized using a sparsity constraint to reduce sidelobes and therefore improve image localization. Applying an appropriate sparsity constraint, the algorithm is able to eliminate most the surrounding clutter and sidelobes, while still rendering valuable image properties such as shape and size. The algorithm is applied to simulated data, controlled experimental data (made available by Dr. Waymond Scott, Georgia Institute of Technology), and government-provided data with irregular sampling and air-ground interface.

  13. Patch-based denoising method using low-rank technique and targeted database for optical coherence tomography image.

    PubMed

    Liu, Xiaoming; Yang, Zhou; Wang, Jia; Liu, Jun; Zhang, Kai; Hu, Wei

    2017-01-01

    Image denoising is a crucial step before performing segmentation or feature extraction on an image, which affects the final result in image processing. In recent years, utilizing the self-similarity characteristics of the images, many patch-based image denoising methods have been proposed, but most of them, named the internal denoising methods, utilized the noisy image only where the performances are constrained by the limited information they used. We proposed a patch-based method, which uses a low-rank technique and targeted database, to denoise the optical coherence tomography (OCT) image. When selecting the similar patches for the noisy patch, our method combined internal and external denoising, utilizing the other images relevant to the noisy image, in which our targeted database is made up of these two kinds of images and is an improvement compared with the previous methods. Next, we leverage the low-rank technique to denoise the group matrix consisting of the noisy patch and the corresponding similar patches, for the fact that a clean image can be seen as a low-rank matrix and rank of the noisy image is much larger than the clean image. After the first-step denoising is accomplished, we take advantage of Gabor transform, which considered the layer characteristic of the OCT retinal images, to construct a noisy image before the second step. Experimental results demonstrate that our method compares favorably with the existing state-of-the-art methods.

  14. NOTE: Automated wavelet denoising of photoacoustic signals for circulating melanoma cell detection and burn image reconstruction

    NASA Astrophysics Data System (ADS)

    Holan, Scott H.; Viator, John A.

    2008-06-01

    Photoacoustic image reconstruction may involve hundreds of point measurements, each of which contributes unique information about the subsurface absorbing structures under study. For backprojection imaging, two or more point measurements of photoacoustic waves induced by irradiating a biological sample with laser light are used to produce an image of the acoustic source. Each of these measurements must undergo some signal processing, such as denoising or system deconvolution. In order to process the numerous signals, we have developed an automated wavelet algorithm for denoising signals. We appeal to the discrete wavelet transform for denoising photoacoustic signals generated in a dilute melanoma cell suspension and in thermally coagulated blood. We used 5, 9, 45 and 270 melanoma cells in the laser beam path as test concentrations. For the burn phantom, we used coagulated blood in 1.6 mm silicon tube submerged in Intralipid. Although these two targets were chosen as typical applications for photoacoustic detection and imaging, they are of independent interest. The denoising employs level-independent universal thresholding. In order to accommodate nonradix-2 signals, we considered a maximal overlap discrete wavelet transform (MODWT). For the lower melanoma cell concentrations, as the signal-to-noise ratio approached 1, denoising allowed better peak finding. For coagulated blood, the signals were denoised to yield a clean photoacoustic resulting in an improvement of 22% in the reconstructed image. The entire signal processing technique was automated so that minimal user intervention was needed to reconstruct the images. Such an algorithm may be used for image reconstruction and signal extraction for applications such as burn depth imaging, depth profiling of vascular lesions in skin and the detection of single cancer cells in blood samples.

  15. 3D Chemical and Elemental Imaging by STXM Spectrotomography

    SciTech Connect

    Wang, J.; Karunakaran, C.; Lu, Y.; Hormes, J.; Hitchcock, A. P.; Prange, A.; Franz, B.; Harkness, T.; Obst, M.

    2011-09-09

    Spectrotomography based on the scanning transmission x-ray microscope (STXM) at the 10ID-1 spectromicroscopy beamline of the Canadian Light Source was used to study two selected unicellular microorganisms. Spatial distributions of sulphur globules, calcium, protein, and polysaccharide in sulphur-metabolizing bacteria (Allochromatium vinosum) were determined at the S 2p, C 1s, and Ca 2p edges. 3D chemical mapping showed that the sulphur globules are located inside the bacteria with a strong spatial correlation with calcium ions (it is most probably calcium carbonate from the medium; however, with STXM the distribution and localization in the cell can be made visible, which is very interesting for a biologist) and polysaccharide-rich polymers, suggesting an influence of the organic components on the formation of the sulphur and calcium deposits. A second study investigated copper accumulating in yeast cells (Saccharomyces cerevisiae) treated with copper sulphate. 3D elemental imaging at the Cu 2p edge showed that Cu(II) is reduced to Cu(I) on the yeast cell wall. A novel needle-like wet cell sample holder for STXM spectrotomography studies of fully hydrated samples is discussed.

  16. 3D Chemical and Elemental Imaging by STXM Spectrotomography

    NASA Astrophysics Data System (ADS)

    Wang, J.; Hitchcock, A. P.; Karunakaran, C.; Prange, A.; Franz, B.; Harkness, T.; Lu, Y.; Obst, M.; Hormes, J.

    2011-09-01

    Spectrotomography based on the scanning transmission x-ray microscope (STXM) at the 10ID-1 spectromicroscopy beamline of the Canadian Light Source was used to study two selected unicellular microorganisms. Spatial distributions of sulphur globules, calcium, protein, and polysaccharide in sulphur-metabolizing bacteria (Allochromatium vinosum) were determined at the S 2p, C 1s, and Ca 2p edges. 3D chemical mapping showed that the sulphur globules are located inside the bacteria with a strong spatial correlation with calcium ions (it is most probably calcium carbonate from the medium; however, with STXM the distribution and localization in the cell can be made visible, which is very interesting for a biologist) and polysaccharide-rich polymers, suggesting an influence of the organic components on the formation of the sulphur and calcium deposits. A second study investigated copper accumulating in yeast cells (Saccharomyces cerevisiae) treated with copper sulphate. 3D elemental imaging at the Cu 2p edge showed that Cu(II) is reduced to Cu(I) on the yeast cell wall. A novel needle-like wet cell sample holder for STXM spectrotomography studies of fully hydrated samples is discussed.

  17. Image sequence coding using 3D scene models

    NASA Astrophysics Data System (ADS)

    Girod, Bernd

    1994-09-01

    The implicit and explicit use of 3D models for image sequence coding is discussed. For implicit use, a 3D model can be incorporated into motion compensating prediction. A scheme that estimates the displacement vector field with a rigid body motion constraint by recovering epipolar lines from an unconstrained displacement estimate and then repeating block matching along the epipolar line is proposed. Experimental results show that an improved displacement vector field can be obtained with a rigid body motion constraint. As an example for explicit use, various results with a facial animation model for videotelephony are discussed. A 13 X 16 B-spline mask can be adapted automatically to individual faces and is used to generate facial expressions based on FACS. A depth-from-defocus range camera suitable for real-time facial motion tracking is described. Finally, the real-time facial animation system `Traugott' is presented that has been used to generate several hours of broadcast video. Experiments suggest that a videophone system based on facial animation might require a transmission bitrate of 1 kbit/s or below.

  18. Medical image denoising using one-dimensional singularity function model.

    PubMed

    Luo, Jianhua; Zhu, Yuemin; Hiba, Bassem

    2010-03-01

    A novel denoising approach is proposed that is based on a spectral data substitution mechanism through using a mathematical model of one-dimensional singularity function analysis (1-D SFA). The method consists in dividing the complete spectral domain of the noisy signal into two subsets: the preserved set where the spectral data are kept unchanged, and the substitution set where the original spectral data having lower signal-to-noise ratio (SNR) are replaced by those reconstructed using the 1-D SFA model. The preserved set containing original spectral data is determined according to the SNR of the spectrum. The singular points and singularity degrees in the 1-D SFA model are obtained through calculating finite difference of the noisy signal. The theoretical formulation and experimental results demonstrated that the proposed method allows more efficient denoising while introducing less distortion, and presents significant improvement over conventional denoising methods.

  19. Quantitative Multiscale Cell Imaging in Controlled 3D Microenvironments

    PubMed Central

    Welf, Erik S.; Driscoll, Meghan K.; Dean, Kevin M.; Schäfer, Claudia; Chu, Jun; Davidson, Michael W.; Lin, Michael Z.; Danuser, Gaudenz; Fiolka, Reto

    2016-01-01

    The microenvironment determines cell behavior, but the underlying molecular mechanisms are poorly understood because quantitative studies of cell signaling and behavior have been challenging due to insufficient spatial and/or temporal resolution and limitations on microenvironmental control. Here we introduce microenvironmental selective plane illumination microscopy (meSPIM) for imaging and quantification of intracellular signaling and submicrometer cellular structures as well as large-scale cell morphological and environmental features. We demonstrate the utility of this approach by showing that the mechanical properties of the microenvironment regulate the transition of melanoma cells from actin-driven protrusion to blebbing, and we present tools to quantify how cells manipulate individual collagen fibers. We leverage the nearly isotropic resolution of meSPIM to quantify the local concentration of actin and phosphatidylinositol 3-kinase signaling on the surfaces of cells deep within 3D collagen matrices and track the many small membrane protrusions that appear in these more physiologically relevant environments. PMID:26906741

  20. Unsupervised fuzzy segmentation of 3D magnetic resonance brain images

    NASA Astrophysics Data System (ADS)

    Velthuizen, Robert P.; Hall, Lawrence O.; Clarke, Laurence P.; Bensaid, Amine M.; Arrington, J. A.; Silbiger, Martin L.

    1993-07-01

    Unsupervised fuzzy methods are proposed for segmentation of 3D Magnetic Resonance images of the brain. Fuzzy c-means (FCM) has shown promising results for segmentation of single slices. FCM has been investigated for volume segmentations, both by combining results of single slices and by segmenting the full volume. Different strategies and initializations have been tried. In particular, two approaches have been used: (1) a method by which, iteratively, the furthest sample is split off to form a new cluster center, and (2) the traditional FCM in which the membership grade matrix is initialized in some way. Results have been compared with volume segmentations by k-means and with two supervised methods, k-nearest neighbors and region growing. Results of individual segmentations are presented as well as comparisons on the application of the different methods to a number of tumor patient data sets.

  1. 3D x-ray reconstruction using lightfield imaging

    NASA Astrophysics Data System (ADS)

    Saha, Sajib; Tahtali, Murat; Lambert, Andrew; Pickering, Mark R.

    2014-09-01

    Existing Computed Tomography (CT) systems require full 360° rotation projections. Using the principles of lightfield imaging, only 4 projections under ideal conditions can be sufficient when the object is illuminated with multiple-point Xray sources. The concept was presented in a previous work with synthetically sampled data from a synthetic phantom. Application to real data requires precise calibration of the physical set up. This current work presents the calibration procedures along with experimental findings for the reconstruction of a physical 3D phantom consisting of simple geometric shapes. The crucial part of this process is to determine the effective distances of the X-ray paths, which are not possible or very difficult by direct measurements. Instead, they are calculated by tracking the positions of fiducial markers under prescribed source and object movements. Iterative algorithms are used for the reconstruction. Customized backprojection is used to ensure better initial guess for the iterative algorithms to start with.

  2. 3D imaging of semiconductor components by discrete laminography

    NASA Astrophysics Data System (ADS)

    Batenburg, K. J.; Palenstijn, W. J.; Sijbers, J.

    2014-06-01

    X-ray laminography is a powerful technique for quality control of semiconductor components. Despite the advantages of nondestructive 3D imaging over 2D techniques based on sectioning, the acquisition time is still a major obstacle for practical use of the technique. In this paper, we consider the application of Discrete Tomography to laminography data, which can potentially reduce the scanning time while still maintaining a high reconstruction quality. By incorporating prior knowledge in the reconstruction algorithm about the materials present in the scanned object, far more accurate reconstructions can be obtained from the same measured data compared to classical reconstruction methods. We present a series of simulation experiments that illustrate the potential of the approach.

  3. 3D imaging of semiconductor components by discrete laminography

    SciTech Connect

    Batenburg, K. J.; Palenstijn, W. J.; Sijbers, J.

    2014-06-19

    X-ray laminography is a powerful technique for quality control of semiconductor components. Despite the advantages of nondestructive 3D imaging over 2D techniques based on sectioning, the acquisition time is still a major obstacle for practical use of the technique. In this paper, we consider the application of Discrete Tomography to laminography data, which can potentially reduce the scanning time while still maintaining a high reconstruction quality. By incorporating prior knowledge in the reconstruction algorithm about the materials present in the scanned object, far more accurate reconstructions can be obtained from the same measured data compared to classical reconstruction methods. We present a series of simulation experiments that illustrate the potential of the approach.

  4. 3D and multispectral imaging for subcutaneous veins detection.

    PubMed

    Paquit, Vincent C; Tobin, Kenneth W; Price, Jeffery R; Mèriaudeau, Fabrice

    2009-07-06

    The first and perhaps most important phase of a surgical procedure is the insertion of an intravenous (IV) catheter. Currently, this is performed manually by trained personnel. In some visions of future operating rooms, however, this process is to be replaced by an automated system. Experiments to determine the best NIR wavelengths to optimize vein contrast for physiological differences such as skin tone and/or the presence of hair on the arm or wrist surface are presented. For illumination our system is composed of a mercury arc lamp coupled to a 10nm band-pass spectrometer. A structured lighting system is also coupled to our multispectral system in order to provide 3D information of the patient arm orientation. Images of each patient arm are captured under every possible combinations of illuminants and the optimal combination of wavelengths for a given subject to maximize vein contrast using linear discriminant analysis is determined.

  5. A Registration Method Based on Contour Point Cloud for 3D Whole-Body PET and CT Images

    PubMed Central

    Yang, Qiyao; Wang, Zhiguo; Zhang, Guoxu

    2017-01-01

    The PET and CT fusion image, combining the anatomical and functional information, has important clinical meaning. An effective registration of PET and CT images is the basis of image fusion. This paper presents a multithread registration method based on contour point cloud for 3D whole-body PET and CT images. Firstly, a geometric feature-based segmentation (GFS) method and a dynamic threshold denoising (DTD) method are creatively proposed to preprocess CT and PET images, respectively. Next, a new automated trunk slices extraction method is presented for extracting feature point clouds. Finally, the multithread Iterative Closet Point is adopted to drive an affine transform. We compare our method with a multiresolution registration method based on Mattes Mutual Information on 13 pairs (246~286 slices per pair) of 3D whole-body PET and CT data. Experimental results demonstrate the registration effectiveness of our method with lower negative normalization correlation (NC = −0.933) on feature images and less Euclidean distance error (ED = 2.826) on landmark points, outperforming the source data (NC = −0.496, ED = 25.847) and the compared method (NC = −0.614, ED = 16.085). Moreover, our method is about ten times faster than the compared one. PMID:28316979

  6. [A novel denoising approach to SVD filtering based on DCT and PCA in CT image].

    PubMed

    Feng, Fuqiang; Wang, Jun

    2013-10-01

    Because of various effects of the imaging mechanism, noises are inevitably introduced in medical CT imaging process. Noises in the images will greatly degrade the quality of images and bring difficulties to clinical diagnosis. This paper presents a new method to improve singular value decomposition (SVD) filtering performance in CT image. Filter based on SVD can effectively analyze characteristics of the image in horizontal (and/or vertical) directions. According to the features of CT image, we can make use of discrete cosine transform (DCT) to extract the region of interest and to shield uninterested region so as to realize the extraction of structure characteristics of the image. Then we transformed SVD to the image after DCT, constructing weighting function for image reconstruction adaptively weighted. The algorithm for the novel denoising approach in this paper was applied in CT image denoising, and the experimental results showed that the new method could effectively improve the performance of SVD filtering.

  7. Needle placement for piriformis injection using 3-D imaging.

    PubMed

    Clendenen, Steven R; Candler, Shawn A; Osborne, Michael D; Palmer, Scott C; Duench, Stephanie; Glynn, Laura; Ghazi, Salim M

    2013-01-01

    Piriformis syndrome is a pain syndrome originating in the buttock and is attributed to 6% - 8% of patients referred for the treatment of back and leg pain. The treatment for piriformis syndrome using fluoroscopy, computed tomography (CT), electromyography (EMG), and ultrasound (US) has become standard practice. The treatment of Piriformis Syndrome has evolved to include fluoroscopy and EMG with CT guidance. We present a case study of 5 successful piriformis injections using 3-D computer-assisted electromagnet needle tracking coupled with ultrasound. A 6-degree of freedom electromagnetic position tracker was attached to the ultrasound probe that allowed the system to detect the position and orientation of the probe in the magnetic field. The tracked ultrasound probe was used to find the posterior superior iliac spine. Subsequently, 3 points were captured to register the ultrasound image with the CT or magnetic resonance image scan. Moreover, after the registration was obtained, the navigation system visualized the tracked needle relative to the CT scan in real-time using 2 orthogonal multi-planar reconstructions centered at the tracked needle tip. Conversely, a recent study revealed that fluoroscopically guided injections had 30% accuracy compared to ultrasound guided injections, which tripled the accuracy percentage. This novel technique exhibited an accurate needle guidance injection precision of 98% while advancing to the piriformis muscle and avoiding the sciatic nerve. The mean (± SD) procedure time was 19.08 (± 4.9) minutes. This technique allows for electromagnetic instrument tip tracking with real-time 3-D guidance to the selected target. As with any new technique, a learning curve is expected; however, this technique could offer an alternative, minimizing radiation exposure.

  8. Deep 3-D seismic reflection imaging of Precambrian sills in the crystalline crust of Alberta, Canada

    NASA Astrophysics Data System (ADS)

    Welford, Joanna Kim

    2005-07-01

    Using deep 3-D seismic reflection datasets collected by the Canadian petroleum exploration industry in southwestern and northwestern Alberta, the Head-Smashed-In and Winagami Precambrian sill complexes within the crystalline upper crust, previously identified on Lithoprobe 2-D multichannel reflection lines, are investigated to determine their 3-D geometries and reflective characteristics. During seismic processing of the dataset in southwestern Alberta, a recently developed wavelet-based method, Physical Wavelet Frame Denoising, is applied and shown to successfully suppress ground roll contamination while preserving low frequency signals from deeper structures. A new 3-D empirical trace interpolation scheme, DSInt, is developed to address the problem of spatial aliasing associated with 3-D data acquisition. Results from applying the algorithm to both datasets are comparable to available interpolation codes while allowing for greater flexibility in the handling of irregular acquisition geometries and interpolated trace headers. Evidence of the Head-Smashed-In reflector in southwestern Alberta is obtained using a dataset acquired to 8 s TWTT (approx. 24 km depth). From locally coherent, discontinuous pockets of basement reflectivity, the dataset appears to image the tapering western edge of the deep reflections imaged by Lithoprobe. A statistical approach of tracking reflectivity is developed and applied to obtain the spatial and temporal distribution of reflections. Simple 1-D forward modelling results reveal that the brightest reflections likely arise from a 50 to 150 m thick body of high density/high velocity material although variations in the amplitudes and lateral distribution of the reflections indicate that the thickness of the sills is laterally variable. Thus, the results are consistent with imaging the tapering edge of the sill complex. Clear evidence of the Winagami reflection sequence in northwestern Alberta, emerges from the second dataset acquired to 5

  9. Computed Tomography Images De-noising using a Novel Two Stage Adaptive Algorithm.

    PubMed

    Fadaee, Mojtaba; Shamsi, Mousa; Saberkari, Hamidreza; Sedaaghi, Mohammad Hossein

    2015-01-01

    In this paper, an optimal algorithm is presented for de-noising of medical images. The presented algorithm is based on improved version of local pixels grouping and principal component analysis. In local pixels grouping algorithm, blocks matching based on L (2) norm method is utilized, which leads to matching performance improvement. To evaluate the performance of our proposed algorithm, peak signal to noise ratio (PSNR) and structural similarity (SSIM) evaluation criteria have been used, which are respectively according to the signal to noise ratio in the image and structural similarity of two images. The proposed algorithm has two de-noising and cleanup stages. The cleanup stage is carried out comparatively; meaning that it is alternately repeated until the two conditions based on PSNR and SSIM are established. Implementation results show that the presented algorithm has a significant superiority in de-noising. Furthermore, the quantities of SSIM and PSNR values are higher in comparison to other methods.

  10. Computed Tomography Images De-noising using a Novel Two Stage Adaptive Algorithm

    PubMed Central

    Fadaee, Mojtaba; Shamsi, Mousa; Saberkari, Hamidreza; Sedaaghi, Mohammad Hossein

    2015-01-01

    In this paper, an optimal algorithm is presented for de-noising of medical images. The presented algorithm is based on improved version of local pixels grouping and principal component analysis. In local pixels grouping algorithm, blocks matching based on L2 norm method is utilized, which leads to matching performance improvement. To evaluate the performance of our proposed algorithm, peak signal to noise ratio (PSNR) and structural similarity (SSIM) evaluation criteria have been used, which are respectively according to the signal to noise ratio in the image and structural similarity of two images. The proposed algorithm has two de-noising and cleanup stages. The cleanup stage is carried out comparatively; meaning that it is alternately repeated until the two conditions based on PSNR and SSIM are established. Implementation results show that the presented algorithm has a significant superiority in de-noising. Furthermore, the quantities of SSIM and PSNR values are higher in comparison to other methods. PMID:26955565

  11. Denoising of PET images by combining wavelets and curvelets for improved preservation of resolution and quantitation.

    PubMed

    Le Pogam, A; Hanzouli, H; Hatt, M; Cheze Le Rest, C; Visvikis, D

    2013-12-01

    Denoising of Positron Emission Tomography (PET) images is a challenging task due to the inherent low signal-to-noise ratio (SNR) of the acquired data. A pre-processing denoising step may facilitate and improve the results of further steps such as segmentation, quantification or textural features characterization. Different recent denoising techniques have been introduced and most state-of-the-art methods are based on filtering in the wavelet domain. However, the wavelet transform suffers from some limitations due to its non-optimal processing of edge discontinuities. More recently, a new multi scale geometric approach has been proposed, namely the curvelet transform. It extends the wavelet transform to account for directional properties in the image. In order to address the issue of resolution loss associated with standard denoising, we considered a strategy combining the complementary wavelet and curvelet transforms. We compared different figures of merit (e.g. SNR increase, noise decrease in homogeneous regions, resolution loss, and intensity bias) on simulated and clinical datasets with the proposed combined approach and the wavelet-only and curvelet-only filtering techniques. The three methods led to an increase of the SNR. Regarding the quantitative accuracy however, the wavelet and curvelet only denoising approaches led to larger biases in the intensity and the contrast than the proposed combined algorithm. This approach could become an alternative solution to filters currently used after image reconstruction in clinical systems such as the Gaussian filter.

  12. High resolution 3D imaging of synchrotron generated microbeams

    SciTech Connect

    Gagliardi, Frank M.; Cornelius, Iwan; Blencowe, Anton; Franich, Rick D.; Geso, Moshi

    2015-12-15

    Purpose: Microbeam radiation therapy (MRT) techniques are under investigation at synchrotrons worldwide. Favourable outcomes from animal and cell culture studies have proven the efficacy of MRT. The aim of MRT researchers currently is to progress to human clinical trials in the near future. The purpose of this study was to demonstrate the high resolution and 3D imaging of synchrotron generated microbeams in PRESAGE® dosimeters using laser fluorescence confocal microscopy. Methods: Water equivalent PRESAGE® dosimeters were fabricated and irradiated with microbeams on the Imaging and Medical Beamline at the Australian Synchrotron. Microbeam arrays comprised of microbeams 25–50 μm wide with 200 or 400 μm peak-to-peak spacing were delivered as single, cross-fire, multidirectional, and interspersed arrays. Imaging of the dosimeters was performed using a NIKON A1 laser fluorescence confocal microscope. Results: The spatial fractionation of the MRT beams was clearly visible in 2D and up to 9 mm in depth. Individual microbeams were easily resolved with the full width at half maximum of microbeams measured on images with resolutions of as low as 0.09 μm/pixel. Profiles obtained demonstrated the change of the peak-to-valley dose ratio for interspersed MRT microbeam arrays and subtle variations in the sample positioning by the sample stage goniometer were measured. Conclusions: Laser fluorescence confocal microscopy of MRT irradiated PRESAGE® dosimeters has been validated in this study as a high resolution imaging tool for the independent spatial and geometrical verification of MRT beam delivery.

  13. Performance assessment of 3D surface imaging technique for medical imaging applications

    NASA Astrophysics Data System (ADS)

    Li, Tuotuo; Geng, Jason; Li, Shidong

    2013-03-01

    Recent development in optical 3D surface imaging technologies provide better ways to digitalize the 3D surface and its motion in real-time. The non-invasive 3D surface imaging approach has great potential for many medical imaging applications, such as motion monitoring of radiotherapy, pre/post evaluation of plastic surgery and dermatology, to name a few. Various commercial 3D surface imaging systems have appeared on the market with different dimension, speed and accuracy. For clinical applications, the accuracy, reproducibility and robustness across the widely heterogeneous skin color, tone, texture, shape properties, and ambient lighting is very crucial. Till now, a systematic approach for evaluating the performance of different 3D surface imaging systems still yet exist. In this paper, we present a systematic performance assessment approach to 3D surface imaging system assessment for medical applications. We use this assessment approach to exam a new real-time surface imaging system we developed, dubbed "Neo3D Camera", for image-guided radiotherapy (IGRT). The assessments include accuracy, field of view, coverage, repeatability, speed and sensitivity to environment, texture and color.

  14. A Simple Quality Assessment Index for Stereoscopic Images Based on 3D Gradient Magnitude

    PubMed Central

    Wang, Shanshan; Shao, Feng; Li, Fucui; Yu, Mei; Jiang, Gangyi

    2014-01-01

    We present a simple quality assessment index for stereoscopic images based on 3D gradient magnitude. To be more specific, we construct 3D volume from the stereoscopic images across different disparity spaces and calculate pointwise 3D gradient magnitude similarity (3D-GMS) along three horizontal, vertical, and viewpoint directions. Then, the quality score is obtained by averaging the 3D-GMS scores of all points in the 3D volume. Experimental results on four publicly available 3D image quality assessment databases demonstrate that, in comparison with the most related existing methods, the devised algorithm achieves high consistency alignment with subjective assessment. PMID:25133265

  15. 3D Slicer as an Image Computing Platform for the Quantitative Imaging Network

    PubMed Central

    Fedorov, Andriy; Beichel, Reinhard; Kalpathy-Cramer, Jayashree; Finet, Julien; Fillion-Robin, Jean-Christophe; Pujol, Sonia; Bauer, Christian; Jennings, Dominique; Fennessy, Fiona; Sonka, Milan; Buatti, John; Aylward, Stephen; Miller, James V.; Pieper, Steve; Kikinis, Ron

    2012-01-01

    Quantitative analysis has tremendous but mostly unrealized potential in healthcare to support objective and accurate interpretation of the clinical imaging. In 2008, the National Cancer Institute began building the Quantitative Imaging Network (QIN) initiative with the goal of advancing quantitative imaging in the context of personalized therapy and evaluation of treatment response. Computerized analysis is an important component contributing to reproducibility and efficiency of the quantitative imaging techniques. The success of quantitative imaging is contingent on robust analysis methods and software tools to bring these methods from bench to bedside. 3D Slicer is a free open source software application for medical image computing. As a clinical research tool, 3D Slicer is similar to a radiology workstation that supports versatile visualizations but also provides advanced functionality such as automated segmentation and registration for a variety of application domains. Unlike a typical radiology workstation, 3D Slicer is free and is not tied to specific hardware. As a programming platform, 3D Slicer facilitates translation and evaluation of the new quantitative methods by allowing the biomedical researcher to focus on the implementation of the algorithm, and providing abstractions for the common tasks of data communication, visualization and user interface development. Compared to other tools that provide aspects of this functionality, 3D Slicer is fully open source and can be readily extended and redistributed. In addition, 3D Slicer is designed to facilitate the development of new functionality in the form of 3D Slicer extensions. In this paper, we present an overview of 3D Slicer as a platform for prototyping, development and evaluation of image analysis tools for clinical research applications. To illustrate the utility of the platform in the scope of QIN, we discuss several use cases of 3D Slicer by the existing QIN teams, and we elaborate on the future

  16. Adaptive Tensor-Based Principal Component Analysis for Low-Dose CT Image Denoising.

    PubMed

    Ai, Danni; Yang, Jian; Fan, Jingfan; Cong, Weijian; Wang, Yongtian

    2015-01-01

    Computed tomography (CT) has a revolutionized diagnostic radiology but involves large radiation doses that directly impact image quality. In this paper, we propose adaptive tensor-based principal component analysis (AT-PCA) algorithm for low-dose CT image denoising. Pixels in the image are presented by their nearby neighbors, and are modeled as a patch. Adaptive searching windows are calculated to find similar patches as training groups for further processing. Tensor-based PCA is used to obtain transformation matrices, and coefficients are sequentially shrunk by the linear minimum mean square error. Reconstructed patches are obtained, and a denoised image is finally achieved by aggregating all of these patches. The experimental results of the standard test image show that the best results are obtained with two denoising rounds according to six quantitative measures. For the experiment on the clinical images, the proposed AT-PCA method can suppress the noise, enhance the edge, and improve the image quality more effectively than NLM and KSVD denoising methods.

  17. Adaptive Tensor-Based Principal Component Analysis for Low-Dose CT Image Denoising

    PubMed Central

    Ai, Danni; Yang, Jian; Fan, Jingfan; Cong, Weijian; Wang, Yongtian

    2015-01-01

    Computed tomography (CT) has a revolutionized diagnostic radiology but involves large radiation doses that directly impact image quality. In this paper, we propose adaptive tensor-based principal component analysis (AT-PCA) algorithm for low-dose CT image denoising. Pixels in the image are presented by their nearby neighbors, and are modeled as a patch. Adaptive searching windows are calculated to find similar patches as training groups for further processing. Tensor-based PCA is used to obtain transformation matrices, and coefficients are sequentially shrunk by the linear minimum mean square error. Reconstructed patches are obtained, and a denoised image is finally achieved by aggregating all of these patches. The experimental results of the standard test image show that the best results are obtained with two denoising rounds according to six quantitative measures. For the experiment on the clinical images, the proposed AT-PCA method can suppress the noise, enhance the edge, and improve the image quality more effectively than NLM and KSVD denoising methods. PMID:25993566

  18. 3D Seismic Imaging over a Potential Collapse Structure

    NASA Astrophysics Data System (ADS)

    Gritto, Roland; O'Connell, Daniel; Elobaid Elnaiem, Ali; Mohamed, Fathelrahman; Sadooni, Fadhil

    2016-04-01

    The Middle-East has seen a recent boom in construction including the planning and development of complete new sub-sections of metropolitan areas. Before planning and construction can commence, however, the development areas need to be investigated to determine their suitability for the planned project. Subsurface parameters such as the type of material (soil/rock), thickness of top soil or rock layers, depth and elastic parameters of basement, for example, comprise important information needed before a decision concerning the suitability of the site for construction can be made. A similar problem arises in environmental impact studies, when subsurface parameters are needed to assess the geological heterogeneity of the subsurface. Environmental impact studies are typically required for each construction project, particularly for the scale of the aforementioned building boom in the Middle East. The current study was conducted in Qatar at the location of a future highway interchange to evaluate a suite of 3D seismic techniques in their effectiveness to interrogate the subsurface for the presence of karst-like collapse structures. The survey comprised an area of approximately 10,000 m2 and consisted of 550 source- and 192 receiver locations. The seismic source was an accelerated weight drop while the geophones consisted of 3-component 10 Hz velocity sensors. At present, we analyzed over 100,000 P-wave phase arrivals and performed high-resolution 3-D tomographic imaging of the shallow subsurface. Furthermore, dispersion analysis of recorded surface waves will be performed to obtain S-wave velocity profiles of the subsurface. Both results, in conjunction with density estimates, will be utilized to determine the elastic moduli of the subsurface rock layers.

  19. Venus Topography in 3D: Imaging of Coronae and Chasmata

    NASA Astrophysics Data System (ADS)

    Jurdy, D. M.; Stefanick, M.; Stoddard, P. R.

    2006-12-01

    Venus' surface hosts hundreds of circular to elongate features, ranging from 60-2600 km, and averaging somewhat over 200 km, in diameter. These enigmatic structures have been classified as "coronae" and attributed to either tectono-volcanic or impact-related mechanisms. A linear to arcuate system of chasmata - rugged zones with some of Venus' deepest troughs, extend 1000's of kilometers. They have extreme relief, with elevations changing as much as 7 km in just 30 km distance. The 54,464 km-long Venus chasmata system defined in great detail by Magellan can be fit by great circle arcs at the 89.6% level, and when corrected for the smaller size of the planet, the total length of the chasmata system measures within 2.7% of the length of Earth's spreading ridges. The relatively young Beta-Atla-Themis region (BAT), within 30° of the equator from 180-300° longitude has the planet's strongest geoid highs and profuse volcanism. This BAT region, the intersection of three rift zones, also has a high coronal concentration, with individual coronae closely associated with the chasmata system. The chasmata with the greatest relief on Venus show linear rifting that prevailed in the latest stage of tectonic deformation. For a three-dimensional view of Venus' surface, we spread out the Magellan topography on a flat surface using a Mercator projection to preserve shape. Next we illuminate the surface with beams at angle 45° from left (or right) so as to simulate mid afternoon (or mid-morning). Finally, we observe the surface with two eyes looking through orange and azure colored filters respectively. This gives a 3D view of tectonic features in the BAT area. The 3D images clearly show coronae sharing boundaries with the chasmata. This suggests that the processes of rifting and corona-formation occur together. It seems unlikely that impact craters would create this pattern.

  20. Autostereoscopic 3D visualization and image processing system for neurosurgery.

    PubMed

    Meyer, Tobias; Kuß, Julia; Uhlemann, Falk; Wagner, Stefan; Kirsch, Matthias; Sobottka, Stephan B; Steinmeier, Ralf; Schackert, Gabriele; Morgenstern, Ute

    2013-06-01

    A demonstrator system for planning neurosurgical procedures was developed based on commercial hardware and software. The system combines an easy-to-use environment for surgical planning with high-end visualization and the opportunity to analyze data sets for research purposes. The demonstrator system is based on the software AMIRA. Specific algorithms for segmentation, elastic registration, and visualization have been implemented and adapted to the clinical workflow. Modules from AMIRA and the image processing library Insight Segmentation and Registration Toolkit (ITK) can be combined to solve various image processing tasks. Customized modules tailored to specific clinical problems can easily be implemented using the AMIRA application programming interface and a self-developed framework for ITK filters. Visualization is done via autostereoscopic displays, which provide a 3D impression without viewing aids. A Spaceball device allows a comfortable, intuitive way of navigation in the data sets. Via an interface to a neurosurgical navigation system, the demonstrator system can be used intraoperatively. The precision, applicability, and benefit of the demonstrator system for planning of neurosurgical interventions and for neurosurgical research were successfully evaluated by neurosurgeons using phantom and patient data sets.

  1. [3D virtual imaging of the upper airways].

    PubMed

    Ferretti, G; Coulomb, M

    2000-04-01

    The different three dimensional reconstructions of the upper airways that can be obtained with spiral computed tomograpy (CT) are presented here. The parameters indispensable to achieve as real as possible spiral CT images are recalled together with the advantages and disadvantages of the different techniues. Multislice reconstruction (MSR) produces slices in different planes of space with the high contrast of CT slices. They provide information similar to that obtained for the rare indications for thoracic MRI. Thick slice reconstructions with maximum intensity projection (MIP) or minimum intensity projection (minIP) give projection views where the contrast can be modified by selecting the more dense (MIP) or less dense (minIP) voxels. They find their application in the exploration of the upper airways. Surface and volume external 3D reconstructions can be obtained. They give an overall view of the upper airways, similar to a bronchogram. Virtual endoscopy reproduces real endoscopic images but cannot provide information on the aspect of the mucosa or biopsy specimens. It offers possible applications for preparing, guiding and controlling interventional fibroscopy procedures.

  2. Multiframe image point matching and 3-d surface reconstruction.

    PubMed

    Tsai, R Y

    1983-02-01

    This paper presents two new methods, the Joint Moment Method (JMM) and the Window Variance Method (WVM), for image matching and 3-D object surface reconstruction using multiple perspective views. The viewing positions and orientations for these perspective views are known a priori, as is usually the case for such applications as robotics and industrial vision as well as close range photogrammetry. Like the conventional two-frame correlation method, the JMM and WVM require finding the extrema of 1-D curves, which are proved to theoretically approach a delta function exponentially as the number of frames increases for the JMM and are much sharper than the two-frame correlation function for both the JMM and the WVM, even when the image point to be matched cannot be easily distinguished from some of the other points. The theoretical findings have been supported by simulations. It is also proved that JMM and WVM are not sensitive to certain radiometric effects. If the same window size is used, the computational complexity for the proposed methods is about n - 1 times that for the two-frame method where n is the number of frames. Simulation results show that the JMM and WVM require smaller windows than the two-frame correlation method with better accuracy, and therefore may even be more computationally feasible than the latter since the computational complexity increases quadratically as a function of the window size.

  3. Enhanced 3D fluorescence live cell imaging on nanoplasmonic substrate

    NASA Astrophysics Data System (ADS)

    Ranjan Gartia, Manas; Hsiao, Austin; Sivaguru, Mayandi; Chen, Yi; Logan Liu, G.

    2011-09-01

    We have created a randomly distributed nanocone substrate on silicon coated with silver for surface-plasmon-enhanced fluorescence detection and 3D cell imaging. Optical characterization of the nanocone substrate showed it can support several plasmonic modes (in the 300-800 nm wavelength range) that can be coupled to a fluorophore on the surface of the substrate, which gives rise to the enhanced fluorescence. Spectral analysis suggests that a nanocone substrate can create more excitons and shorter lifetime in the model fluorophore Rhodamine 6G (R6G) due to plasmon resonance energy transfer from the nanocone substrate to the nearby fluorophore. We observed three-dimensional fluorescence enhancement on our substrate shown from the confocal fluorescence imaging of chinese hamster ovary (CHO) cells grown on the substrate. The fluorescence intensity from the fluorophores bound on the cell membrane was amplified more than 100-fold as compared to that on a glass substrate. We believe that strong scattering within the nanostructured area coupled with random scattering inside the cell resulted in the observed three-dimensional enhancement in fluorescence with higher photostability on the substrate surface.

  4. Advanced 3D polarimetric flash ladar imaging through foliage

    NASA Astrophysics Data System (ADS)

    Murray, James T.; Moran, Steven E.; Roddier, Nicolas; Vercillo, Richard; Bridges, Robert; Austin, William

    2003-08-01

    High-resolution three-dimensional flash ladar system technologies are under development that enables remote identification of vehicles and armament hidden by heavy tree canopies. We have developed a sensor architecture and design that employs a 3D flash ladar receiver to address this mission. The receiver captures 128×128×>30 three-dimensional images for each laser pulse fired. The voxel size of the image is 3"×3"×4" at the target location. A novel signal-processing algorithm has been developed that achieves sub-voxel (sub-inch) range precision estimates of target locations within each pixel. Polarization discrimination is implemented to augment the target-to-foliage contrast. When employed, this method improves the range resolution of the system beyond the classical limit (based on pulsewidth and detection bandwidth). Experiments were performed with a 6 ns long transmitter pulsewidth that demonstrate 1-inch range resolution of a tank-like target that is occluded by foliage and a range precision of 0.3" for unoccluded targets.

  5. Complex adaptation-based LDR image rendering for 3D image reconstruction

    NASA Astrophysics Data System (ADS)

    Lee, Sung-Hak; Kwon, Hyuk-Ju; Sohng, Kyu-Ik

    2014-07-01

    A low-dynamic tone-compression technique is developed for realistic image rendering that can make three-dimensional (3D) images similar to realistic scenes by overcoming brightness dimming in the 3D display mode. The 3D surround provides varying conditions for image quality, illuminant adaptation, contrast, gamma, color, sharpness, and so on. In general, gain/offset adjustment, gamma compensation, and histogram equalization have performed well in contrast compression; however, as a result of signal saturation and clipping effects, image details are removed and information is lost on bright and dark areas. Thus, an enhanced image mapping technique is proposed based on space-varying image compression. The performance of contrast compression is enhanced with complex adaptation in a 3D viewing surround combining global and local adaptation. Evaluating local image rendering in view of tone and color expression, noise reduction, and edge compensation confirms that the proposed 3D image-mapping model can compensate for the loss of image quality in the 3D mode.

  6. 3D-3D registration of partial capitate bones using spin-images

    NASA Astrophysics Data System (ADS)

    Breighner, Ryan; Holmes, David R.; Leng, Shuai; An, Kai-Nan; McCollough, Cynthia; Zhao, Kristin

    2013-03-01

    It is often necessary to register partial objects in medical imaging. Due to limited field of view (FOV), the entirety of an object cannot always be imaged. This study presents a novel application of an existing registration algorithm to this problem. The spin-image algorithm [1] creates pose-invariant representations of global shape with respect to individual mesh vertices. These `spin-images,' are then compared for two different poses of the same object to establish correspondences and subsequently determine relative orientation of the poses. In this study, the spin-image algorithm is applied to 4DCT-derived capitate bone surfaces to assess the relative accuracy of registration with various amounts of geometry excluded. The limited longitudinal coverage under the 4DCT technique (38.4mm, [2]), results in partial views of the capitate when imaging wrist motions. This study assesses the ability of the spin-image algorithm to register partial bone surfaces by artificially restricting the capitate geometry available for registration. Under IRB approval, standard static CT and 4DCT scans were obtained on a patient. The capitate was segmented from the static CT and one phase of 4DCT in which the whole bone was available. Spin-image registration was performed between the static and 4DCT. Distal portions of the 4DCT capitate (10-70%) were then progressively removed and registration was repeated. Registration accuracy was evaluated by angular errors and the percentage of sub-resolution fitting. It was determined that 60% of the distal capitate could be omitted without appreciable effect on registration accuracy using the spin-image algorithm (angular error < 1.5 degree, sub-resolution fitting < 98.4%).

  7. Automated wavelet denoising of photoacoustic signals for burn-depth image reconstruction

    NASA Astrophysics Data System (ADS)

    Holan, Scott H.; Viator, John A.

    2007-02-01

    Photoacoustic image reconstruction involves dozens or perhaps hundreds of point measurements, each of which contributes unique information about the subsurface absorbing structures under study. For backprojection imaging, two or more point measurements of photoacoustic waves induced by irradiating a sample with laser light are used to produce an image of the acoustic source. Each of these point measurements must undergo some signal processing, such as denoising and system deconvolution. In order to efficiently process the numerous signals acquired for photoacoustic imaging, we have developed an automated wavelet algorithm for processing signals generated in a burn injury phantom. We used the discrete wavelet transform to denoise photoacoustic signals generated in an optically turbid phantom containing whole blood. The denoising used universal level independent thresholding, as developed by Donoho and Johnstone. The entire signal processing technique was automated so that no user intervention was needed to reconstruct the images. The signals were backprojected using the automated wavelet processing software and showed reconstruction using denoised signals improved image quality by 21%, using a relative 2-norm difference scheme.

  8. Analysis and dynamic 3D visualization of cerebral blood flow combining 3D and 4D MR image sequences

    NASA Astrophysics Data System (ADS)

    Forkert, Nils Daniel; Säring, Dennis; Fiehler, Jens; Illies, Till; Möller, Dietmar; Handels, Heinz

    2009-02-01

    In this paper we present a method for the dynamic visualization of cerebral blood flow. Spatio-temporal 4D magnetic resonance angiography (MRA) image datasets and 3D MRA datasets with high spatial resolution were acquired for the analysis of arteriovenous malformations (AVMs). One of the main tasks is the combination of the information of the 3D and 4D MRA image sequences. Initially, in the 3D MRA dataset the vessel system is segmented and a 3D surface model is generated. Then, temporal intensity curves are analyzed voxelwise in the 4D MRA image sequences. A curve fitting of the temporal intensity curves to a patient individual reference curve is used to extract the bolus arrival times in the 4D MRA sequences. After non-linear registration of both MRA datasets the extracted hemodynamic information is transferred to the surface model where the time points of inflow can be visualized color coded dynamically over time. The dynamic visualizations computed using the curve fitting method for the estimation of the bolus arrival times were rated superior compared to those computed using conventional approaches for bolus arrival time estimation. In summary the procedure suggested allows a dynamic visualization of the individual hemodynamic situation and better understanding during the visual evaluation of cerebral vascular diseases.

  9. Exploring the impact of wavelet-based denoising in the classification of remote sensing hyperspectral images

    NASA Astrophysics Data System (ADS)

    Quesada-Barriuso, Pablo; Heras, Dora B.; Argüello, Francisco

    2016-10-01

    The classification of remote sensing hyperspectral images for land cover applications is a very intensive topic. In the case of supervised classification, Support Vector Machines (SVMs) play a dominant role. Recently, the Extreme Learning Machine algorithm (ELM) has been extensively used. The classification scheme previously published by the authors, and called WT-EMP, introduces spatial information in the classification process by means of an Extended Morphological Profile (EMP) that is created from features extracted by wavelets. In addition, the hyperspectral image is denoised in the 2-D spatial domain, also using wavelets and it is joined to the EMP via a stacked vector. In this paper, the scheme is improved achieving two goals. The first one is to reduce the classification time while preserving the accuracy of the classification by using ELM instead of SVM. The second one is to improve the accuracy results by performing not only a 2-D denoising for every spectral band, but also a previous additional 1-D spectral signature denoising applied to each pixel vector of the image. For each denoising the image is transformed by applying a 1-D or 2-D wavelet transform, and then a NeighShrink thresholding is applied. Improvements in terms of classification accuracy are obtained, especially for images with close regions in the classification reference map, because in these cases the accuracy of the classification in the edges between classes is more relevant.

  10. 3D Soil Images Structure Quantification using Relative Entropy

    NASA Astrophysics Data System (ADS)

    Tarquis, A. M.; Gonzalez-Nieto, P. L.; Bird, N. R. A.

    2012-04-01

    Soil voids manifest the cumulative effect of local pedogenic processes and ultimately influence soil behavior - especially as it pertains to aeration and hydrophysical properties. Because of the relatively weak attenuation of X-rays by air, compared with liquids or solids, non-disruptive CT scanning has become a very attractive tool for generating three-dimensional imagery of soil voids. One of the main steps involved in this analysis is the thresholding required to transform the original (greyscale) images into the type of binary representation (e.g., pores in white, solids in black) needed for fractal analysis or simulation with Lattice-Boltzmann models (Baveye et al., 2010). The objective of the current work is to apply an innovative approach to quantifying soil voids and pore networks in original X-ray CT imagery using Relative Entropy (Bird et al., 2006; Tarquis et al., 2008). These will be illustrated using typical imagery representing contrasting soil structures. Particular attention will be given to the need to consider the full 3D context of the CT imagery, as well as scaling issues, in the application and interpretation of this index.

  11. Automated 3D renal segmentation based on image partitioning

    NASA Astrophysics Data System (ADS)

    Yeghiazaryan, Varduhi; Voiculescu, Irina D.

    2016-03-01

    Despite several decades of research into segmentation techniques, automated medical image segmentation is barely usable in a clinical context, and still at vast user time expense. This paper illustrates unsupervised organ segmentation through the use of a novel automated labelling approximation algorithm followed by a hypersurface front propagation method. The approximation stage relies on a pre-computed image partition forest obtained directly from CT scan data. We have implemented all procedures to operate directly on 3D volumes, rather than slice-by-slice, because our algorithms are dimensionality-independent. The results picture segmentations which identify kidneys, but can easily be extrapolated to other body parts. Quantitative analysis of our automated segmentation compared against hand-segmented gold standards indicates an average Dice similarity coefficient of 90%. Results were obtained over volumes of CT data with 9 kidneys, computing both volume-based similarity measures (such as the Dice and Jaccard coefficients, true positive volume fraction) and size-based measures (such as the relative volume difference). The analysis considered both healthy and diseased kidneys, although extreme pathological cases were excluded from the overall count. Such cases are difficult to segment both manually and automatically due to the large amplitude of Hounsfield unit distribution in the scan, and the wide spread of the tumorous tissue inside the abdomen. In the case of kidneys that have maintained their shape, the similarity range lies around the values obtained for inter-operator variability. Whilst the procedure is fully automated, our tools also provide a light level of manual editing.

  12. Comparison of bootstrap resampling methods for 3-D PET imaging.

    PubMed

    Lartizien, C; Aubin, J-B; Buvat, I

    2010-07-01

    Two groups of bootstrap methods have been proposed to estimate the statistical properties of positron emission tomography (PET) images by generating multiple statistically equivalent data sets from few data samples. The first group generates resampled data based on a parametric approach assuming that data from which resampling is performed follows a Poisson distribution while the second group consists of nonparametric approaches. These methods either require a unique original sample or a series of statistically equivalent data that can be list-mode files or sinograms. Previous reports regarding these bootstrap approaches suggest different results. This work compares the accuracy of three of these bootstrap methods for 3-D PET imaging based on simulated data. Two methods are based on a unique file, namely a list-mode based nonparametric (LMNP) method and a sinogram based parametric (SP) method. The third method is a sinogram-based nonparametric (SNP) method. Another original method (extended LMNP) was also investigated, which is an extension of the LMNP methods based on deriving a resampled list-mode file by drawings events from multiple original list-mode files. Our comparison is based on the analysis of the statistical moments estimated on the repeated and resampled data. This includes the probability density function and the moments of order 1 and 2. Results show that the two methods based on multiple original data (SNP and extended LMNP) are the only methods that correctly estimate the statistical parameters. Performances of the LMNP and SP methods are variable. Simulated data used in this study were characterized by a high noise level. Differences among the tested strategies might be reduced with clinical data sets with lower noise.

  13. Improved DCT-Based Nonlocal Means Filter for MR Images Denoising

    PubMed Central

    Hu, Jinrong; Pu, Yifei; Wu, Xi; Zhang, Yi; Zhou, Jiliu

    2012-01-01

    The nonlocal means (NLM) filter has been proven to be an efficient feature-preserved denoising method and can be applied to remove noise in the magnetic resonance (MR) images. To suppress noise more efficiently, we present a novel NLM filter based on the discrete cosine transform (DCT). Instead of computing similarity weights using the gray level information directly, the proposed method calculates similarity weights in the DCT subspace of neighborhood. Due to promising characteristics of DCT, such as low data correlation and high energy compaction, the proposed filter is naturally endowed with more accurate estimation of weights thus enhances denoising effectively. The performance of the proposed filter is evaluated qualitatively and quantitatively together with two other NLM filters, namely, the original NLM filter and the unbiased NLM (UNLM) filter. Experimental results demonstrate that the proposed filter achieves better denoising performance in MRI compared to the others. PMID:22545063

  14. Subject-specific patch-based denoising for contrast-enhanced cardiac MR images

    NASA Astrophysics Data System (ADS)

    Ma, Lorraine; Ebrahimi, Mehran; Pop, Mihaela

    2016-03-01

    Many patch-based techniques in imaging, e.g., Non-local means denoising, require tuning parameters to yield optimal results. In real-world applications, e.g., denoising of MR images, ground truth is not generally available and the process of choosing an appropriate set of parameters is a challenge. Recently, Zhu et al. proposed a method to define an image quality measure, called Q, that does not require ground truth. In this manuscript, we evaluate the effect of various parameters of the NL-means denoising on this quality metric Q. Our experiments are based on the late-gadolinium enhancement (LGE) cardiac MR images that are inherently noisy. Our described exhaustive evaluation approach can be used in tuning parameters of patch-based schemes. Even in the case that an estimation of optimal parameters is provided using another existing approach, our described method can be used as a secondary validation step. Our preliminary results suggest that denoising parameters should be case-specific rather than generic.

  15. Denoising and Multivariate Analysis of Time-Of-Flight SIMS Images

    SciTech Connect

    Wickes, Bronwyn; Kim, Y.; Castner, David G.

    2003-08-30

    Time-of-flight SIMS (ToF-SIMS) imaging offers a modality for simultaneously visualizing the spatial distribution of different surface species. However, the utility of ToF-SIMS datasets may be limited by their large size, degraded mass resolution and low ion counts per pixel. Through denoising and multivariate image analysis, regions of similar chemistries may be differentiated more readily in ToF-SIMS image data. Three established denoising algorithms down-binning, boxcar and wavelet filtering were applied to ToF-SIMS images of different surface geometries and chemistries. The effect of these filters on the performance of principal component analysis (PCA) was evaluated in terms of the capture of important chemical image features in the principal component score images, the quality of the principal component

  16. The Application of Wavelet-Domain Hidden Markov Tree Model in Diabetic Retinal Image Denoising.

    PubMed

    Cui, Dong; Liu, Minmin; Hu, Lei; Liu, Keju; Guo, Yongxin; Jiao, Qing

    2015-01-01

    The wavelet-domain Hidden Markov Tree Model can properly describe the dependence and correlation of fundus angiographic images' wavelet coefficients among scales. Based on the construction of the fundus angiographic images Hidden Markov Tree Models and Gaussian Mixture Models, this paper applied expectation-maximum algorithm to estimate the wavelet coefficients of original fundus angiographic images and the Bayesian estimation to achieve the goal of fundus angiographic images denoising. As is shown in the experimental result, compared with the other algorithms as mean filter and median filter, this method effectively improved the peak signal to noise ratio of fundus angiographic images after denoising and preserved the details of vascular edge in fundus angiographic images.

  17. Variance stabilizing transformations in patch-based bilateral filters for poisson noise image denoising.

    PubMed

    de Deckerk, Arnaud; Lee, John Aldo; Verlysen, Michel

    2009-01-01

    Denoising is a key step in the processing of medical images. It aims at improving both the interpretability and visual aspect of the images. Yet, designing a robust and efficient denoising tool remains an unsolved challenge and a specific issue concerns the noise model. Many filters typically assume that noise is additive and Gaussian, with uniform variance. In contrast, noise in medical images often has more complex properties. This paper considers images with Poissonian noise and the patch-based bilateral filters, that is, filters that involve a tonal kernel and pair wise comparisons between shifted blocks of the images. The main aim is then to integrate two variance stabilizing transformations that allow the filters to work with Gaussianized noise. The performances of these filters are compared to those of the classical bilateral filter with the same transformations. The experiments include an artificial benchmark as well as a positron emission tomography image.

  18. Image denoising using trivariate shrinkage filter in the wavelet domain and joint bilateral filter in the spatial domain.

    PubMed

    Yu, Hancheng; Zhao, Li; Wang, Haixian

    2009-10-01

    This correspondence proposes an efficient algorithm for removing Gaussian noise from corrupted image by incorporating a wavelet-based trivariate shrinkage filter with a spatial-based joint bilateral filter. In the wavelet domain, the wavelet coefficients are modeled as trivariate Gaussian distribution, taking into account the statistical dependencies among intrascale wavelet coefficients, and then a trivariate shrinkage filter is derived by using the maximum a posteriori (MAP) estimator. Although wavelet-based methods are efficient in image denoising, they are prone to producing salient artifacts such as low-frequency noise and edge ringing which relate to the structure of the underlying wavelet. On the other hand, most spatial-based algorithms output much higher quality denoising image with less artifacts. However, they are usually too computationally demanding. In order to reduce the computational cost, we develop an efficient joint bilateral filter by using the wavelet denoising result rather than directly processing the noisy image in the spatial domain. This filter could suppress the noise while preserve image details with small computational cost. Extension to color image denoising is also presented. We compare our denoising algorithm with other denoising techniques in terms of PSNR and visual quality. The experimental results indicate that our algorithm is competitive with other denoising techniques.

  19. Assessing 3D tunnel position in ACL reconstruction using a novel single image 3D-2D registration

    NASA Astrophysics Data System (ADS)

    Kang, X.; Yau, W. P.; Otake, Y.; Cheung, P. Y. S.; Hu, Y.; Taylor, R. H.

    2012-02-01

    The routinely used procedure for evaluating tunnel positions following anterior cruciate ligament (ACL) reconstructions based on standard X-ray images is known to pose difficulties in terms of obtaining accurate measures, especially in providing three-dimensional tunnel positions. This is largely due to the variability in individual knee joint pose relative to X-ray plates. Accurate results were reported using postoperative CT. However, its extensive usage in clinical routine is hampered by its major requirement of having CT scans of individual patients, which is not available for most ACL reconstructions. These difficulties are addressed through the proposed method, which aligns a knee model to X-ray images using our novel single-image 3D-2D registration method and then estimates the 3D tunnel position. In the proposed method, the alignment is achieved by using a novel contour-based 3D-2D registration method wherein image contours are treated as a set of oriented points. However, instead of using some form of orientation weighting function and multiplying it with a distance function, we formulate the 3D-2D registration as a probability density estimation using a mixture of von Mises-Fisher-Gaussian (vMFG) distributions and solve it through an expectation maximization (EM) algorithm. Compared with the ground-truth established from postoperative CT, our registration method in an experiment using a plastic phantom showed accurate results with errors of (-0.43°+/-1.19°, 0.45°+/-2.17°, 0.23°+/-1.05°) and (0.03+/-0.55, -0.03+/-0.54, -2.73+/-1.64) mm. As for the entry point of the ACL tunnel, one of the key measurements, it was obtained with high accuracy of 0.53+/-0.30 mm distance errors.

  20. Translation invariant directional framelet transform combined with Gabor filters for image denoising.

    PubMed

    Shi, Yan; Yang, Xiaoyuan; Guo, Yuhua

    2014-01-01

    This paper is devoted to the study of a directional lifting transform for wavelet frames. A nonsubsampled lifting structure is developed to maintain the translation invariance as it is an important property in image denoising. Then, the directionality of the lifting-based tight frame is explicitly discussed, followed by a specific translation invariant directional framelet transform (TIDFT). The TIDFT has two framelets ψ1, ψ2 with vanishing moments of order two and one respectively, which are able to detect singularities in a given direction set. It provides an efficient and sparse representation for images containing rich textures along with properties of fast implementation and perfect reconstruction. In addition, an adaptive block-wise orientation estimation method based on Gabor filters is presented instead of the conventional minimization of residuals. Furthermore, the TIDFT is utilized to exploit the capability of image denoising, incorporating the MAP estimator for multivariate exponential distribution. Consequently, the TIDFT is able to eliminate the noise effectively while preserving the textures simultaneously. Experimental results show that the TIDFT outperforms some other frame-based denoising methods, such as contourlet and shearlet, and is competitive to the state-of-the-art denoising approaches.

  1. Biomedical image and signal de-noising using dual tree complex wavelet transform

    NASA Astrophysics Data System (ADS)

    Rizi, F. Yousefi; Noubari, H. Ahmadi; Setarehdan, S. K.

    2011-10-01

    Dual tree complex wavelet transform(DTCWT) is a form of discrete wavelet transform, which generates complex coefficients by using a dual tree of wavelet filters to obtain their real and imaginary parts. The purposes of de-noising are reducing noise level and improving signal to noise ratio (SNR) without distorting the signal or image. This paper proposes a method for removing white Gaussian noise from ECG signals and biomedical images. The discrete wavelet transform (DWT) is very valuable in a large scope of de-noising problems. However, it has limitations such as oscillations of the coefficients at a singularity, lack of directional selectivity in higher dimensions, aliasing and consequent shift variance. The complex wavelet transform CWT strategy that we focus on in this paper is Kingsbury's and Selesnick's dual tree CWT (DTCWT) which outperforms the critically decimated DWT in a range of applications, such as de-noising. Each complex wavelet is oriented along one of six possible directions, and the magnitude of each complex wavelet has a smooth bell-shape. In the final part of this paper, we present biomedical image and signal de-noising by the means of thresholding magnitude of the wavelet coefficients.

  2. 3-D Imaging Systems for Agricultural Applications—A Review

    PubMed Central

    Vázquez-Arellano, Manuel; Griepentrog, Hans W.; Reiser, David; Paraforos, Dimitris S.

    2016-01-01

    Efficiency increase of resources through automation of agriculture requires more information about the production process, as well as process and machinery status. Sensors are necessary for monitoring the status and condition of production by recognizing the surrounding structures such as objects, field structures, natural or artificial markers, and obstacles. Currently, three dimensional (3-D) sensors are economically affordable and technologically advanced to a great extent, so a breakthrough is already possible if enough research projects are commercialized. The aim of this review paper is to investigate the state-of-the-art of 3-D vision systems in agriculture, and the role and value that only 3-D data can have to provide information about environmental structures based on the recent progress in optical 3-D sensors. The structure of this research consists of an overview of the different optical 3-D vision techniques, based on the basic principles. Afterwards, their application in agriculture are reviewed. The main focus lays on vehicle navigation, and crop and animal husbandry. The depth dimension brought by 3-D sensors provides key information that greatly facilitates the implementation of automation and robotics in agriculture. PMID:27136560

  3. 3-D Imaging Systems for Agricultural Applications-A Review.

    PubMed

    Vázquez-Arellano, Manuel; Griepentrog, Hans W; Reiser, David; Paraforos, Dimitris S

    2016-04-29

    Efficiency increase of resources through automation of agriculture requires more information about the production process, as well as process and machinery status. Sensors are necessary for monitoring the status and condition of production by recognizing the surrounding structures such as objects, field structures, natural or artificial markers, and obstacles. Currently, three dimensional (3-D) sensors are economically affordable and technologically advanced to a great extent, so a breakthrough is already possible if enough research projects are commercialized. The aim of this review paper is to investigate the state-of-the-art of 3-D vision systems in agriculture, and the role and value that only 3-D data can have to provide information about environmental structures based on the recent progress in optical 3-D sensors. The structure of this research consists of an overview of the different optical 3-D vision techniques, based on the basic principles. Afterwards, their application in agriculture are reviewed. The main focus lays on vehicle navigation, and crop and animal husbandry. The depth dimension brought by 3-D sensors provides key information that greatly facilitates the implementation of automation and robotics in agriculture.

  4. Segmented images and 3D images for studying the anatomical structures in MRIs

    NASA Astrophysics Data System (ADS)

    Lee, Yong Sook; Chung, Min Suk; Cho, Jae Hyun

    2004-05-01

    For identifying the pathological findings in MRIs, the anatomical structures in MRIs should be identified in advance. For studying the anatomical structures in MRIs, an education al tool that includes the horizontal, coronal, sagittal MRIs of entire body, corresponding segmented images, 3D images, and browsing software is necessary. Such an educational tool, however, is hard to obtain. Therefore, in this research, such an educational tool which helps medical students and doctors study the anatomical structures in MRIs was made as follows. A healthy, young Korean male adult with standard body shape was selected. Six hundred thirteen horizontal MRIs of the entire body were scanned and inputted to the personal computer. Sixty anatomical structures in the horizontal MRIs were segmented to make horizontal segmented images. Coronal, sagittal MRIs and coronal, sagittal segmented images were made. 3D images of anatomical structures in the segmented images were reconstructed by surface rendering method. Browsing software of the MRIs, segmented images, and 3D images was composed. This educational tool that includes horizontal, coronal, sagittal MRIs of entire body, corresponding segmented images, 3D images, and browsing software is expected to help medical students and doctors study anatomical structures in MRIs.

  5. 3-D Reconstruction From 2-D Radiographic Images and Its Application to Clinical Veterinary Medicine

    NASA Astrophysics Data System (ADS)

    Hamamoto, Kazuhiko; Sato, Motoyoshi

    3D imaging technique is very important and indispensable in diagnosis. The main stream of the technique is one in which 3D image is reconstructed from a set of slice images, such as X-ray CT and MRI. However, these systems require large space and high costs. On the other hand, a low cost and small size 3D imaging system is needed in clinical veterinary medicine, for example, in the case of diagnosis in X-ray car or pasture area. We propose a novel 3D imaging technique using 2-D X-ray radiographic images. This system can be realized by cheaper system than X-ray CT and enables to get 3D image in X-ray car or portable X-ray equipment. In this paper, a 3D visualization technique from 2-D radiographic images is proposed and several reconstructions are shown. These reconstructions are evaluated by veterinarians.

  6. Free segmentation in rendered 3D images through synthetic impulse response in integral imaging

    NASA Astrophysics Data System (ADS)

    Martínez-Corral, M.; Llavador, A.; Sánchez-Ortiga, E.; Saavedra, G.; Javidi, B.

    2016-06-01

    Integral Imaging is a technique that has the capability of providing not only the spatial, but also the angular information of three-dimensional (3D) scenes. Some important applications are the 3D display and digital post-processing as for example, depth-reconstruction from integral images. In this contribution we propose a new reconstruction method that takes into account the integral image and a simplified version of the impulse response function (IRF) of the integral imaging (InI) system to perform a two-dimensional (2D) deconvolution. The IRF of an InI system has a periodic structure that depends directly on the axial position of the object. Considering different periods of the IRFs we recover by deconvolution the depth information of the 3D scene. An advantage of our method is that it is possible to obtain nonconventional reconstructions by considering alternative synthetic impulse responses. Our experiments show the feasibility of the proposed method.

  7. High-Performance 3D Image Processing Architectures for Image-Guided Interventions

    DTIC Science & Technology

    2008-01-01

    Circuits and Systems, vol. 1 (2), 2007, pp. 116-127. iv • O. Dandekar, C. Castro- Pareja , and R. Shekhar, “FPGA-based real-time 3D image...How low can we go?,” presented at IEEE International Symposium on Biomedical Imaging, 2006, pp. 502-505. • C. R. Castro- Pareja , O. Dandekar, and R...Venugopal, C. R. Castro- Pareja , and O. Dandekar, “An FPGA-based 3D image processor with median and convolution filters for real-time applications,” in

  8. An unbiased risk estimator for image denoising in the presence of mixed poisson-gaussian noise.

    PubMed

    Le Montagner, Yoann; Angelini, Elsa D; Olivo-Marin, Jean-Christophe

    2014-03-01

    The behavior and performance of denoising algorithms are governed by one or several parameters, whose optimal settings depend on the content of the processed image and the characteristics of the noise, and are generally designed to minimize the mean squared error (MSE) between the denoised image returned by the algorithm and a virtual ground truth. In this paper, we introduce a new Poisson-Gaussian unbiased risk estimator (PG-URE) of the MSE applicable to a mixed Poisson-Gaussian noise model that unifies the widely used Gaussian and Poisson noise models in fluorescence bioimaging applications. We propose a stochastic methodology to evaluate this estimator in the case when little is known about the internal machinery of the considered denoising algorithm, and we analyze both theoretically and empirically the characteristics of the PG-URE estimator. Finally, we evaluate the PG-URE-driven parametrization for three standard denoising algorithms, with and without variance stabilizing transforms, and different characteristics of the Poisson-Gaussian noise mixture.

  9. Denoising of hyperspectral images by best multilinear rank approximation of a tensor

    NASA Astrophysics Data System (ADS)

    Marin-McGee, Maider; Velez-Reyes, Miguel

    2010-04-01

    The hyperspectral image cube can be modeled as a three dimensional array. Tensors and the tools of multilinear algebra provide a natural framework to deal with this type of mathematical object. Singular value decomposition (SVD) and its variants have been used by the HSI community for denoising of hyperspectral imagery. Denoising of HSI using SVD is achieved by finding a low rank approximation of a matrix representation of the hyperspectral image cube. This paper investigates similar concepts in hyperspectral denoising by using a low multilinear rank approximation the given HSI tensor representation. The Best Multilinear Rank Approximation (BMRA) of a given tensor A is to find a lower multilinear rank tensor B that is as close as possible to A in the Frobenius norm. Different numerical methods to compute the BMRA using Alternating Least Square (ALS) method and Newton's Methods over product of Grassmann manifolds are presented. The effect of the multilinear rank, the numerical method used to compute the BMRA, and different parameter choices in those methods are studied. Results show that comparable results are achievable with both ALS and Newton type methods. Also, classification results using the filtered tensor are better than those obtained either with denoising using SVD or MNF.

  10. Robust Reconstruction and Generalized Dual Hahn Moments Invariants Extraction for 3D Images

    NASA Astrophysics Data System (ADS)

    Mesbah, Abderrahim; Zouhri, Amal; El Mallahi, Mostafa; Zenkouar, Khalid; Qjidaa, Hassan

    2017-03-01

    In this paper, we introduce a new set of 3D weighed dual Hahn moments which are orthogonal on a non-uniform lattice and their polynomials are numerically stable to scale, consequent, producing a set of weighted orthonormal polynomials. The dual Hahn is the general case of Tchebichef and Krawtchouk, and the orthogonality of dual Hahn moments eliminates the numerical approximations. The computational aspects and symmetry property of 3D weighed dual Hahn moments are discussed in details. To solve their inability to invariability of large 3D images, which cause to overflow issues, a generalized version of these moments noted 3D generalized weighed dual Hahn moment invariants are presented where whose as linear combination of regular geometric moments. For 3D pattern recognition, a generalized expression of 3D weighted dual Hahn moment invariants, under translation, scaling and rotation transformations, have been proposed where a new set of 3D-GWDHMIs have been provided. In experimental studies, the local and global capability of free and noisy 3D image reconstruction of the 3D-WDHMs has been compared with other orthogonal moments such as 3D Tchebichef and 3D Krawtchouk moments using Princeton Shape Benchmark database. On pattern recognition using the 3D-GWDHMIs like 3D object descriptors, the experimental results confirm that the proposed algorithm is more robust than other orthogonal moments for pattern classification of 3D images with and without noise.

  11. Potential Cost Savings for Use of 3D Printing Combined With 3D Imaging and CPLM for Fleet Maintenance and Revitalization

    DTIC Science & Technology

    2013-12-04

    pmlkploba=obmloq=pbofbp= = = Potential Cost Savings for Use of 3D Printing Combined With 3D Imaging and CPLM for Fleet Maintenance and Revitalization...REPORT TYPE 3. DATES COVERED 00-00-2013 to 00-00-2013 4. TITLE AND SUBTITLE Potential Cost Savings for Use of 3D Printing Combined With 3D ...oÉëÉ~êÅÜ=mêçÖê~ã= ëéçåëçêÉÇ=oÉéçêí=pÉêáÉë= Potential Cost Savings for Use of 3D Printing Combined With 3D Imaging and CPLM for Fleet Maintenance and

  12. Dual-view integral imaging 3D display using polarizer parallax barriers.

    PubMed

    Wu, Fei; Wang, Qiong-Hua; Luo, Cheng-Gao; Li, Da-Hai; Deng, Huan

    2014-04-01

    We propose a dual-view integral imaging (DVII) 3D display using polarizer parallax barriers (PPBs). The DVII 3D display consists of a display panel, a microlens array, and two PPBs. The elemental images (EIs) displayed on the left and right half of the display panel are captured from two different 3D scenes, respectively. The lights emitted from two kinds of EIs are modulated by the left and right half of the microlens array to present two different 3D images, respectively. A prototype of the DVII 3D display is developed, and the experimental results agree well with the theory.

  13. Non-local neighbor embedding image denoising algorithm in sparse domain

    NASA Astrophysics Data System (ADS)

    Shi, Guo-chuan; Xia, Liang; Liu, Shuang-qing; Xu, Guo-ming

    2013-12-01

    To get better denoising results, the prior knowledge of nature images should be taken into account to regularize the ill-posed inverse problem. In this paper, we propose an image denoising algorithm via non-local similar neighbor embedding in sparse domain. Firstly, a local statistical feature, namely histograms of oriented gradients of image patches is used to perform the clustering, and then the whole training data set is partitioned into a set of subsets which have similar local geometric structures and the centroid of each subset is also obtained. Secondly, we apply the principal component analysis (PCA) to learn the compact sub-dictionary for each cluster. Next, through sparse coding over the sub-dictionary and neighborhood selecting, the image patch to be synthesized can be approximated by its top k neighbors. The extensive experimental results validate the effective of the proposed method both in PSNR and visual perception.

  14. Multiresolution parametric estimation of transparent motions and denoising of fluoroscopic images.

    PubMed

    Auvray, Vincent; Liénard, Jean; Bouthemy, Patrick

    2005-01-01

    We describe a novel multiresolution parametric framework to estimate transparent motions typically present in X-Ray exams. Assuming the presence if two transparent layers, it computes two affine velocity fields by minimizing an appropriate objective function with an incremental Gauss-Newton technique. We have designed a realistic simulation scheme of fluoroscopic image sequences to validate our method on data with ground truth and different levels of noise. An experiment on real clinical images is also reported. We then exploit this transparent-motion estimation method to denoise two layers image sequences using a motion-compensated estimation method. In accordance with theory, we show that we reach a denoising factor of 2/3 in a few iterations without bringing any local artifacts in the image sequence.

  15. Quantitative 3-D imaging topogrammetry for telemedicine applications

    NASA Technical Reports Server (NTRS)

    Altschuler, Bruce R.

    1994-01-01

    The technology to reliably transmit high-resolution visual imagery over short to medium distances in real time has led to the serious considerations of the use of telemedicine, telepresence, and telerobotics in the delivery of health care. These concepts may involve, and evolve toward: consultation from remote expert teaching centers; diagnosis; triage; real-time remote advice to the surgeon; and real-time remote surgical instrument manipulation (telerobotics with virtual reality). Further extrapolation leads to teledesign and telereplication of spare surgical parts through quantitative teleimaging of 3-D surfaces tied to CAD/CAM devices and an artificially intelligent archival data base of 'normal' shapes. The ability to generate 'topogrames' or 3-D surface numerical tables of coordinate values capable of creating computer-generated virtual holographic-like displays, machine part replication, and statistical diagnostic shape assessment is critical to the progression of telemedicine. Any virtual reality simulation will remain in 'video-game' realm until realistic dimensional and spatial relational inputs from real measurements in vivo during surgeries are added to an ever-growing statistical data archive. The challenges of managing and interpreting this 3-D data base, which would include radiographic and surface quantitative data, are considerable. As technology drives toward dynamic and continuous 3-D surface measurements, presenting millions of X, Y, Z data points per second of flexing, stretching, moving human organs, the knowledge base and interpretive capabilities of 'brilliant robots' to work as a surgeon's tireless assistants becomes imaginable. The brilliant robot would 'see' what the surgeon sees--and more, for the robot could quantify its 3-D sensing and would 'see' in a wider spectral range than humans, and could zoom its 'eyes' from the macro world to long-distance microscopy. Unerring robot hands could rapidly perform machine-aided suturing with

  16. Imaging 3D strain field monitoring during hydraulic fracturing processes

    NASA Astrophysics Data System (ADS)

    Chen, Rongzhang; Zaghloul, Mohamed A. S.; Yan, Aidong; Li, Shuo; Lu, Guanyi; Ames, Brandon C.; Zolfaghari, Navid; Bunger, Andrew P.; Li, Ming-Jun; Chen, Kevin P.

    2016-05-01

    In this paper, we present a distributed fiber optic sensing scheme to study 3D strain fields inside concrete cubes during hydraulic fracturing process. Optical fibers embedded in concrete were used to monitor 3D strain field build-up with external hydraulic pressures. High spatial resolution strain fields were interrogated by the in-fiber Rayleigh backscattering with 1-cm spatial resolution using optical frequency domain reflectometry. The fiber optics sensor scheme presented in this paper provides scientists and engineers a unique laboratory tool to understand the hydraulic fracturing processes in various rock formations and its impacts to environments.

  17. Evolution of 3D surface imaging systems in facial plastic surgery.

    PubMed

    Tzou, Chieh-Han John; Frey, Manfred

    2011-11-01

    Recent advancements in computer technologies have propelled the development of 3D imaging systems. 3D surface-imaging is taking surgeons to a new level of communication with patients; moreover, it provides quick and standardized image documentation. This article recounts the chronologic evolution of 3D surface imaging, and summarizes the current status of today's facial surface capturing technology. This article also discusses current 3D surface imaging hardware and software, and their different techniques, technologies, and scientific validation, which provides surgeons with the background information necessary for evaluating the systems and knowledge about the systems they might incorporate into their own practice.

  18. Display of travelling 3D scenes from single integral-imaging capture

    NASA Astrophysics Data System (ADS)

    Martinez-Corral, Manuel; Dorado, Adrian; Hong, Seok-Min; Sola-Pikabea, Jorge; Saavedra, Genaro

    2016-06-01

    Integral imaging (InI) is a 3D auto-stereoscopic technique that captures and displays 3D images. We present a method for easily projecting the information recorded with this technique by transforming the integral image into a plenoptic image, as well as choosing, at will, the field of view (FOV) and the focused plane of the displayed plenoptic image. Furthermore, with this method we can generate a sequence of images that simulates a camera travelling through the scene from a single integral image. The application of this method permits to improve the quality of 3D display images and videos.

  19. 3D fingerprint imaging system based on full-field fringe projection profilometry

    NASA Astrophysics Data System (ADS)

    Huang, Shujun; Zhang, Zonghua; Zhao, Yan; Dai, Jie; Chen, Chao; Xu, Yongjia; Zhang, E.; Xie, Lili

    2014-01-01

    As an unique, unchangeable and easily acquired biometrics, fingerprint has been widely studied in academics and applied in many fields over the years. The traditional fingerprint recognition methods are based on the obtained 2D feature of fingerprint. However, fingerprint is a 3D biological characteristic. The mapping from 3D to 2D loses 1D information and causes nonlinear distortion of the captured fingerprint. Therefore, it is becoming more and more important to obtain 3D fingerprint information for recognition. In this paper, a novel 3D fingerprint imaging system is presented based on fringe projection technique to obtain 3D features and the corresponding color texture information. A series of color sinusoidal fringe patterns with optimum three-fringe numbers are projected onto a finger surface. From another viewpoint, the fringe patterns are deformed by the finger surface and captured by a CCD camera. 3D shape data of the finger can be obtained from the captured fringe pattern images. This paper studies the prototype of the 3D fingerprint imaging system, including principle of 3D fingerprint acquisition, hardware design of the 3D imaging system, 3D calibration of the system, and software development. Some experiments are carried out by acquiring several 3D fingerprint data. The experimental results demonstrate the feasibility of the proposed 3D fingerprint imaging system.

  20. Lensfree diffractive tomography for the imaging of 3D cell cultures

    PubMed Central

    Momey, F.; Berdeu, A.; Bordy, T.; Dinten, J.-M.; Marcel, F. Kermarrec; Picollet-D’hahan, N.; Gidrol, X.; Allier, C.

    2016-01-01

    New microscopes are needed to help realize the full potential of 3D organoid culture studies. In order to image large volumes of 3D organoid cultures while preserving the ability to catch every single cell, we propose a new imaging platform based on lensfree microscopy. We have built a lensfree diffractive tomography setup performing multi-angle acquisitions of 3D organoid culture embedded in Matrigel and developed a dedicated 3D holographic reconstruction algorithm based on the Fourier diffraction theorem. With this new imaging platform, we have been able to reconstruct a 3D volume as large as 21.5 mm3 of a 3D organoid culture of prostatic RWPE1 cells showing the ability of these cells to assemble in 3D intricate cellular network at the mesoscopic scale. Importantly, comparisons with 2D images show that it is possible to resolve single cells isolated from the main cellular structure with our lensfree diffractive tomography setup. PMID:27231600

  1. Denoising approach for remote sensing image based on anisotropic diffusion and wavelet transform algorithm

    NASA Astrophysics Data System (ADS)

    Wang, Xiaojun; Lai, Weidong

    2011-08-01

    In this paper, a combined method have been put forward for one ASTER detected image with the wavelet filter to attenuate the noise and the anisotropic diffusion PDE(Partial Differential Equation) for further recovering image contrast. The model is verified in different noising background, since the remote sensing image usually contains salt and pepper, Gaussian as well as speckle noise. Considered the features that noise existing in wavelet domain, the wavelet filter with Bayesian estimation threshold is applied for recovering image contrast from the blurring background. The proposed PDE are performing an anisotropic diffusion in the orthogonal direction, thus preserving the edges during further denoising process. Simulation indicates that the combined algorithm can more effectively recover the blurred image from speckle and Gauss noise background than the only wavelet denoising method, while the denoising effect is also distinct when the pepper-salt noise has low intensity. The combined algorithm proposed in this article can be integrated in remote sensing image analyzing to obtain higher accuracy for environmental interpretation and pattern recognition.

  2. Volumetric medical image compression using 3D listless embedded block partitioning.

    PubMed

    Senapati, Ranjan K; Prasad, P M K; Swain, Gandharba; Shankar, T N

    2016-01-01

    This paper presents a listless variant of a modified three-dimensional (3D)-block coding algorithm suitable for medical image compression. A higher degree of correlation is achieved by using a 3D hybrid transform. The 3D hybrid transform is performed by a wavelet transform in the spatial dimension and a Karhunen-Loueve transform in the spectral dimension. The 3D transformed coefficients are arranged in a one-dimensional (1D) fashion, as in the hierarchical nature of the wavelet-coefficient distribution strategy. A novel listless block coding algorithm is applied to the mapped 1D coefficients which encode in an ordered-bit-plane fashion. The algorithm originates from the most significant bit plane and terminates at the least significant bit plane to generate an embedded bit stream, as in 3D-SPIHT. The proposed algorithm is called 3D hierarchical listless block (3D-HLCK), which exhibits better compression performance than that exhibited by 3D-SPIHT. Further, it is highly competitive with some of the state-of-the-art 3D wavelet coders for a wide range of bit rates for magnetic resonance, digital imaging and communication in medicine and angiogram images. 3D-HLCK provides rate and resolution scalability similar to those provided by 3D-SPIHT and 3D-SPECK. In addition, a significant memory reduction is achieved owing to the listless nature of 3D-HLCK.

  3. Image guidance of breast cancer surgery using 3-D ultrasound images and augmented reality visualization.

    PubMed

    Sato, Y; Nakamoto, M; Tamaki, Y; Sasama, T; Sakita, I; Nakajima, Y; Monden, M; Tamura, S

    1998-10-01

    This paper describes augmented reality visualization for the guidance of breast-conservative cancer surgery using ultrasonic images acquired in the operating room just before surgical resection. By combining an optical three-dimensional (3-D) position sensor, the position and orientation of each ultrasonic cross section are precisely measured to reconstruct geometrically accurate 3-D tumor models from the acquired ultrasonic images. Similarly, the 3-D position and orientation of a video camera are obtained to integrate video and ultrasonic images in a geometrically accurate manner. Superimposing the 3-D tumor models onto live video images of the patient's breast enables the surgeon to perceive the exact 3-D position of the tumor, including irregular cancer invasions which cannot be perceived by touch, as if it were visible through the breast skin. Using the resultant visualization, the surgeon can determine the region for surgical resection in a more objective and accurate manner, thereby minimizing the risk of a relapse and maximizing breast conservation. The system was shown to be effective in experiments using phantom and clinical data.

  4. 360 degree realistic 3D image display and image processing from real objects

    NASA Astrophysics Data System (ADS)

    Luo, Xin; Chen, Yue; Huang, Yong; Tan, Xiaodi; Horimai, Hideyoshi

    2016-12-01

    A 360-degree realistic 3D image display system based on direct light scanning method, so-called Holo-Table has been introduced in this paper. High-density directional continuous 3D motion images can be displayed easily with only one spatial light modulator. Using the holographic screen as the beam deflector, 360-degree full horizontal viewing angle was achieved. As an accompany part of the system, CMOS camera based image acquisition platform was built to feed the display engine, which can take a full 360-degree continuous imaging of the sample at the center. Customized image processing techniques such as scaling, rotation, format transformation were also developed and embedded into the system control software platform. In the end several samples were imaged to demonstrate the capability of our system.

  5. Projection domain denoising method based on dictionary learning for low-dose CT image reconstruction.

    PubMed

    Zhang, Haiyan; Zhang, Liyi; Sun, Yunshan; Zhang, Jingyu

    2015-01-01

    Reducing X-ray tube current is one of the widely used methods for decreasing the radiation dose. Unfortunately, the signal-to-noise ratio (SNR) of the projection data degrades simultaneously. To improve the quality of reconstructed images, a dictionary learning based penalized weighted least-squares (PWLS) approach is proposed for sinogram denoising. The weighted least-squares considers the statistical characteristic of noise and the penalty models the sparsity of sinogram based on dictionary learning. Then reconstruct CT image using filtered back projection (FBP) algorithm from the denoised sinogram. The proposed method is particularly suitable for the projection data with low SNR. Experimental results show that the proposed method can get high-quality CT images when the signal to noise ratio of projection data declines sharply.

  6. Denoising MR images using non-local means filter with combined patch and pixel similarity.

    PubMed

    Zhang, Xinyuan; Hou, Guirong; Ma, Jianhua; Yang, Wei; Lin, Bingquan; Xu, Yikai; Chen, Wufan; Feng, Yanqiu

    2014-01-01

    Denoising is critical for improving visual quality and reliability of associative quantitative analysis when magnetic resonance (MR) images are acquired with low signal-to-noise ratios. The classical non-local means (NLM) filter, which averages pixels weighted by the similarity of their neighborhoods, is adapted and demonstrated to effectively reduce Rician noise without affecting edge details in MR magnitude images. However, the Rician NLM (RNLM) filter usually blurs small high-contrast particle details which might be clinically relevant information. In this paper, we investigated the reason of this particle blurring problem and proposed a novel particle-preserving RNLM filter with combined patch and pixel (RNLM-CPP) similarity. The results of experiments on both synthetic and real MR data demonstrate that the proposed RNLM-CPP filter can preserve small high-contrast particle details better than the original RNLM filter while denoising MR images.

  7. Accuracy of volume measurement using 3D ultrasound and development of CT-3D US image fusion algorithm for prostate cancer radiotherapy

    SciTech Connect

    Baek, Jihye; Huh, Jangyoung; Hyun An, So; Oh, Yoonjin; Kim, Myungsoo; Kim, DongYoung; Chung, Kwangzoo; Cho, Sungho; Lee, Rena

    2013-02-15

    Purpose: To evaluate the accuracy of measuring volumes using three-dimensional ultrasound (3D US), and to verify the feasibility of the replacement of CT-MR fusion images with CT-3D US in radiotherapy treatment planning. Methods: Phantoms, consisting of water, contrast agent, and agarose, were manufactured. The volume was measured using 3D US, CT, and MR devices. A CT-3D US and MR-3D US image fusion software was developed using the Insight Toolkit library in order to acquire three-dimensional fusion images. The quality of the image fusion was evaluated using metric value and fusion images. Results: Volume measurement, using 3D US, shows a 2.8 {+-} 1.5% error, 4.4 {+-} 3.0% error for CT, and 3.1 {+-} 2.0% error for MR. The results imply that volume measurement using the 3D US devices has a similar accuracy level to that of CT and MR. Three-dimensional image fusion of CT-3D US and MR-3D US was successfully performed using phantom images. Moreover, MR-3D US image fusion was performed using human bladder images. Conclusions: 3D US could be used in the volume measurement of human bladders and prostates. CT-3D US image fusion could be used in monitoring the target position in each fraction of external beam radiation therapy. Moreover, the feasibility of replacing the CT-MR image fusion to the CT-3D US in radiotherapy treatment planning was verified.

  8. 3D imaging of telomeres and nuclear architecture: An emerging tool of 3D nano-morphology-based diagnosis.

    PubMed

    Knecht, Hans; Mai, Sabine

    2011-04-01

    Patient samples are evaluated by experienced pathologists whose diagnosis guides treating physicians. Pathological diagnoses are complex and often assisted by the application of specific tissue markers. However, cases still exist where pathologists cannot distinguish between closely related entities or determine the aggressiveness of the disease they identify under the microscope. This is due to the absence of reliable markers that define diagnostic subgroups in several cancers. Three-dimensional (3D) imaging of nuclear telomere signatures is emerging as a new tool that may change this situation offering new opportunities to the patients. This article will review current and future avenues in the assessment of diagnostic patient samples.

  9. Image denoising in bidimensional empirical mode decomposition domain: the role of Student's probability distribution function

    PubMed Central

    2015-01-01

    Hybridisation of the bi-dimensional empirical mode decomposition (BEMD) with denoising techniques has been proposed in the literature as an effective approach for image denoising. In this Letter, the Student's probability density function is introduced in the computation of the mean envelope of the data during the BEMD sifting process to make it robust to values that are far from the mean. The resulting BEMD is denoted tBEMD. In order to show the effectiveness of the tBEMD, several image denoising techniques in tBEMD domain are employed; namely, fourth order partial differential equation (PDE), linear complex diffusion process (LCDP), non-linear complex diffusion process (NLCDP), and the discrete wavelet transform (DWT). Two biomedical images and a standard digital image were considered for experiments. The original images were corrupted with additive Gaussian noise with three different levels. Based on peak-signal-to-noise ratio, the experimental results show that PDE, LCDP, NLCDP, and DWT all perform better in the tBEMD than in the classical BEMD domain. It is also found that tBEMD is faster than classical BEMD when the noise level is low. When it is high, the computational cost in terms of processing time is similar. The effectiveness of the presented approach makes it promising for clinical applications. PMID:27222723

  10. Image Denoising With Edge-Preserving and Segmentation Based on Mask NHA.

    PubMed

    Hosotani, Fumitaka; Inuzuka, Yuya; Hasegawa, Masaya; Hirobayashi, Shigeki; Misawa, Tadanobu

    2015-12-01

    In this paper, we propose a zero-mean white Gaussian noise removal method using a high-resolution frequency analysis. It is difficult to separate an original image component from a noise component when using discrete Fourier transform or discrete cosine transform for analysis because sidelobes occur in the results. The 2D non-harmonic analysis (2D NHA) is a high-resolution frequency analysis technique that improves noise removal accuracy because of its sidelobe reduction feature. However, spectra generated by NHA are distorted, because of which the signal of the image is non-stationary. In this paper, we analyze each region with a homogeneous texture in the noisy image. Non-uniform regions that occur due to segmentation are analyzed by an extended 2D NHA method called Mask NHA. We conducted an experiment using a simulation image, and found that Mask NHA denoising attains a higher peak signal-to-noise ratio (PSNR) value than the state-of-the-art methods if a suitable segmentation result can be obtained from the input image, even though parameter optimization was incomplete. This experimental result exhibits the upper limit on the value of PSNR in our Mask NHA denoising method. The performance of Mask NHA denoising is expected to approach the limit of PSNR by improving the segmentation method.

  11. A New Adaptive Diffusive Function for Magnetic Resonance Imaging Denoising Based on Pixel Similarity

    PubMed Central

    Heydari, Mostafa; Karami, Mohammad Reza

    2015-01-01

    Although there are many methods for image denoising, but partial differential equation (PDE) based denoising attracted much attention in the field of medical image processing such as magnetic resonance imaging (MRI). The main advantage of PDE-based denoising approach is laid in its ability to smooth image in a nonlinear way, which effectively removes the noise, as well as preserving edge through anisotropic diffusion controlled by the diffusive function. This function was first introduced by Perona and Malik (P-M) in their model. They proposed two functions that are most frequently used in PDE-based methods. Since these functions consider only the gradient information of a diffused pixel, they cannot remove noise in noisy images with low signal-to-noise (SNR). In this paper we propose a modified diffusive function with fractional power that is based on pixel similarity to improve P-M model for low SNR. We also will show that our proposed function will stabilize the P-M method. As experimental results show, our proposed function that is modified version of P-M function effectively improves the SNR and preserves edges more than P-M functions in low SNR. PMID:26955563

  12. Image denoising in bidimensional empirical mode decomposition domain: the role of Student's probability distribution function.

    PubMed

    Lahmiri, Salim

    2016-03-01

    Hybridisation of the bi-dimensional empirical mode decomposition (BEMD) with denoising techniques has been proposed in the literature as an effective approach for image denoising. In this Letter, the Student's probability density function is introduced in the computation of the mean envelope of the data during the BEMD sifting process to make it robust to values that are far from the mean. The resulting BEMD is denoted tBEMD. In order to show the effectiveness of the tBEMD, several image denoising techniques in tBEMD domain are employed; namely, fourth order partial differential equation (PDE), linear complex diffusion process (LCDP), non-linear complex diffusion process (NLCDP), and the discrete wavelet transform (DWT). Two biomedical images and a standard digital image were considered for experiments. The original images were corrupted with additive Gaussian noise with three different levels. Based on peak-signal-to-noise ratio, the experimental results show that PDE, LCDP, NLCDP, and DWT all perform better in the tBEMD than in the classical BEMD domain. It is also found that tBEMD is faster than classical BEMD when the noise level is low. When it is high, the computational cost in terms of processing time is similar. The effectiveness of the presented approach makes it promising for clinical applications.

  13. Seeing More Is Knowing More: V3D Enables Real-Time 3D Visualization and Quantitative Analysis of Large-Scale Biological Image Data Sets

    NASA Astrophysics Data System (ADS)

    Peng, Hanchuan; Long, Fuhui

    Everyone understands seeing more is knowing more. However, for large-scale 3D microscopic image analysis, it has not been an easy task to efficiently visualize, manipulate and understand high-dimensional data in 3D, 4D or 5D spaces. We developed a new 3D+ image visualization and analysis platform, V3D, to meet this need. The V3D system provides 3D visualization of gigabyte-sized microscopy image stacks in real time on current laptops and desktops. V3D streamlines the online analysis, measurement and proofreading of complicated image patterns by combining ergonomic functions for selecting a location in an image directly in 3D space and for displaying biological measurements, such as from fluorescent probes, using the overlaid surface objects. V3D runs on all major computer platforms and can be enhanced by software plug-ins to address specific biological problems. To demonstrate this extensibility, we built a V3Dbased application, V3D-Neuron, to reconstruct complex 3D neuronal structures from high-resolution brain images. V3D-Neuron can precisely digitize the morphology of a single neuron in a fruitfly brain in minutes, with about a 17-fold improvement in reliability and tenfold savings in time compared with other neuron reconstruction tools. Using V3D-Neuron, we demonstrate the feasibility of building a high-resolution 3D digital atlas of neurite tracts in the fruitfly brain. V3D can be easily extended using a simple-to-use and comprehensive plugin interface.

  14. Increasing the depth of field in Multiview 3D images

    NASA Astrophysics Data System (ADS)

    Lee, Beom-Ryeol; Son, Jung-Young; Yano, Sumio; Jung, Ilkwon

    2016-06-01

    A super-multiview condition simulator which can project up to four different view images to each eye is introduced. This simulator with the image having both disparity and perspective informs that the depth of field (DOF) will be extended to more than the default DOF values as the number of simultaneously but separately projected different view images to each eye increase. The DOF range can be extended to near 2 diopters with the four simultaneous view images. However, the DOF value increments are not prominent as the image with both disparity and perspective with the image with disparity only.

  15. Holographic imaging of 3D objects on dichromated polymer systems

    NASA Astrophysics Data System (ADS)

    Lemelin, Guylain; Jourdain, Anne; Manivannan, Gurusamy; Lessard, Roger A.

    1996-01-01

    Conventional volume transmission holograms of a 3D scene were recorded on dichromated poly(acrylic acid) (DCPAA) films under 488 nm light. The holographic characterization and quality of reconstruction have been studied by varying the influencing parameters such as concentration of dichromate and electron donor, and the molecular weight of the polymer matrix. Ammonium and potassium dichromate have been employed to sensitize the poly(acrylic) matrix. the recorded hologram can be efficiently reconstructed either with red light or with low energy in the blue region without any post thermal or chemical processing.

  16. 3-D Velocity Measurement of Natural Convection Using Image Processing

    NASA Astrophysics Data System (ADS)

    Shinoki, Masatoshi; Ozawa, Mamoru; Okada, Toshifumi; Kimura, Ichiro

    This paper describes quantitative three-dimensional measurement method for flow field of a rotating Rayleigh-Benard convection in a cylindrical cell heated below and cooled above. A correlation method for two-dimensional measurement was well advanced to a spatio-temporal correlation method. Erroneous vectors, often appeared in the correlation method, was successfully removed using Hopfield neural network. As a result, calculated 3-D velocity vector distribution well corresponded to the observed temperature distribution. Consequently, the simultaneous three-dimensional measurement system for temperature and flow field was developed.

  17. Fractional-order TV-L2 model for image denoising

    NASA Astrophysics Data System (ADS)

    Chen, Dali; Sun, Shenshen; Zhang, Congrong; Chen, YangQuan; Xue, Dingyu

    2013-10-01

    This paper proposes a new fractional order total variation (TV) denoising method, which provides a much more elegant and effective way of treating problems of the algorithm implementation, ill-posed inverse, regularization parameter selection and blocky effect. Two fractional order TV-L2 models are constructed for image denoising. The majorization-minimization (MM) algorithm is used to decompose these two complex fractional TV optimization problems into a set of linear optimization problems which can be solved by the conjugate gradient algorithm. The final adaptive numerical procedure is given. Finally, we report experimental results which show that the proposed methodology avoids the blocky effect and achieves state-of-the-art performance. In addition, two medical image processing experiments are presented to demonstrate the validity of the proposed methodology.

  18. A joint inter- and intrascale statistical model for Bayesian wavelet based image denoising.

    PubMed

    Pizurica, Aleksandra; Philips, Wilfried; Lemahieu, Ignace; Acheroy, Marc

    2002-01-01

    This paper presents a new wavelet-based image denoising method, which extends a "geometrical" Bayesian framework. The new method combines three criteria for distinguishing supposedly useful coefficients from noise: coefficient magnitudes, their evolution across scales and spatial clustering of large coefficients near image edges. These three criteria are combined in a Bayesian framework. The spatial clustering properties are expressed in a prior model. The statistical properties concerning coefficient magnitudes and their evolution across scales are expressed in a joint conditional model. The three main novelties with respect to related approaches are (1) the interscale-ratios of wavelet coefficients are statistically characterized and different local criteria for distinguishing useful coefficients from noise are evaluated, (2) a joint conditional model is introduced, and (3) a novel anisotropic Markov random field prior model is proposed. The results demonstrate an improved denoising performance over related earlier techniques.

  19. Laplacian based non-local means denoising of MR images with Rician noise.

    PubMed

    Bhujle, Hemalata V; Chaudhuri, Subhasis

    2013-11-01

    Magnetic Resonance (MR) image is often corrupted with a complex white Gaussian noise (Rician noise) which is signal dependent. Considering the special characteristics of Rician noise, we carry out nonlocal means denoising on squared magnitude images and compensate the introduced bias. In this paper, we propose an algorithm which not only preserves the edges and fine structures but also performs efficient denoising. For this purpose we have used a Laplacian of Gaussian (LoG) filter in conjunction with a nonlocal means filter (NLM). Further, to enhance the edges and to accelerate the filtering process, only a few similar patches have been preselected on the basis of closeness in edge and inverted mean values. Experiments have been conducted on both simulated and clinical data sets. The qualitative and quantitative measures demonstrate the efficacy of the proposed method.

  20. D3D augmented reality imaging system: proof of concept in mammography

    PubMed Central

    Douglas, David B; Petricoin, Emanuel F; Liotta, Lance; Wilson, Eugene

    2016-01-01

    Purpose The purpose of this article is to present images from simulated breast microcalcifications and assess the pattern of the microcalcifications with a technical development called “depth 3-dimensional (D3D) augmented reality”. Materials and methods A computer, head display unit, joystick, D3D augmented reality software, and an in-house script of simulated data of breast microcalcifications in a ductal distribution were used. No patient data was used and no statistical analysis was performed. Results The D3D augmented reality system demonstrated stereoscopic depth perception by presenting a unique image to each eye, focal point convergence, head position tracking, 3D cursor, and joystick fly-through. Conclusion The D3D augmented reality imaging system offers image viewing with depth perception and focal point convergence. The D3D augmented reality system should be tested to determine its utility in clinical practice. PMID:27563261

  1. Dual-Color 3D Superresolution Microscopy by Combined Spectral-Demixing and Biplane Imaging

    PubMed Central

    Winterflood, Christian M.; Platonova, Evgenia; Albrecht, David; Ewers, Helge

    2015-01-01

    Multicolor three-dimensional (3D) superresolution techniques allow important insight into the relative organization of cellular structures. While a number of innovative solutions have emerged, multicolor 3D techniques still face significant technical challenges. In this Letter we provide a straightforward approach to single-molecule localization microscopy imaging in three dimensions and two colors. We combine biplane imaging and spectral-demixing, which eliminates a number of problems, including color cross-talk, chromatic aberration effects, and problems with color registration. We present 3D dual-color images of nanoscopic structures in hippocampal neurons with a 3D compound resolution routinely achieved only in a single color. PMID:26153696

  2. 3D fluorescence anisotropy imaging using selective plane illumination microscopy

    PubMed Central

    Hedde, Per Niklas; Ranjit, Suman; Gratton, Enrico

    2015-01-01

    Fluorescence anisotropy imaging is a popular method to visualize changes in organization and conformation of biomolecules within cells and tissues. In such an experiment, depolarization effects resulting from differences in orientation, proximity and rotational mobility of fluorescently labeled molecules are probed with high spatial resolution. Fluorescence anisotropy is typically imaged using laser scanning and epifluorescence-based approaches. Unfortunately, those techniques are limited in either axial resolution, image acquisition speed, or by photobleaching. In the last decade, however, selective plane illumination microscopy has emerged as the preferred choice for three-dimensional time lapse imaging combining axial sectioning capability with fast, camera-based image acquisition, and minimal light exposure. We demonstrate how selective plane illumination microscopy can be utilized for three-dimensional fluorescence anisotropy imaging of live cells. We further examined the formation of focal adhesions by three-dimensional time lapse anisotropy imaging of CHO-K1 cells expressing an EGFP-paxillin fusion protein. PMID:26368202

  3. Reconstruction of 3d Digital Image of Weepingforsythia Pollen

    NASA Astrophysics Data System (ADS)

    Liu, Dongwu; Chen, Zhiwei; Xu, Hongzhi; Liu, Wenqi; Wang, Lina

    Confocal microscopy, which is a major advance upon normal light microscopy, has been used in a number of scientific fields. By confocal microscopy techniques, cells and tissues can be visualized deeply, and three-dimensional images created. Compared with conventional microscopes, confocal microscope improves the resolution of images by eliminating out-of-focus light. Moreover, confocal microscope has a higher level of sensitivity due to highly sensitive light detectors and the ability to accumulate images captured over time. In present studies, a series of Weeping Forsythia pollen digital images (35 images in total) were acquired with confocal microscope, and the three-dimensional digital image of the pollen reconstructed with confocal microscope. Our results indicate that it's a very easy job to analysis threedimensional digital image of the pollen with confocal microscope and the probe Acridine orange (AO).

  4. [A fast non-local means algorithm for denoising of computed tomography images].

    PubMed

    Kang, Changqing; Cao, Wenping; Fang, Lei; Hua, Li; Cheng, Hong

    2012-11-01

    A fast non-local means image denoising algorithm is presented based on the single motif of existing computed tomography images in medical archiving systems. The algorithm is carried out in two steps of prepossessing and actual possessing. The sample neighborhood database is created via the data structure of locality sensitive hashing in the prepossessing stage. The CT image noise is removed by non-local means algorithm based on the sample neighborhoods accessed fast by locality sensitive hashing. The experimental results showed that the proposed algorithm could greatly reduce the execution time, as compared to NLM, and effectively preserved the image edges and details.

  5. 3D image display of fetal ultrasonic images by thin shell

    NASA Astrophysics Data System (ADS)

    Wang, Shyh-Roei; Sun, Yung-Nien; Chang, Fong-Ming; Jiang, Ching-Fen

    1999-05-01

    Due to the properties of convenience and non-invasion, ultrasound has become an essential tool for diagnosis of fetal abnormality during women pregnancy in obstetrics. However, the 'noisy and blurry' nature of ultrasound data makes the rendering of the data a challenge in comparison with MRI and CT images. In spite of the speckle noise, the unwanted objects usually occlude the target to be observed. In this paper, we proposed a new system that can effectively depress the speckle noise, extract the target object, and clearly render the 3D fetal image in almost real-time from 3D ultrasound image data. The system is based on a deformable model that detects contours of the object according to the local image feature of ultrasound. Besides, in order to accelerate rendering speed, a thin shell is defined to separate the observed organ from unrelated structures depending on those detected contours. In this way, we can support quick 3D display of ultrasound, and the efficient visualization of 3D fetal ultrasound thus becomes possible.

  6. 3D image reconstruction algorithms for cryo-electron-microscopy images of virus particles

    NASA Astrophysics Data System (ADS)

    Doerschuk, Peter C.; Johnson, John E.

    2000-11-01

    A statistical model for the object and the complete image formation process in cryo electron microscopy of viruses is presented. Using this model, maximum likelihood reconstructions of the 3D structure of viruses are computed using the expectation maximization algorithm and an example based on Cowpea mosaic virus is provided.

  7. Infrared imaging of the polymer 3D-printing process

    NASA Astrophysics Data System (ADS)

    Dinwiddie, Ralph B.; Kunc, Vlastimil; Lindal, John M.; Post, Brian; Smith, Rachel J.; Love, Lonnie; Duty, Chad E.

    2014-05-01

    Both mid-wave and long-wave IR cameras are used to measure various temperature profiles in thermoplastic parts as they are printed. Two significantly different 3D-printers are used in this study. The first is a small scale commercially available Solidoodle 3 printer, which prints parts with layer thicknesses on the order of 125μm. The second printer used is a "Big Area Additive Manufacturing" (BAAM) 3D-printer developed at Oak Ridge National Laboratory. The BAAM prints parts with a layer thicknesses of 4.06 mm. Of particular interest is the temperature of the previously deposited layer as the new hot layer is about to be extruded onto it. The two layers are expected have a stronger bond if the temperature of the substrate layer is above the glass transition temperature. This paper describes the measurement technique and results for a study of temperature decay and substrate layer temperature for ABS thermoplastic with and without the addition of chopped carbon fibers.

  8. Multi-layer 3D imaging using a few viewpoint images and depth map

    NASA Astrophysics Data System (ADS)

    Suginohara, Hidetsugu; Sakamoto, Hirotaka; Yamanaka, Satoshi; Suyama, Shiro; Yamamoto, Hirotsugu

    2015-03-01

    In this paper, we propose a new method that makes multi-layer images from a few viewpoint images to display a 3D image by the autostereoscopic display that has multiple display screens in the depth direction. We iterate simple "Shift and Subtraction" processes to make each layer image alternately. The image made in accordance with depth map like a volume slicing by gradations is used as the initial solution of iteration process. Through the experiments using the prototype stacked two LCDs, we confirmed that it was enough to make multi-layer images from three viewpoint images to display a 3D image. Limiting the number of viewpoint images, the viewing area that allows stereoscopic view becomes narrow. To broaden the viewing area, we track the head motion of the viewer and update screen images in real time so that the viewer can maintain correct stereoscopic view within +/- 20 degrees area. In addition, we render pseudo multiple viewpoint images using depth map, then we can generate motion parallax at the same time.

  9. Research in Image Understanding as Applied to 3-D Microwave Tomographic Imaging with Near Optical Resolution.

    DTIC Science & Technology

    1986-03-10

    Severe Clutter .... ........ 1I-i III . Optical Implementation of the HopfieldModel .I -? .- . ." Model........................ . . BY...can be employed in future broad-band imaging radar networks capable of providing 3-D projective or . - tomographic images of remote aerospace targets...We expect the results of this effort to tell us how to achieve centimeter resolution on remote aerospace objects cost-effectively using microwave

  10. 3-D Target Location from Stereoscopic SAR Images

    SciTech Connect

    DOERRY,ARMIN W.

    1999-10-01

    SAR range-Doppler images are inherently 2-dimensional. Targets with a height offset lay over onto offset range and azimuth locations. Just which image locations are laid upon depends on the imaging geometry, including depression angle, squint angle, and target bearing. This is the well known layover phenomenon. Images formed with different aperture geometries will exhibit different layover characteristics. These differences can be exploited to ascertain target height information, in a stereoscopic manner. Depending on the imaging geometries, height accuracy can be on the order of horizontal position accuracies, thereby rivaling the best IFSAR capabilities in fine resolution SAR images. All that is required for this to work are two distinct passes with suitably different geometries from any plain old SAR.

  11. 3D integral imaging using diffractive Fresnel lens arrays.

    PubMed

    Hain, Mathias; von Spiegel, Wolff; Schmiedchen, Marc; Tschudi, Theo; Javidi, Bahram

    2005-01-10

    We present experimental results with binary amplitude Fresnel lens arrays and binary phase Fresnel lens arrays used to implement integral imaging systems. Their optical performance is compared with high quality refractive microlens arrays and pinhole arrays in terms of image quality, color distortion and contrast. Additionally, we show the first experimental results of lens arrays with different focal lengths in integral imaging, and discuss their ability to simultaneously increase both the depth of focus and the field of view.

  12. Real-time computer-generated integral imaging and 3D image calibration for augmented reality surgical navigation.

    PubMed

    Wang, Junchen; Suenaga, Hideyuki; Liao, Hongen; Hoshi, Kazuto; Yang, Liangjing; Kobayashi, Etsuko; Sakuma, Ichiro

    2015-03-01

    Autostereoscopic 3D image overlay for augmented reality (AR) based surgical navigation has been studied and reported many times. For the purpose of surgical overlay, the 3D image is expected to have the same geometric shape as the original organ, and can be transformed to a specified location for image overlay. However, how to generate a 3D image with high geometric fidelity and quantitative evaluation of 3D image's geometric accuracy have not been addressed. This paper proposes a graphics processing unit (GPU) based computer-generated integral imaging pipeline for real-time autostereoscopic 3D display, and an automatic closed-loop 3D image calibration paradigm for displaying undistorted 3D images. Based on the proposed methods, a novel AR device for 3D image surgical overlay is presented, which mainly consists of a 3D display, an AR window, a stereo camera for 3D measurement, and a workstation for information processing. The evaluation on the 3D image rendering performance with 2560×1600 elemental image resolution shows the rendering speeds of 50-60 frames per second (fps) for surface models, and 5-8 fps for large medical volumes. The evaluation of the undistorted 3D image after the calibration yields sub-millimeter geometric accuracy. A phantom experiment simulating oral and maxillofacial surgery was also performed to evaluate the proposed AR overlay device in terms of the image registration accuracy, 3D image overlay accuracy, and the visual effects of the overlay. The experimental results show satisfactory image registration and image overlay accuracy, and confirm the system usability.

  13. Automatic brain MR image denoising based on texture feature-based artificial neural networks.

    PubMed

    Chang, Yu-Ning; Chang, Herng-Hua

    2015-01-01

    Noise is one of the main sources of quality deterioration not only for visual inspection but also in computerized processing in brain magnetic resonance (MR) image analysis such as tissue classification, segmentation and registration. Accordingly, noise removal in brain MR images is important for a wide variety of subsequent processing applications. However, most existing denoising algorithms require laborious tuning of parameters that are often sensitive to specific image features and textures. Automation of these parameters through artificial intelligence techniques will be highly beneficial. In the present study, an artificial neural network associated with image texture feature analysis is proposed to establish a predictable parameter model and automate the denoising procedure. In the proposed approach, a total of 83 image attributes were extracted based on four categories: 1) Basic image statistics. 2) Gray-level co-occurrence matrix (GLCM). 3) Gray-level run-length matrix (GLRLM) and 4) Tamura texture features. To obtain the ranking of discrimination in these texture features, a paired-samples t-test was applied to each individual image feature computed in every image. Subsequently, the sequential forward selection (SFS) method was used to select the best texture features according to the ranking of discrimination. The selected optimal features were further incorporated into a back propagation neural network to establish a predictable parameter model. A wide variety of MR images with various scenarios were adopted to evaluate the performance of the proposed framework. Experimental results indicated that this new automation system accurately predicted the bilateral filtering parameters and effectively removed the noise in a number of MR images. Comparing to the manually tuned filtering process, our approach not only produced better denoised results but also saved significant processing time.

  14. Realization of real-time interactive 3D image holographic display [Invited].

    PubMed

    Chen, Jhen-Si; Chu, Daping

    2016-01-20

    Realization of a 3D image holographic display supporting real-time interaction requires fast actions in data uploading, hologram calculation, and image projection. These three key elements will be reviewed and discussed, while algorithms of rapid hologram calculation will be presented with the corresponding results. Our vision of interactive holographic 3D displays will be discussed.

  15. A review of 3D/2D registration methods for image-guided interventions.

    PubMed

    Markelj, P; Tomaževič, D; Likar, B; Pernuš, F

    2012-04-01

    Registration of pre- and intra-interventional data is one of the key technologies for image-guided radiation therapy, radiosurgery, minimally invasive surgery, endoscopy, and interventional radiology. In this paper, we survey those 3D/2D data registration methods that utilize 3D computer tomography or magnetic resonance images as the pre-interventional data and 2D X-ray projection images as the intra-interventional data. The 3D/2D registration methods are reviewed with respect to image modality, image dimensionality, registration basis, geometric transformation, user interaction, optimization procedure, subject, and object of registration.

  16. Bi-sided integral imaging with 2D/3D convertibility using scattering polarizer.

    PubMed

    Yeom, Jiwoon; Hong, Keehoon; Park, Soon-gi; Hong, Jisoo; Min, Sung-Wook; Lee, Byoungho

    2013-12-16

    We propose a two-dimensional (2D) and three-dimensional (3D) convertible bi-sided integral imaging. The proposed system uses the polarization state of projected light for switching its operation mode between 2D and 3D modes. By using an optical module composed of two scattering polarizers and one linear polarizer, the proposed integral imaging system simultaneously provides 3D images with 2D background images for observers who are located in the front and the rear sides of the system. The occlusion effect between 2D images and 3D images is realized by using a compensation mask for 2D images and the elemental images. The principle of proposed system is experimentally verified.

  17. Median-modified Wiener filter provides efficient denoising, preserving spot edge and morphology in 2-DE image processing.

    PubMed

    Cannistraci, Carlo V; Montevecchi, Franco M; Alessio, Massimo

    2009-11-01

    Denoising is a fundamental early stage in 2-DE image analysis strongly influencing spot detection or pixel-based methods. A novel nonlinear adaptive spatial filter (median-modified Wiener filter, MMWF), is here compared with five well-established denoising techniques (Median, Wiener, Gaussian, and Polynomial-Savitzky-Golay filters; wavelet denoising) to suggest, by means of fuzzy sets evaluation, the best denoising approach to use in practice. Although median filter and wavelet achieved the best performance in spike and Gaussian denoising respectively, they are unsuitable for contemporary removal of different types of noise, because their best setting is noise-dependent. Vice versa, MMWF that arrived second in each single denoising category, was evaluated as the best filter for global denoising, being its best setting invariant of the type of noise. In addition, median filter eroded the edge of isolated spots and filled the space between close-set spots, whereas MMWF because of a novel filter effect (drop-off-effect) does not suffer from erosion problem, preserves the morphology of close-set spots, and avoids spot and spike fuzzyfication, an aberration encountered for Wiener filter. In our tests, MMWF was assessed as the best choice when the goal is to minimize spot edge aberrations while removing spike and Gaussian noise.

  18. 3-D ultrafast Doppler imaging applied to the noninvasive mapping of blood vessels in vivo.

    PubMed

    Provost, Jean; Papadacci, Clement; Demene, Charlie; Gennisson, Jean-Luc; Tanter, Mickael; Pernot, Mathieu

    2015-08-01

    Ultrafast Doppler imaging was introduced as a technique to quantify blood flow in an entire 2-D field of view, expanding the field of application of ultrasound imaging to the highly sensitive anatomical and functional mapping of blood vessels. We have recently developed 3-D ultrafast ultrasound imaging, a technique that can produce thousands of ultrasound volumes per second, based on a 3-D plane and diverging wave emissions, and demonstrated its clinical feasibility in human subjects in vivo. In this study, we show that noninvasive 3-D ultrafast power Doppler, pulsed Doppler, and color Doppler imaging can be used to perform imaging of blood vessels in humans when using coherent compounding of 3-D tilted plane waves. A customized, programmable, 1024-channel ultrasound system was designed to perform 3-D ultrafast imaging. Using a 32 × 32, 3-MHz matrix phased array (Vermon, Tours, France), volumes were beamformed by coherently compounding successive tilted plane wave emissions. Doppler processing was then applied in a voxel-wise fashion. The proof of principle of 3-D ultrafast power Doppler imaging was first performed by imaging Tygon tubes of various diameters, and in vivo feasibility was demonstrated by imaging small vessels in the human thyroid. Simultaneous 3-D color and pulsed Doppler imaging using compounded emissions were also applied in the carotid artery and the jugular vein in one healthy volunteer.

  19. Computation of tooth axes of existent and missing teeth from 3D CT images.

    PubMed

    Wang, Yang; Wu, Lin; Guo, Huayan; Qiu, Tiantian; Huang, Yuanliang; Lin, Bin; Wang, Lisheng

    2015-12-01

    Orientations of tooth axes are important quantitative information used in dental diagnosis and surgery planning. However, their computation is a complex problem, and the existing methods have respective limitations. This paper proposes new methods to compute 3D tooth axes from 3D CT images for existent teeth with single root or multiple roots and to estimate 3D tooth axes from 3D CT images for missing teeth. The tooth axis of a single-root tooth will be determined by segmenting the pulp cavity of the tooth and computing the principal direction of the pulp cavity, and the estimation of tooth axes of the missing teeth is modeled as an interpolation problem of some quaternions along a 3D curve. The proposed methods can either avoid the difficult teeth segmentation problem or improve the limitations of existing methods. Their effectiveness and practicality are demonstrated by experimental results of different 3D CT images from the clinic.

  20. Review of three-dimensional (3D) surface imaging for oncoplastic, reconstructive and aesthetic breast surgery.

    PubMed

    O'Connell, Rachel L; Stevens, Roger J G; Harris, Paul A; Rusby, Jennifer E

    2015-08-01

    Three-dimensional surface imaging (3D-SI) is being marketed as a tool in aesthetic breast surgery. It has recently also been studied in the objective evaluation of cosmetic outcome of oncological procedures. The aim of this review is to summarise the use of 3D-SI in oncoplastic, reconstructive and aesthetic breast surgery. An extensive literature review was undertaken to identify published studies. Two reviewers independently screened all abstracts and selected relevant articles using specific inclusion criteria. Seventy two articles relating to 3D-SI for breast surgery were identified. These covered endpoints such as image acquisition, calculations and data obtainable, comparison of 3D and 2D imaging and clinical research applications of 3D-SI. The literature provides a favourable view of 3D-SI. However, evidence of its superiority over current methods of clinical decision making, surgical planning, communication and evaluation of outcome is required before it can be accepted into mainstream practice.

  1. Clinical Study of 3D Imaging and 3D Printing Technique for Patient-Specific Instrumentation in Total Knee Arthroplasty.

    PubMed

    Qiu, Bing; Liu, Fei; Tang, Bensen; Deng, Biyong; Liu, Fang; Zhu, Weimin; Zhen, Dong; Xue, Mingyuan; Zhang, Mingjiao

    2017-01-25

    Patient-specific instrumentation (PSI) was designed to improve the accuracy of preoperative planning and postoperative prosthesis positioning in total knee arthroplasty (TKA). However, better understanding needs to be achieved due to the subtle nature of the PSI systems. In this study, 3D printing technique based on the image data of computed tomography (CT) has been utilized for optimal controlling of the surgical parameters. Two groups of TKA cases have been randomly selected as PSI group and control group with no significant difference of age and sex (p > 0.05). The PSI group is treated with 3D printed cutting guides whereas the control group is treated with conventional instrumentation (CI). By evaluating the proximal osteotomy amount, distal osteotomy amount, valgus angle, external rotation angle, and tibial posterior slope angle of patients, it can be found that the preoperative quantitative assessment and intraoperative changes can be controlled with PSI whereas CI is relied on experience. In terms of postoperative parameters, such as hip-knee-ankle (HKA), frontal femoral component (FFC), frontal tibial component (FTC), and lateral tibial component (LTC) angles, there is a significant improvement in achieving the desired implant position (p < 0.05). Assigned from the morphology of patients' knees, the PSI represents the convergence of congruent designs with current personalized treatment tools. The PSI can achieve less extremity alignment and greater accuracy of prosthesis implantation compared against control method, which indicates potential for optimal HKA, FFC, and FTC angles.

  2. Evaluation of stereoscopic 3D displays for image analysis tasks

    NASA Astrophysics Data System (ADS)

    Peinsipp-Byma, E.; Rehfeld, N.; Eck, R.

    2009-02-01

    In many application domains the analysis of aerial or satellite images plays an important role. The use of stereoscopic display technologies can enhance the image analyst's ability to detect or to identify certain objects of interest, which results in a higher performance. Changing image acquisition from analog to digital techniques entailed the change of stereoscopic visualisation techniques. Recently different kinds of digital stereoscopic display techniques with affordable prices have appeared on the market. At Fraunhofer IITB usability tests were carried out to find out (1) with which kind of these commercially available stereoscopic display techniques image analysts achieve the best performance and (2) which of these techniques achieve a high acceptance. First, image analysts were interviewed to define typical image analysis tasks which were expected to be solved with a higher performance using stereoscopic display techniques. Next, observer experiments were carried out whereby image analysts had to solve defined tasks with different visualization techniques. Based on the experimental results (performance parameters and qualitative subjective evaluations of the used display techniques) two of the examined stereoscopic display technologies were found to be very good and appropriate.

  3. Advances in automated 3-D image analyses of cell populations imaged by confocal microscopy.

    PubMed

    Ancin, H; Roysam, B; Dufresne, T E; Chestnut, M M; Ridder, G M; Szarowski, D H; Turner, J N

    1996-11-01

    Automated three-dimensional (3-D) image analysis methods are presented for rapid and effective analysis of populations of fluorescently labeled cells or nuclei in thick tissue sections that have been imaged three dimensionally using a confocal microscope. The methods presented here greatly improve upon our earlier work (Roysam et al.:J Microsc 173: 115-126, 1994). The principal advances reported are: algorithms for efficient data pre-processing and adaptive segmentation, effective handling of image anisotrophy, and fast 3-D morphological algorithms for separating overlapping or connected clusters utilizing image gradient information whenever available. A particular feature of this method is its ability to separate densely packed and connected clusters of cell nuclei. Some of the challenges overcome in this work include the efficient and effective handling of imaging noise, anisotrophy, and large variations in image parameters such as intensity, object size, and shape. The method is able to handle significant inter-cell, intra-cell, inter-image, and intra-image variations. Studies indicate that this method is rapid, robust, and adaptable. Examples were presented to illustrate the applicability of this approach to analyzing images of nuclei from densely packed regions in thick sections of rat liver, and brain that were labeled with a fluorescent Schiff reagent.

  4. Registering preprocedure volumetric images with intraprocedure 3-D ultrasound using an ultrasound imaging model.

    PubMed

    King, A P; Rhode, K S; Ma, Y; Yao, C; Jansen, C; Razavi, R; Penney, G P

    2010-03-01

    For many image-guided interventions there exists a need to compute the registration between preprocedure image(s) and the physical space of the intervention. Real-time intraprocedure imaging such as ultrasound (US) can be used to image the region of interest directly and provide valuable anatomical information for computing this registration. Unfortunately, real-time US images often have poor signal-to-noise ratio and suffer from imaging artefacts. Therefore, registration using US images can be challenging and significant preprocessing is often required to make the registrations robust. In this paper we present a novel technique for computing the image-to-physical registration for minimally invasive cardiac interventions using 3-D US. Our technique uses knowledge of the physics of the US imaging process to reduce the amount of preprocessing required on the 3-D US images. To account for the fact that clinical US images normally undergo significant image processing before being exported from the US machine our optimization scheme allows the parameters of the US imaging model to vary. We validated our technique by computing rigid registrations for 12 cardiac US/magnetic resonance imaging (MRI) datasets acquired from six volunteers and two patients. The technique had mean registration errors of 2.1-4.4 mm, and 75% capture ranges of 5-30 mm. We also demonstrate how the same approach can be used for respiratory motion correction: on 15 datasets acquired from five volunteers the registration errors due to respiratory motion were reduced by 45%-92%.

  5. Image processing and 3D visualization in forensic pathologic examination

    NASA Astrophysics Data System (ADS)

    Oliver, William R.; Altschuler, Bruce R.

    1996-02-01

    The use of image processing is becoming increasingly important in the evaluation of violent crime. While much work has been done in the use of these techniques for forensic purposes outside of forensic pathology, its use in the pathologic examination of wounding has been limited. We are investigating the use of image processing and three-dimensional visualization in the analysis of patterned injuries and tissue damage. While image processing will never replace classical understanding and interpretation of how injuries develop and evolve, it can be a useful tool in helping an observer notice features in an image, may help provide correlation of surface to deep tissue injury, and provide a mechanism for the development of a metric for analyzing how likely it may be that a given object may have caused a given wound. We are also exploring methods of acquiring three-dimensional data for such measurements, which is the subject of a second paper.

  6. Online reconstruction of 3D magnetic particle imaging data

    NASA Astrophysics Data System (ADS)

    Knopp, T.; Hofmann, M.

    2016-06-01

    Magnetic particle imaging is a quantitative functional imaging technique that allows imaging of the spatial distribution of super-paramagnetic iron oxide particles at high temporal resolution. The raw data acquisition can be performed at frame rates of more than 40 volumes s-1. However, to date image reconstruction is performed in an offline step and thus no direct feedback is available during the experiment. Considering potential interventional applications such direct feedback would be mandatory. In this work, an online reconstruction framework is implemented that allows direct visualization of the particle distribution on the screen of the acquisition computer with a latency of about 2 s. The reconstruction process is adaptive and performs block-averaging in order to optimize the signal quality for a given amount of reconstruction time.

  7. IMPROMPTU: a system for automatic 3D medical image-analysis.

    PubMed

    Sundaramoorthy, G; Hoford, J D; Hoffman, E A; Higgins, W E

    1995-01-01

    The utility of three-dimensional (3D) medical imaging is hampered by difficulties in extracting anatomical regions and making measurements in 3D images. Presently, a user is generally forced to use time-consuming, subjective, manual methods, such as slice tracing and region painting, to define regions of interest. Automatic image-analysis methods can ameliorate the difficulties of manual methods. This paper describes a graphical user interface (GUI) system for constructing automatic image-analysis processes for 3D medical-imaging applications. The system, referred to as IMPROMPTU, provides a user-friendly environment for prototyping, testing and executing complex image-analysis processes. IMPROMPTU can stand alone or it can interact with an existing graphics-based 3D medical image-analysis package (VIDA), giving a strong environment for 3D image-analysis, consisting of tools for visualization, manual interaction, and automatic processing. IMPROMPTU links to a large library of 1D, 2D, and 3D image-processing functions, referred to as VIPLIB, but a user can easily link in custom-made functions. 3D applications of the system are given for left-ventricular chamber, myocardial, and upper-airway extractions.

  8. Segmentation and interpretation of 3D protein images

    SciTech Connect

    Leherte, L.; Baxter, K.; Glasgow, J.; Fortier, S.

    1994-12-31

    The segmentation and interpretation of three-dimensional images of proteins is considered. A topological approach is used to represent a protein structure as a spanning tree of critical points, where each critical point corresponds to a residue or the connectivity between residues. The critical points are subsequently analyzed to recognize secondary structure motifs within the protein. Results of applying the approach to ideal and experimental images of proteins at medium resolution are presented.

  9. Cytology 3D structure formation based on optical microscopy images

    NASA Astrophysics Data System (ADS)

    Pronichev, A. N.; Polyakov, E. V.; Shabalova, I. P.; Djangirova, T. V.; Zaitsev, S. M.

    2017-01-01

    The article the article is devoted to optimization of the parameters of imaging of biological preparations in optical microscopy using a multispectral camera in visible range of electromagnetic radiation. A model for the image forming of virtual preparations was proposed. The optimum number of layers was determined for the object scan in depth and holistic perception of its switching according to the results of the experiment.

  10. 3D ultrasound image segmentation using multiple incomplete feature sets

    NASA Astrophysics Data System (ADS)

    Fan, Liexiang; Herrington, David M.; Santago, Peter, II

    1999-05-01

    We use three features, the intensity, texture and motion to obtain robust results for segmentation of intracoronary ultrasound images. Using a parameterized equation to describe the lumen-plaque and media-adventitia boundaries, we formulate the segmentation as a parameter estimation through a cost functional based on the posterior probability, which can handle the incompleteness of the features in ultrasound images by employing outlier detection.

  11. Improved 3D cellular imaging by multispectral focus assessment

    NASA Astrophysics Data System (ADS)

    Zhao, Tong; Xiong, Yizhi; Chung, Alice P.; Wachman, Elliot S.; Farkas, Daniel L.

    2005-03-01

    Biological specimens are three-dimensional structures. However, when capturing their images through a microscope, there is only one plane in the field of view that is in focus, and out-of-focus portions of the specimen affect image quality in the in-focus plane. It is well-established that the microscope"s point spread function (PSF) can be used for blur quantitation, for the restoration of real images. However, this is an ill-posed problem, with no unique solution and with high computational complexity. In this work, instead of estimating and using the PSF, we studied focus quantitation in multi-spectral image sets. A gradient map we designed was used to evaluate the sharpness degree of each pixel, in order to identify blurred areas not to be considered. Experiments with realistic multi-spectral Pap smear images showed that measurement of their sharp gradients can provide depth information roughly comparable to human perception (through a microscope), while avoiding PSF estimation. Spectrum and morphometrics-based statistical analysis for abnormal cell detection can then be implemented in an image database where the axial structure has been refined.

  12. Photon counting passive 3D image sensing for automatic target recognition.

    PubMed

    Yeom, Seokwon; Javidi, Bahram; Watson, Edward

    2005-11-14

    In this paper, we propose photon counting three-dimensional (3D) passive sensing and object recognition using integral imaging. The application of this approach to 3D automatic target recognition (ATR) is investigated using both linear and nonlinear matched filters. We find there is significant potential of the proposed system for 3D sensing and recognition with a low number of photons. The discrimination capability of the proposed system is quantified in terms of discrimination ratio, Fisher ratio, and receiver operating characteristic (ROC) curves. To the best of our knowledge, this is the first report on photon counting 3D passive sensing and ATR with integral imaging.

  13. ICER-3D: A Progressive Wavelet-Based Compressor for Hyperspectral Images

    NASA Technical Reports Server (NTRS)

    Kiely, A.; Klimesh, M.; Xie, H.; Aranki, N.

    2005-01-01

    ICER-3D is a progressive, wavelet-based compressor for hyperspectral images. ICER-3D is derived from the ICER image compressor. ICER-3D can provide lossless and lossy compression, and incorporates an error-containment scheme to limit the effects of data loss during transmission. The three-dimensional wavelet decomposition structure used by ICER-3D exploits correlations in all three dimensions of hyperspectral data sets, while facilitating elimination of spectral ringing artifacts. Correlation is further exploited by a context modeler that effectively exploits spectral dependencies in the wavelet-transformed hyperspectral data. Performance results illustrating the benefits of these features are presented.

  14. Real-time auto-stereoscopic visualization of 3D medical images

    NASA Astrophysics Data System (ADS)

    Portoni, Luisa; Patak, Alexandre; Noirard, Pierre; Grossetie, Jean-Claude; van Berkel, Cees

    2000-04-01

    The work here described regards multi-viewer auto- stereoscopic visualization of 3D models of anatomical structures and organs of the human body. High-quality 3D models of more than 1600 anatomical structures have been reconstructed using the Visualization Toolkit, a freely available C++ class library for 3D graphics and visualization. 2D images used for 3D reconstruction comes from the Visible Human Data Set. Auto-stereoscopic 3D image visualization is obtained using a prototype monitor developed at Philips Research Labs, UK. This special multiview 3D-LCD screen has been connected directly to a SGI workstation, where 3D reconstruction and medical imaging applications are executed. Dedicated software has been developed to implement multiview capability. A number of static or animated contemporary views of the same object can simultaneously be seen on the 3D-LCD screen by several observers, having a real 3D perception of the visualized scene without the use of extra media as dedicated glasses or head-mounted displays. Developed software applications allow real-time interaction with visualized 3D models, didactical animations and movies have been realized as well.

  15. Contactless operating table control based on 3D image processing.

    PubMed

    Schröder, Stephan; Loftfield, Nina; Langmann, Benjamin; Frank, Klaus; Reithmeier, Eduard

    2014-01-01

    Interaction with mobile consumer devices leads to a higher acceptance and affinity of persons to natural user interfaces and perceptional interaction possibilities. New interaction modalities become accessible and are capable to improve human machine interaction even in complex and high risk environments, like the operation room. Here, manifold medical disciplines cause a great variety of procedures and thus staff and equipment. One universal challenge is to meet the sterility requirements, for which common contact-afflicted remote interfaces always pose a potential risk causing a hazard for the process. The proposed operating table control system overcomes this process risk and thus improves the system usability significantly. The 3D sensor system, the Microsoft Kinect, captures the motion of the user, allowing a touchless manipulation of an operating table. Three gestures enable the user to select, activate and manipulate all segments of the motorised system in a safe and intuitive way. The gesture dynamics are synchronised with the table movement. In a usability study, 15 participants evaluated the system with a system usability score by Broke of 79. This states a high potential for implementation and acceptance in interventional environments. In the near future, even processes with higher risks could be controlled with the proposed interface, while interfaces become safer and more direct.

  16. Computer acquisition of 3D images utilizing dynamic speckles

    NASA Astrophysics Data System (ADS)

    Kamshilin, Alexei A.; Semenov, Dmitry V.; Nippolainen, Ervin; Raita, Erik

    2006-05-01

    We present novel technique for fast non-contact and continuous profile measurements of rough surfaces by use of dynamic speckles. The dynamic speckle pattern is generated when the laser beam scans the surface under study. The most impressive feature of the proposed technique is its ability to work at extremely high scanning speed of hundreds meters per second. The technique is based on the continuous frequency measurements of the light-power modulation after spatial filtering of the scattered light. The complete optical-electronic system was designed and fabricated for fast measurement of the speckles velocity, its recalculation into the distance, and further data acquisition into computer. The measured surface profile is displayed in a PC monitor in real time. The response time of the measuring system is below 1 μs. Important parameters of the system such as accuracy, range of measurements, and spatial resolution are analyzed. Limits of the spatial filtering technique used for continuous tracking of the speckle-pattern velocity are shown. Possible ways of further improvement of the measurements accuracy are demonstrated. Owing to its extremely fast operation, the proposed technique could be applied for online control of the 3D-shape of complex objects (e.g., electronic circuits) during their assembling.

  17. Image quality of a cone beam O-arm 3D imaging system

    NASA Astrophysics Data System (ADS)

    Zhang, Jie; Weir, Victor; Lin, Jingying; Hsiung, Hsiang; Ritenour, E. Russell

    2009-02-01

    The O-arm is a cone beam imaging system designed primarily to support orthopedic surgery and is also used for image-guided and vascular surgery. Using a gantry that can be opened or closed, the O-arm can function as a 2-dimensional (2D) fluoroscopy device or collect 3-dimensional (3D) volumetric imaging data like a CT system. Clinical applications of the O-arm in spine surgical procedures, assessment of pedicle screw position, and kyphoplasty procedures show that the O-arm 3D mode provides enhanced imaging information compared to radiographs or fluoroscopy alone. In this study, the image quality of an O-arm system was quantitatively evaluated. A 20 cm diameter CATPHAN 424 phantom was scanned using the pre-programmed head protocols: small/medium (120 kVp, 100 mAs), large (120 kVp, 128 mAs), and extra-large (120 kVp, 160 mAs) in 3D mode. High resolution reconstruction mode (512×512×0.83 mm) was used to reconstruct images for the analysis of low and high contrast resolution, and noise power spectrum. MTF was measured using the point spread function. The results show that the O-arm image is uniform but with a noise pattern which cannot be removed by simply increasing the mAs. The high contrast resolution of the O-arm system was approximately 9 lp/cm. The system has a 10% MTF at 0.45 mm. The low-contrast resolution cannot be decided due to the noise pattern. For surgery where locations of a structure are emphasized over a survey of all image details, the image quality of the O-arm is well accepted clinically.

  18. Air-touch interaction system for integral imaging 3D display

    NASA Astrophysics Data System (ADS)

    Dong, Han Yuan; Xiang, Lee Ming; Lee, Byung Gook

    2016-07-01

    In this paper, we propose an air-touch interaction system for the tabletop type integral imaging 3D display. This system consists of the real 3D image generation system based on integral imaging technique and the interaction device using a real-time finger detection interface. In this system, we used multi-layer B-spline surface approximation to detect the fingertip and gesture easily in less than 10cm height from the screen via input the hand image. The proposed system can be used in effective human computer interaction method for the tabletop type 3D display.

  19. Space Radar Image Isla Isabela in 3-D

    NASA Technical Reports Server (NTRS)

    1999-01-01

    This is a three-dimensional view of Isabela, one of the Galapagos Islands located off the western coast of Ecuador, South America. This view was constructed by overlaying a Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar (SIR-C/X-SAR) image on a digital elevation map produced by TOPSAR, a prototype airborne interferometric radar which produces simultaneous image and elevation data. The vertical scale in this image is exaggerated by a factor of 1.87. The SIR-C/X-SAR image was taken on the 40th orbit of space shuttle Endeavour. The image is centered at about 0.5 degree south latitude and 91 degrees west longitude and covers an area of 75 by 60 kilometers (47 by 37 miles). The radar incidence angle at the center of the image is about 20 degrees. The western Galapagos Islands, which lie about 1,200 kilometers (750 miles)west of Ecuador in the eastern Pacific, have six active volcanoes similar to the volcanoes found in Hawaii and reflect the volcanic processes that occur where the ocean floor is created. Since the time of Charles Darwin's visit to the area in 1835, there have been more than 60 recorded eruptions on these volcanoes. This SIR-C/X-SAR image of Alcedo and Sierra Negra volcanoes shows the rougher lava flows as bright features, while ash deposits and smooth pahoehoe lava flows appear dark. Vertical exaggeration of relief is a common tool scientists use to detect relationships between structure (for example, faults, and fractures) and topography. Spaceborne Imaging Radar-C and X-Synthetic Aperture Radar (SIR-C/X-SAR) is part of NASA's Mission to Planet Earth. The radars illuminate Earth with microwaves allowing detailed observations at any time, regardless of weather or sunlight conditions. SIR-C/X-SAR uses three microwave wavelengths: L-band (24 cm), C-band (6 cm) and X-band (3 cm). The multi-frequency data will be used by the international scientific community to better understand the global environment and how it is changing. The SIR-C/X-SAR data

  20. Radar Imaging of Spheres in 3D using MUSIC

    SciTech Connect

    Chambers, D H; Berryman, J G

    2003-01-21

    We have shown that multiple spheres can be imaged by linear and planar EM arrays using only one component of polarization. The imaging approach involves calculating the SVD of the scattering response matrix, selecting a subset of singular values that represents noise, and evaluating the MUSIC functional. The noise threshold applied to the spectrum of singular values for optimal performance is typically around 1%. The resulting signal subspace includes more than one singular value per sphere. The presence of reflections from the ground improves height localization, even for a linear array parallel to the ground. However, the interference between direct and reflected energy modulates the field, creating periodic nulls that can obscure targets in typical images. These nulls are largely eliminated by normalizing the MUSIC functional with the broadside beam pattern of the array. The resulting images show excellent localization for 1 and 2 spheres. The performance for the 3 sphere configurations are complicated by shadowing effects and the greater range of the 3rd sphere in case 2. Two of the three spheres are easily located by MUSIC but the third is difficult to distinguish from other local maxima of the complex imaging functional. Improvement is seen when the linear array is replace with a planar array, which increases the effective aperture height. Further analysis of the singular values and their relationship to modes of scattering from the spheres, as well as better ways to exploit polarization, should improve performance. Work along these lines is currently being pursued by the authors.

  1. 3D-2D registration of cerebral angiograms: a method and evaluation on clinical images.

    PubMed

    Mitrovic, Uroš; Špiclin, Žiga; Likar, Boštjan; Pernuš, Franjo

    2013-08-01

    Endovascular image-guided interventions (EIGI) involve navigation of a catheter through the vasculature followed by application of treatment at the site of anomaly using live 2D projection images for guidance. 3D images acquired prior to EIGI are used to quantify the vascular anomaly and plan the intervention. If fused with the information of live 2D images they can also facilitate navigation and treatment. For this purpose 3D-2D image registration is required. Although several 3D-2D registration methods for EIGI achieve registration accuracy below 1 mm, their clinical application is still limited by insufficient robustness or reliability. In this paper, we propose a 3D-2D registration method based on matching a 3D vasculature model to intensity gradients of live 2D images. To objectively validate 3D-2D registration methods, we acquired a clinical image database of 10 patients undergoing cerebral EIGI and established "gold standard" registrations by aligning fiducial markers in 3D and 2D images. The proposed method had mean registration accuracy below 0.65 mm, which was comparable to tested state-of-the-art methods, and execution time below 1 s. With the highest rate of successful registrations and the highest capture range the proposed method was the most robust and thus a good candidate for application in EIGI.

  2. A monthly quality assurance procedure for 3D surface imaging.

    PubMed

    Wooten, H Omar; Klein, Eric E; Gokhroo, Garima; Santanam, Lakshmi

    2010-12-21

    A procedure for periodic quality assurance of a video surface imaging system is introduced. AlignRT is a video camera-based patient localization system that captures and compares images of a patient's topography to a DICOM-formatted external contour, then calculates shifts required to accurately reposition the patient. This technical note describes the tools and methods implemented in our department to verify correct and accurate operation of the AlignRT hardware and software components. The procedure described is performed monthly and complements a daily calibration of the system.

  3. 3-D capacitance density imaging of fluidized bed

    DOEpatents

    Fasching, George E.

    1990-01-01

    A three-dimensional capacitance density imaging of a gasified bed or the like in a containment vessel is achieved using a plurality of electrodes provided circumferentially about the bed in levels and along the bed in channels. The electrodes are individually and selectively excited electrically at each level to produce a plurality of current flux field patterns generated in the bed at each level. The current flux field patterns are suitably sensed and a density pattern of the bed at each level determined. By combining the determined density patterns at each level, a three-dimensional density image of the bed is achieved.

  4. A general strategy for anisotropic diffusion in MR image denoising and enhancement.

    PubMed

    Tong, Chenchen; Sun, Ying; Payet, Nicolas; Ong, Sim-Heng

    2012-12-01

    Anisotropic diffusion (AD) has proven to be very effective in the denoising of magnetic resonance (MR) images. The result of AD filtering is highly dependent on several parameters, especially the conductance parameter. However, there is no automatic method to select the optimal parameter values. This paper presents a general strategy for AD filtering of MR images using an automatic parameter selection method. The basic idea is to estimate the parameters through an optimization step on a synthetic image model, which is different from traditional analytical methods. This approach can be easily applied to more sophisticated diffusion models for better denoising results. We conducted a systematic study of parameter selection for the AD filter, including the dynamic parameter decreasing rate, the parameter selection range for different noise levels and the influence of the image contrast on parameter selection. The proposed approach was validated using both simulated and real MR images. The model image generated using our approach was shown to be highly suitable for the purpose of parameter optimization. The results confirm that our method outperforms most state-of-the-art methods in both quantitative measurement and visual evaluation. By testing on real images with different noise levels, we demonstrated that our method is sufficiently general to be applied to a variety of MR images.

  5. Realization of an aerial 3D image that occludes the background scenery.

    PubMed

    Kakeya, Hideki; Ishizuka, Shuta; Sato, Yuya

    2014-10-06

    In this paper we describe an aerial 3D image that occludes far background scenery based on coarse integral volumetric imaging (CIVI) technology. There have been many volumetric display devices that present floating 3D images, most of which have not reproduced the visual occlusion. CIVI is a kind of multilayered integral imaging and realizes an aerial volumetric image with visual occlusion by combining multiview and volumetric display technologies. The conventional CIVI, however, cannot show a deep space, for the number of layered panels is limited because of the low transmittance of each panel. To overcome this problem, we propose a novel optical design to attain an aerial 3D image that occludes far background scenery. In the proposed system, a translucent display panel with 120 Hz refresh rate is located between the CIVI system and the aerial 3D image. The system modulates between the aerial image mode and the background image mode. In the aerial image mode, the elemental images are shown on the CIVI display and the inserted translucent display is uniformly translucent. In the background image mode, the black shadows of the elemental images in a white background are shown on the CIVI display and the background scenery is displayed on the inserted translucent panel. By alternation of these two modes at 120 Hz, an aerial 3D image that visually occludes the far background scenery is perceived by the viewer.

  6. 3D spectral imaging system for anterior chamber metrology

    NASA Astrophysics Data System (ADS)

    Anderson, Trevor; Segref, Armin; Frisken, Grant; Frisken, Steven

    2015-03-01

    Accurate metrology of the anterior chamber of the eye is useful for a number of diagnostic and clinical applications. In particular, accurate corneal topography and corneal thickness data is desirable for fitting contact lenses, screening for diseases and monitoring corneal changes. Anterior OCT systems can be used to measure anterior chamber surfaces, however accurate curvature measurements for single point scanning systems are known to be very sensitive to patient movement. To overcome this problem we have developed a parallel 3D spectral metrology system that captures simultaneous A-scans on a 2D lateral grid. This approach enables estimates of the elevation and curvature of anterior and posterior corneal surfaces that are robust to sample movement. Furthermore, multiple simultaneous surface measurements greatly improve the ability to register consecutive frames and enable aggregate measurements over a finer lateral grid. A key element of our approach has been to exploit standard low cost optical components including lenslet arrays and a 2D sensor to provide a path towards low cost implementation. We demonstrate first prototypes based on 6 Mpixel sensor using a 250 μm pitch lenslet array with 300 sample beams to achieve an RMS elevation accuracy of 1μm with 95 dB sensitivity and a 7.0 mm range. Initial tests on Porcine eyes, model eyes and calibration spheres demonstrate the validity of the concept. With the next iteration of designs we expect to be able to achieve over 1000 simultaneous A-scans in excess of 75 frames per second.

  7. Registration and 3D visualization of large microscopy images

    NASA Astrophysics Data System (ADS)

    Mosaliganti, Kishore; Pan, Tony; Sharp, Richard; Ridgway, Randall; Iyengar, Srivathsan; Gulacy, Alexandra; Wenzel, Pamela; de Bruin, Alain; Machiraju, Raghu; Huang, Kun; Leone, Gustavo; Saltz, Joel

    2006-03-01

    Inactivation of the retinoblastoma gene in mouse embryos causes tissue infiltrations into critical sections of the placenta, which has been shown to affect fetal survivability. Our collaborators in cancer genetics are extremely interested in examining the three dimensional nature of these infiltrations given a stack of two dimensional light microscopy images. Three sets of wildtype and mutant placentas was sectioned serially and digitized using a commercial light microscopy scanner. Each individual placenta dataset consisted of approximately 1000 images totaling 700 GB in size, which were registered into a volumetric dataset using National Library of Medicine's (NIH/NLM) Insight Segmentation and Registration Toolkit (ITK). This paper describes our method for image registration to aid in volume visualization of tissue level intermixing for both wildtype and Rb - specimens. The registration process faces many challenges arising from the large image sizes, damages during sectioning, staining gradients both within and across sections, and background noise. These issues limit the direct application of standard registration techniques due to frequent convergence to local solutions. In this work, we develop a mixture of automated and semi-automated enhancements with ground-truth validation for the mutual information-based registration algorithm. Our final volume renderings clearly show tissue intermixing differences between both wildtype and Rb - specimens which are not obvious prior to registration.

  8. Space Radar Image of Kilauea, Hawaii in 3-D

    NASA Technical Reports Server (NTRS)

    1999-01-01

    This is a three-dimensional perspective view of a false-color image of the eastern part of the Big Island of Hawaii. It was produced using all three radar frequencies -- X-band, C-band and L-band -- from the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) flying on the space shuttle Endeavour, overlaid on a U.S. Geological Survey digital elevation map. Visible in the center of the image in blue are the summit crater (Kilauea Caldera) which contains the smaller Halemaumau Crater, and the line of collapse craters below them that form the Chain of Craters Road. The image was acquired on April 12, 1994 during orbit 52 of the space shuttle. The area shown is approximately 34 by 57 kilometers (21 by 35 miles) with the top of the image pointing toward northwest. The image is centered at about 155.25 degrees west longitude and 19.5 degrees north latitude. The false colors are created by displaying three radar channels of different frequency. Red areas correspond to high backscatter at L-HV polarization, while green areas exhibit high backscatter at C-HV polarization. Finally, blue shows high return at X-VV polarization. Using this color scheme, the rain forest appears bright on the image, while the green areas correspond to lower vegetation. The lava flows have different colors depending on their types and are easily recognizable due to their shapes. The flows at the top of the image originated from the Mauna Loa volcano. Kilauea volcano has been almost continuously active for more than the last 11 years. Field teams that were on the ground specifically to support these radar observations report that there was vigorous surface activity about 400 meters (one-quartermile) inland from the coast. A moving lava flow about 200 meters (650 feet) in length was observed at the time of the shuttle overflight, raising the possibility that subsequent images taken during this mission will show changes in the landscape. Currently, most of the lava that is

  9. High definition 3D imaging lidar system using CCD

    NASA Astrophysics Data System (ADS)

    Jo, Sungeun; Kong, Hong Jin; Bang, Hyochoong

    2016-10-01

    In this study we propose and demonstrate a novel technique for measuring distance with high definition three-dimensional imaging. To meet the stringent requirements of various missions, spatial resolution and range precision are important properties for flash LIDAR systems. The proposed LIDAR system employs a polarization modulator and a CCD. When a laser pulse is emitted from the laser, it triggers the polarization modulator. The laser pulse is scattered by the target and is reflected back to the LIDAR system while the polarization modulator is rotating. Its polarization state is a function of time. The laser-return pulse passes through the polarization modulator in a certain polarization state, and the polarization state is calculated using the intensities of the laser pulses measured by the CCD. Because the function of the time and the polarization state is already known, the polarization state can be converted to time-of-flight. By adopting a polarization modulator and a CCD and only measuring the energy of a laser pulse to obtain range, a high resolution three-dimensional image can be acquired by the proposed three-dimensional imaging LIDAR system. Since this system only measures the energy of the laser pulse, a high bandwidth detector and a high resolution TDC are not required for high range precision. The proposed method is expected to be an alternative method for many three-dimensional imaging LIDAR system applications that require high resolution.

  10. A 3-D fluorescence imaging system incorporating structured illumination technology

    NASA Astrophysics Data System (ADS)

    Antos, L.; Emord, P.; Luquette, B.; McGee, B.; Nguyen, D.; Phipps, A.; Phillips, D.; Helguera, M.

    2010-02-01

    A currently available 2-D high-resolution, optical molecular imaging system was modified by the addition of a structured illumination source, OptigridTM, to investigate the feasibility of providing depth resolution along the optical axis. The modification involved the insertion of the OptigridTM and a lens in the path between the light source and the image plane, as well as control and signal processing software. Projection of the OptigridTM onto the imaging surface at an angle, was resolved applying the Scheimpflug principle. The illumination system implements modulation of the light source and provides a framework for capturing depth resolved mages. The system is capable of in-focus projection of the OptigridTM at different spatial frequencies, and supports the use of different lenses. A calibration process was developed for the system to achieve consistent phase shifts of the OptigridTM. Post-processing extracted depth information using depth modulation analysis using a phantom block with fluorescent sheets at different depths. An important aspect of this effort was that it was carried out by a multidisciplinary team of engineering and science students as part of a capstone senior design program. The disciplines represented are mechanical engineering, electrical engineering and imaging science. The project was sponsored by a financial grant from New York State with equipment support from two industrial concerns. The students were provided with a basic imaging concept and charged with developing, implementing, testing and validating a feasible proof-of-concept prototype system that was returned to the originator of the concept for further evaluation and characterization.

  11. 3D Modeling from Multi-views Images for Cultural Heritage in Wat-Pho, Thailand

    NASA Astrophysics Data System (ADS)

    Soontranon, N.; Srestasathiern, P.; Lawawirojwong, S.

    2015-08-01

    In Thailand, there are several types of (tangible) cultural heritages. This work focuses on 3D modeling of the heritage objects from multi-views images. The images are acquired by using a DSLR camera which costs around 1,500 (camera and lens). Comparing with a 3D laser scanner, the camera is cheaper and lighter than the 3D scanner. Hence, the camera is available for public users and convenient for accessing narrow areas. The acquired images consist of various sculptures and architectures in Wat-Ph