ImageJ: Image processing and analysis in Java

NASA Astrophysics Data System (ADS)

Rasband, W. S.

2012-06-01

ImageJ is a public domain Java image processing program inspired by NIH Image. It can display, edit, analyze, process, save and print 8-bit, 16-bit and 32-bit images. It can read many image formats including TIFF, GIF, JPEG, BMP, DICOM, FITS and "raw". It supports "stacks", a series of images that share a single window. It is multithreaded, so time-consuming operations such as image file reading can be performed in parallel with other operations.

A blind deconvolution method based on L1/L2 regularization prior in the gradient space

NASA Astrophysics Data System (ADS)

Cai, Ying; Shi, Yu; Hua, Xia

2018-02-01

In the process of image restoration, the result of image restoration is very different from the real image because of the existence of noise, in order to solve the ill posed problem in image restoration, a blind deconvolution method based on L1/L2 regularization prior to gradient domain is proposed. The method presented in this paper first adds a function to the prior knowledge, which is the ratio of the L1 norm to the L2 norm, and takes the function as the penalty term in the high frequency domain of the image. Then, the function is iteratively updated, and the iterative shrinkage threshold algorithm is applied to solve the high frequency image. In this paper, it is considered that the information in the gradient domain is better for the estimation of blur kernel, so the blur kernel is estimated in the gradient domain. This problem can be quickly implemented in the frequency domain by fast Fast Fourier Transform. In addition, in order to improve the effectiveness of the algorithm, we have added a multi-scale iterative optimization method. This paper proposes the blind deconvolution method based on L1/L2 regularization priors in the gradient space can obtain the unique and stable solution in the process of image restoration, which not only keeps the edges and details of the image, but also ensures the accuracy of the results.

Optimized Setup and Protocol for Magnetic Domain Imaging with In Situ Hysteresis Measurement.

PubMed

Liu, Jun; Wilson, John; Davis, Claire; Peyton, Anthony

2017-11-07

This paper elaborates the sample preparation protocols required to obtain optimal domain patterns using the Bitter method, focusing on the extra steps compared to standard metallographic sample preparation procedures. The paper proposes a novel bespoke rig for dynamic domain imaging with in situ BH (magnetic hysteresis) measurements and elaborates the protocols for the sensor preparation and the use of the rig to ensure accurate BH measurement. The protocols for static and ordinary dynamic domain imaging (without in situ BH measurements) are also presented. The reported method takes advantage of the convenience and high sensitivity of the traditional Bitter method and enables in situ BH measurement without interrupting or interfering with the domain wall movement processes. This facilitates establishing a direct and quantitative link between the domain wall movement processes-microstructural feature interactions in ferritic steels with their BH loops. This method is anticipated to become a useful tool for the fundamental study of microstructure-magnetic property relationships in steels and to help interpret the electromagnetic sensor signals for non-destructive evaluation of steel microstructures.

Efficient Time-Domain Imaging Processing for One-Stationary Bistatic Forward-Looking SAR Including Motion Errors

PubMed Central

Xie, Hongtu; Shi, Shaoying; Xiao, Hui; Xie, Chao; Wang, Feng; Fang, Qunle

2016-01-01

With the rapid development of the one-stationary bistatic forward-looking synthetic aperture radar (OS-BFSAR) technology, the huge amount of the remote sensing data presents challenges for real-time imaging processing. In this paper, an efficient time-domain algorithm (ETDA) considering the motion errors for the OS-BFSAR imaging processing, is presented. This method can not only precisely handle the large spatial variances, serious range-azimuth coupling and motion errors, but can also greatly improve the imaging efficiency compared with the direct time-domain algorithm (DTDA). Besides, it represents the subimages on polar grids in the ground plane instead of the slant-range plane, and derives the sampling requirements considering motion errors for the polar grids to offer a near-optimum tradeoff between the imaging precision and efficiency. First, OS-BFSAR imaging geometry is built, and the DTDA for the OS-BFSAR imaging is provided. Second, the polar grids of subimages are defined, and the subaperture imaging in the ETDA is derived. The sampling requirements for polar grids are derived from the point of view of the bandwidth. Finally, the implementation and computational load of the proposed ETDA are analyzed. Experimental results based on simulated and measured data validate that the proposed ETDA outperforms the DTDA in terms of the efficiency improvement. PMID:27845757

The Dark Energy Survey Image Processing Pipeline

NASA Astrophysics Data System (ADS)

Morganson, E.; Gruendl, R. A.; Menanteau, F.; Carrasco Kind, M.; Chen, Y.-C.; Daues, G.; Drlica-Wagner, A.; Friedel, D. N.; Gower, M.; Johnson, M. W. G.; Johnson, M. D.; Kessler, R.; Paz-Chinchón, F.; Petravick, D.; Pond, C.; Yanny, B.; Allam, S.; Armstrong, R.; Barkhouse, W.; Bechtol, K.; Benoit-Lévy, A.; Bernstein, G. M.; Bertin, E.; Buckley-Geer, E.; Covarrubias, R.; Desai, S.; Diehl, H. T.; Goldstein, D. A.; Gruen, D.; Li, T. S.; Lin, H.; Marriner, J.; Mohr, J. J.; Neilsen, E.; Ngeow, C.-C.; Paech, K.; Rykoff, E. S.; Sako, M.; Sevilla-Noarbe, I.; Sheldon, E.; Sobreira, F.; Tucker, D. L.; Wester, W.; DES Collaboration

2018-07-01

The Dark Energy Survey (DES) is a five-year optical imaging campaign with the goal of understanding the origin of cosmic acceleration. DES performs a ∼5000 deg2 survey of the southern sky in five optical bands (g, r, i, z, Y) to a depth of ∼24th magnitude. Contemporaneously, DES performs a deep, time-domain survey in four optical bands (g, r, i, z) over ∼27 deg2. DES exposures are processed nightly with an evolving data reduction pipeline and evaluated for image quality to determine if they need to be retaken. Difference imaging and transient source detection are also performed in the time domain component nightly. On a bi-annual basis, DES exposures are reprocessed with a refined pipeline and coadded to maximize imaging depth. Here we describe the DES image processing pipeline in support of DES science, as a reference for users of archival DES data, and as a guide for future astronomical surveys.

Removing the depth-degeneracy in optical frequency domain imaging with frequency shifting

PubMed Central

Yun, S. H.; Tearney, G. J.; de Boer, J. F.; Bouma, B. E.

2009-01-01

A novel technique using an acousto-optic frequency shifter in optical frequency domain imaging (OFDI) is presented. The frequency shift eliminates the ambiguity between positive and negative differential delays, effectively doubling the interferometric ranging depth while avoiding image cross-talk. A signal processing algorithm is demonstrated to accommodate nonlinearity in the tuning slope of the wavelength-swept OFDI laser source. PMID:19484034

Digital processing of radiographic images

NASA Technical Reports Server (NTRS)

Bond, A. D.; Ramapriyan, H. K.

1973-01-01

Some techniques are presented and the software documentation for the digital enhancement of radiographs. Both image handling and image processing operations are considered. The image handling operations dealt with are: (1) conversion of format of data from packed to unpacked and vice versa; (2) automatic extraction of image data arrays; (3) transposition and 90 deg rotations of large data arrays; (4) translation of data arrays for registration; and (5) reduction of the dimensions of data arrays by integral factors. Both the frequency and the spatial domain approaches are presented for the design and implementation of the image processing operation. It is shown that spatial domain recursive implementation of filters is much faster than nonrecursive implementations using fast fourier transforms (FFT) for the cases of interest in this work. The recursive implementation of a class of matched filters for enhancing image signal to noise ratio is described. Test patterns are used to illustrate the filtering operations. The application of the techniques to radiographic images of metallic structures is demonstrated through several examples.

Parallelized multi–graphics processing unit framework for high-speed Gabor-domain optical coherence microscopy

PubMed Central

Tankam, Patrice; Santhanam, Anand P.; Lee, Kye-Sung; Won, Jungeun; Canavesi, Cristina; Rolland, Jannick P.

2014-01-01

Abstract. Gabor-domain optical coherence microscopy (GD-OCM) is a volumetric high-resolution technique capable of acquiring three-dimensional (3-D) skin images with histological resolution. Real-time image processing is needed to enable GD-OCM imaging in a clinical setting. We present a parallelized and scalable multi-graphics processing unit (GPU) computing framework for real-time GD-OCM image processing. A parallelized control mechanism was developed to individually assign computation tasks to each of the GPUs. For each GPU, the optimal number of amplitude-scans (A-scans) to be processed in parallel was selected to maximize GPU memory usage and core throughput. We investigated five computing architectures for computational speed-up in processing 1000×1000 A-scans. The proposed parallelized multi-GPU computing framework enables processing at a computational speed faster than the GD-OCM image acquisition, thereby facilitating high-speed GD-OCM imaging in a clinical setting. Using two parallelized GPUs, the image processing of a 1×1×0.6  mm3 skin sample was performed in about 13 s, and the performance was benchmarked at 6.5 s with four GPUs. This work thus demonstrates that 3-D GD-OCM data may be displayed in real-time to the examiner using parallelized GPU processing. PMID:24695868

Parallelized multi-graphics processing unit framework for high-speed Gabor-domain optical coherence microscopy.

PubMed

Tankam, Patrice; Santhanam, Anand P; Lee, Kye-Sung; Won, Jungeun; Canavesi, Cristina; Rolland, Jannick P

2014-07-01

Gabor-domain optical coherence microscopy (GD-OCM) is a volumetric high-resolution technique capable of acquiring three-dimensional (3-D) skin images with histological resolution. Real-time image processing is needed to enable GD-OCM imaging in a clinical setting. We present a parallelized and scalable multi-graphics processing unit (GPU) computing framework for real-time GD-OCM image processing. A parallelized control mechanism was developed to individually assign computation tasks to each of the GPUs. For each GPU, the optimal number of amplitude-scans (A-scans) to be processed in parallel was selected to maximize GPU memory usage and core throughput. We investigated five computing architectures for computational speed-up in processing 1000×1000 A-scans. The proposed parallelized multi-GPU computing framework enables processing at a computational speed faster than the GD-OCM image acquisition, thereby facilitating high-speed GD-OCM imaging in a clinical setting. Using two parallelized GPUs, the image processing of a 1×1×0.6  mm3 skin sample was performed in about 13 s, and the performance was benchmarked at 6.5 s with four GPUs. This work thus demonstrates that 3-D GD-OCM data may be displayed in real-time to the examiner using parallelized GPU processing.

Adaptive multifocus image fusion using block compressed sensing with smoothed projected Landweber integration in the wavelet domain.

PubMed

V S, Unni; Mishra, Deepak; Subrahmanyam, G R K S

2016-12-01

The need for image fusion in current image processing systems is increasing mainly due to the increased number and variety of image acquisition techniques. Image fusion is the process of combining substantial information from several sensors using mathematical techniques in order to create a single composite image that will be more comprehensive and thus more useful for a human operator or other computer vision tasks. This paper presents a new approach to multifocus image fusion based on sparse signal representation. Block-based compressive sensing integrated with a projection-driven compressive sensing (CS) recovery that encourages sparsity in the wavelet domain is used as a method to get the focused image from a set of out-of-focus images. Compression is achieved during the image acquisition process using a block compressive sensing method. An adaptive thresholding technique within the smoothed projected Landweber recovery process reconstructs high-resolution focused images from low-dimensional CS measurements of out-of-focus images. Discrete wavelet transform and dual-tree complex wavelet transform are used as the sparsifying basis for the proposed fusion. The main finding lies in the fact that sparsification enables a better selection of the fusion coefficients and hence better fusion. A Laplacian mixture model fit is done in the wavelet domain and estimation of the probability density function (pdf) parameters by expectation maximization leads us to the proper selection of the coefficients of the fused image. Using the proposed method compared with the fusion scheme without employing the projected Landweber (PL) scheme and the other existing CS-based fusion approaches, it is observed that with fewer samples itself, the proposed method outperforms other approaches.

High-speed spectral domain optical coherence tomography using non-uniform fast Fourier transform

PubMed Central

Chan, Kenny K. H.; Tang, Shuo

2010-01-01

The useful imaging range in spectral domain optical coherence tomography (SD-OCT) is often limited by the depth dependent sensitivity fall-off. Processing SD-OCT data with the non-uniform fast Fourier transform (NFFT) can improve the sensitivity fall-off at maximum depth by greater than 5dB concurrently with a 30 fold decrease in processing time compared to the fast Fourier transform with cubic spline interpolation method. NFFT can also improve local signal to noise ratio (SNR) and reduce image artifacts introduced in post-processing. Combined with parallel processing, NFFT is shown to have the ability to process up to 90k A-lines per second. High-speed SD-OCT imaging is demonstrated at camera-limited 100 frames per second on an ex-vivo squid eye. PMID:21258551

Quantum image median filtering in the spatial domain

NASA Astrophysics Data System (ADS)

Li, Panchi; Liu, Xiande; Xiao, Hong

2018-03-01

Spatial filtering is one principal tool used in image processing for a broad spectrum of applications. Median filtering has become a prominent representation of spatial filtering because its performance in noise reduction is excellent. Although filtering of quantum images in the frequency domain has been described in the literature, and there is a one-to-one correspondence between linear spatial filters and filters in the frequency domain, median filtering is a nonlinear process that cannot be achieved in the frequency domain. We therefore investigated the spatial filtering of quantum image, focusing on the design method of the quantum median filter and applications in image de-noising. To this end, first, we presented the quantum circuits for three basic modules (i.e., Cycle Shift, Comparator, and Swap), and then, we design two composite modules (i.e., Sort and Median Calculation). We next constructed a complete quantum circuit that implements the median filtering task and present the results of several simulation experiments on some grayscale images with different noise patterns. Although experimental results show that the proposed scheme has almost the same noise suppression capacity as its classical counterpart, the complexity analysis shows that the proposed scheme can reduce the computational complexity of the classical median filter from the exponential function of image size n to the second-order polynomial function of image size n, so that the classical method can be speeded up.

Microscopy mineral image enhancement based on improved adaptive threshold in nonsubsampled shearlet transform domain

NASA Astrophysics Data System (ADS)

Li, Liangliang; Si, Yujuan; Jia, Zhenhong

2018-03-01

In this paper, a novel microscopy mineral image enhancement method based on adaptive threshold in non-subsampled shearlet transform (NSST) domain is proposed. First, the image is decomposed into one low-frequency sub-band and several high-frequency sub-bands. Second, the gamma correction is applied to process the low-frequency sub-band coefficients, and the improved adaptive threshold is adopted to suppress the noise of the high-frequency sub-bands coefficients. Third, the processed coefficients are reconstructed with the inverse NSST. Finally, the unsharp filter is used to enhance the details of the reconstructed image. Experimental results on various microscopy mineral images demonstrated that the proposed approach has a better enhancement effect in terms of objective metric and subjective metric.

Digital image processing for photo-reconnaissance applications

NASA Technical Reports Server (NTRS)

Billingsley, F. C.

1972-01-01

Digital image-processing techniques developed for processing pictures from NASA space vehicles are analyzed in terms of enhancement, quantitative restoration, and information extraction. Digital filtering, and the action of a high frequency filter in the real and Fourier domain are discussed along with color and brightness.

Fractional domain varying-order differential denoising method

NASA Astrophysics Data System (ADS)

Zhang, Yan-Shan; Zhang, Feng; Li, Bing-Zhao; Tao, Ran

2014-10-01

Removal of noise is an important step in the image restoration process, and it remains a challenging problem in image processing. Denoising is a process used to remove the noise from the corrupted image, while retaining the edges and other detailed features as much as possible. Recently, denoising in the fractional domain is a hot research topic. The fractional-order anisotropic diffusion method can bring a less blocky effect and preserve edges in image denoising, a method that has received much interest in the literature. Based on this method, we propose a new method for image denoising, in which fractional-varying-order differential, rather than constant-order differential, is used. The theoretical analysis and experimental results show that compared with the state-of-the-art fractional-order anisotropic diffusion method, the proposed fractional-varying-order differential denoising model can preserve structure and texture well, while quickly removing noise, and yields good visual effects and better peak signal-to-noise ratio.

Improvement of lateral resolution of spectral domain optical coherence tomography images in out-of-focus regions with holographic data processing techniques

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moiseev, A A; Gelikonov, G V; Terpelov, D A

2014-08-31

An analogy between spectral-domain optical coherence tomography (SD OCT) data and broadband digital holography data is considered. Based on this analogy, a method for processing SD OCT data, which makes it possible to construct images with a lateral resolution in the whole investigated volume equal to the resolution in the in-focus region, is developed. Several issues concerning practical application of the proposed method are discussed. (laser biophotonics)

A novel fractal image compression scheme with block classification and sorting based on Pearson's correlation coefficient.

PubMed

Wang, Jianji; Zheng, Nanning

2013-09-01

Fractal image compression (FIC) is an image coding technology based on the local similarity of image structure. It is widely used in many fields such as image retrieval, image denoising, image authentication, and encryption. FIC, however, suffers from the high computational complexity in encoding. Although many schemes are published to speed up encoding, they do not easily satisfy the encoding time or the reconstructed image quality requirements. In this paper, a new FIC scheme is proposed based on the fact that the affine similarity between two blocks in FIC is equivalent to the absolute value of Pearson's correlation coefficient (APCC) between them. First, all blocks in the range and domain pools are chosen and classified using an APCC-based block classification method to increase the matching probability. Second, by sorting the domain blocks with respect to APCCs between these domain blocks and a preset block in each class, the matching domain block for a range block can be searched in the selected domain set in which these APCCs are closer to APCC between the range block and the preset block. Experimental results show that the proposed scheme can significantly speed up the encoding process in FIC while preserving the reconstructed image quality well.

Transform- and multi-domain deep learning for single-frame rapid autofocusing in whole slide imaging.

PubMed

Jiang, Shaowei; Liao, Jun; Bian, Zichao; Guo, Kaikai; Zhang, Yongbing; Zheng, Guoan

2018-04-01

A whole slide imaging (WSI) system has recently been approved for primary diagnostic use in the US. The image quality and system throughput of WSI is largely determined by the autofocusing process. Traditional approaches acquire multiple images along the optical axis and maximize a figure of merit for autofocusing. Here we explore the use of deep convolution neural networks (CNNs) to predict the focal position of the acquired image without axial scanning. We investigate the autofocusing performance with three illumination settings: incoherent Kohler illumination, partially coherent illumination with two plane waves, and one-plane-wave illumination. We acquire ~130,000 images with different defocus distances as the training data set. Different defocus distances lead to different spatial features of the captured images. However, solely relying on the spatial information leads to a relatively bad performance of the autofocusing process. It is better to extract defocus features from transform domains of the acquired image. For incoherent illumination, the Fourier cutoff frequency is directly related to the defocus distance. Similarly, autocorrelation peaks are directly related to the defocus distance for two-plane-wave illumination. In our implementation, we use the spatial image, the Fourier spectrum, the autocorrelation of the spatial image, and combinations thereof as the inputs for the CNNs. We show that the information from the transform domains can improve the performance and robustness of the autofocusing process. The resulting focusing error is ~0.5 µm, which is within the 0.8-µm depth-of-field range. The reported approach requires little hardware modification for conventional WSI systems and the images can be captured on the fly without focus map surveying. It may find applications in WSI and time-lapse microscopy. The transform- and multi-domain approaches may also provide new insights for developing microscopy-related deep-learning networks. We have made our training and testing data set (~12 GB) open-source for the broad research community.

Improving the Performance of the Prony Method Using a Wavelet Domain Filter for MRI Denoising

PubMed Central

Lentini, Marianela; Paluszny, Marco

2014-01-01

The Prony methods are used for exponential fitting. We use a variant of the Prony method for abnormal brain tissue detection in sequences of T 2 weighted magnetic resonance images. Here, MR images are considered to be affected only by Rician noise, and a new wavelet domain bilateral filtering process is implemented to reduce the noise in the images. This filter is a modification of Kazubek's algorithm and we use synthetic images to show the ability of the new procedure to suppress noise and compare its performance with respect to the original filter, using quantitative and qualitative criteria. The tissue classification process is illustrated using a real sequence of T 2 MR images, and the filter is applied to each image before using the variant of the Prony method. PMID:24834108

Improving the performance of the prony method using a wavelet domain filter for MRI denoising.

PubMed

Jaramillo, Rodney; Lentini, Marianela; Paluszny, Marco

2014-01-01

The Prony methods are used for exponential fitting. We use a variant of the Prony method for abnormal brain tissue detection in sequences of T 2 weighted magnetic resonance images. Here, MR images are considered to be affected only by Rician noise, and a new wavelet domain bilateral filtering process is implemented to reduce the noise in the images. This filter is a modification of Kazubek's algorithm and we use synthetic images to show the ability of the new procedure to suppress noise and compare its performance with respect to the original filter, using quantitative and qualitative criteria. The tissue classification process is illustrated using a real sequence of T 2 MR images, and the filter is applied to each image before using the variant of the Prony method.

Imaging workflow and calibration for CT-guided time-domain fluorescence tomography

PubMed Central

Tichauer, Kenneth M.; Holt, Robert W.; El-Ghussein, Fadi; Zhu, Qun; Dehghani, Hamid; Leblond, Frederic; Pogue, Brian W.

2011-01-01

In this study, several key optimization steps are outlined for a non-contact, time-correlated single photon counting small animal optical tomography system, using simultaneous collection of both fluorescence and transmittance data. The system is presented for time-domain image reconstruction in vivo, illustrating the sensitivity from single photon counting and the calibration steps needed to accurately process the data. In particular, laser time- and amplitude-referencing, detector and filter calibrations, and collection of a suitable instrument response function are all presented in the context of time-domain fluorescence tomography and a fully automated workflow is described. Preliminary phantom time-domain reconstructed images demonstrate the fidelity of the workflow for fluorescence tomography based on signal from multiple time gates. PMID:22076264

The Dark Energy Survey Image Processing Pipeline

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morganson, E.; et al.

The Dark Energy Survey (DES) is a five-year optical imaging campaign with the goal of understanding the origin of cosmic acceleration. DES performs a 5000 square degree survey of the southern sky in five optical bands (g,r,i,z,Y) to a depth of ~24th magnitude. Contemporaneously, DES performs a deep, time-domain survey in four optical bands (g,r,i,z) over 27 square degrees. DES exposures are processed nightly with an evolving data reduction pipeline and evaluated for image quality to determine if they need to be retaken. Difference imaging and transient source detection are also performed in the time domain component nightly. On amore » bi-annual basis, DES exposures are reprocessed with a refined pipeline and coadded to maximize imaging depth. Here we describe the DES image processing pipeline in support of DES science, as a reference for users of archival DES data, and as a guide for future astronomical surveys.« less

MARS-MD: rejection based image domain material decomposition

NASA Astrophysics Data System (ADS)

Bateman, C. J.; Knight, D.; Brandwacht, B.; McMahon, J.; Healy, J.; Panta, R.; Aamir, R.; Rajendran, K.; Moghiseh, M.; Ramyar, M.; Rundle, D.; Bennett, J.; de Ruiter, N.; Smithies, D.; Bell, S. T.; Doesburg, R.; Chernoglazov, A.; Mandalika, V. B. H.; Walsh, M.; Shamshad, M.; Anjomrouz, M.; Atharifard, A.; Vanden Broeke, L.; Bheesette, S.; Kirkbride, T.; Anderson, N. G.; Gieseg, S. P.; Woodfield, T.; Renaud, P. F.; Butler, A. P. H.; Butler, P. H.

2018-05-01

This paper outlines image domain material decomposition algorithms that have been routinely used in MARS spectral CT systems. These algorithms (known collectively as MARS-MD) are based on a pragmatic heuristic for solving the under-determined problem where there are more materials than energy bins. This heuristic contains three parts: (1) splitting the problem into a number of possible sub-problems, each containing fewer materials; (2) solving each sub-problem; and (3) applying rejection criteria to eliminate all but one sub-problem's solution. An advantage of this process is that different constraints can be applied to each sub-problem if necessary. In addition, the result of this process is that solutions will be sparse in the material domain, which reduces crossover of signal between material images. Two algorithms based on this process are presented: the Segmentation variant, which uses segmented material classes to define each sub-problem; and the Angular Rejection variant, which defines the rejection criteria using the angle between reconstructed attenuation vectors.

Green's function and image system for the Laplace operator in the prolate spheroidal geometry

NASA Astrophysics Data System (ADS)

Xue, Changfeng; Deng, Shaozhong

2017-01-01

In the present paper, electrostatic image theory is studied for Green's function for the Laplace operator in the case where the fundamental domain is either the exterior or the interior of a prolate spheroid. In either case, an image system is developed to consist of a point image inside the complement of the fundamental domain and an additional symmetric continuous surface image over a confocal prolate spheroid outside the fundamental domain, although the process of calculating such an image system is easier for the exterior than for the interior Green's function. The total charge of the surface image is zero and its centroid is at the origin of the prolate spheroid. In addition, if the source is on the focal axis outside the prolate spheroid, then the image system of the exterior Green's function consists of a point image on the focal axis and a line image on the line segment between the two focal points.

Simultaneous storage of medical images in the spatial and frequency domain: a comparative study.

PubMed

Nayak, Jagadish; Bhat, P Subbanna; Acharya U, Rajendra; Uc, Niranjan

2004-06-05

Digital watermarking is a technique of hiding specific identification data for copyright authentication. This technique is adapted here for interleaving patient information with medical images, to reduce storage and transmission overheads. The patient information is encrypted before interleaving with images to ensure greater security. The bio-signals are compressed and subsequently interleaved with the image. This interleaving is carried out in the spatial domain and Frequency domain. The performance of interleaving in the spatial, Discrete Fourier Transform (DFT), Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) coefficients is studied. Differential pulse code modulation (DPCM) is employed for data compression as well as encryption and results are tabulated for a specific example. It can be seen from results, the process does not affect the picture quality. This is attributed to the fact that the change in LSB of a pixel changes its brightness by 1 part in 256. Spatial and DFT domain interleaving gave very less %NRMSE as compared to DCT and DWT domain. The Results show that spatial domain the interleaving, the %NRMSE was less than 0.25% for 8-bit encoded pixel intensity. Among the frequency domain interleaving methods, DFT was found to be very efficient.

[Spatial domain display for interference image dataset].

PubMed

Wang, Cai-Ling; Li, Yu-Shan; Liu, Xue-Bin; Hu, Bing-Liang; Jing, Juan-Juan; Wen, Jia

2011-11-01

The requirements of imaging interferometer visualization is imminent for the user of image interpretation and information extraction. However, the conventional researches on visualization only focus on the spectral image dataset in spectral domain. Hence, the quick show of interference spectral image dataset display is one of the nodes in interference image processing. The conventional visualization of interference dataset chooses classical spectral image dataset display method after Fourier transformation. In the present paper, the problem of quick view of interferometer imager in image domain is addressed and the algorithm is proposed which simplifies the matter. The Fourier transformation is an obstacle since its computation time is very large and the complexion would be even deteriorated with the size of dataset increasing. The algorithm proposed, named interference weighted envelopes, makes the dataset divorced from transformation. The authors choose three interference weighted envelopes respectively based on the Fourier transformation, features of interference data and human visual system. After comparing the proposed with the conventional methods, the results show the huge difference in display time.

Super-resolution reconstruction in frequency, image, and wavelet domains to reduce through-plane partial voluming in MRI.

PubMed

Gholipour, Ali; Afacan, Onur; Aganj, Iman; Scherrer, Benoit; Prabhu, Sanjay P; Sahin, Mustafa; Warfield, Simon K

2015-12-01

To compare and evaluate the use of super-resolution reconstruction (SRR), in frequency, image, and wavelet domains, to reduce through-plane partial voluming effects in magnetic resonance imaging. The reconstruction of an isotropic high-resolution image from multiple thick-slice scans has been investigated through techniques in frequency, image, and wavelet domains. Experiments were carried out with thick-slice T2-weighted fast spin echo sequence on the Academic College of Radiology MRI phantom, where the reconstructed images were compared to a reference high-resolution scan using peak signal-to-noise ratio (PSNR), structural similarity image metric (SSIM), mutual information (MI), and the mean absolute error (MAE) of image intensity profiles. The application of super-resolution reconstruction was then examined in retrospective processing of clinical neuroimages of ten pediatric patients with tuberous sclerosis complex (TSC) to reduce through-plane partial voluming for improved 3D delineation and visualization of thin radial bands of white matter abnormalities. Quantitative evaluation results show improvements in all evaluation metrics through super-resolution reconstruction in the frequency, image, and wavelet domains, with the highest values obtained from SRR in the image domain. The metric values for image-domain SRR versus the original axial, coronal, and sagittal images were PSNR = 32.26 vs 32.22, 32.16, 30.65; SSIM = 0.931 vs 0.922, 0.924, 0.918; MI = 0.871 vs 0.842, 0.844, 0.831; and MAE = 5.38 vs 7.34, 7.06, 6.19. All similarity metrics showed high correlations with expert ranking of image resolution with MI showing the highest correlation at 0.943. Qualitative assessment of the neuroimages of ten TSC patients through in-plane and out-of-plane visualization of structures showed the extent of partial voluming effect in a real clinical scenario and its reduction using SRR. Blinded expert evaluation of image resolution in resampled out-of-plane views consistently showed the superiority of SRR compared to original axial and coronal image acquisitions. Thick-slice 2D T2-weighted MRI scans are part of many routine clinical protocols due to their high signal-to-noise ratio, but are often severely affected by through-plane partial voluming effects. This study shows that while radiologic assessment is performed in 2D on thick-slice scans, super-resolution MRI reconstruction techniques can be used to fuse those scans to generate a high-resolution image with reduced partial voluming for improved postacquisition processing. Qualitative and quantitative evaluation showed the efficacy of all SRR techniques with the best results obtained from SRR in the image domain. The limitations of SRR techniques are uncertainties in modeling the slice profile, density compensation, quantization in resampling, and uncompensated motion between scans.

Application of Time-Frequency Domain Transform to Three-Dimensional Interpolation of Medical Images.

PubMed

Lv, Shengqing; Chen, Yimin; Li, Zeyu; Lu, Jiahui; Gao, Mingke; Lu, Rongrong

2017-11-01

Medical image three-dimensional (3D) interpolation is an important means to improve the image effect in 3D reconstruction. In image processing, the time-frequency domain transform is an efficient method. In this article, several time-frequency domain transform methods are applied and compared in 3D interpolation. And a Sobel edge detection and 3D matching interpolation method based on wavelet transform is proposed. We combine wavelet transform, traditional matching interpolation methods, and Sobel edge detection together in our algorithm. What is more, the characteristics of wavelet transform and Sobel operator are used. They deal with the sub-images of wavelet decomposition separately. Sobel edge detection 3D matching interpolation method is used in low-frequency sub-images under the circumstances of ensuring high frequency undistorted. Through wavelet reconstruction, it can get the target interpolation image. In this article, we make 3D interpolation of the real computed tomography (CT) images. Compared with other interpolation methods, our proposed method is verified to be effective and superior.

Comparison of ring artifact removal methods using flat panel detector based CT images

PubMed Central

2011-01-01

Background Ring artifacts are the concentric rings superimposed on the tomographic images often caused by the defective and insufficient calibrated detector elements as well as by the damaged scintillator crystals of the flat panel detector. It may be also generated by objects attenuating X-rays very differently in different projection direction. Ring artifact reduction techniques so far reported in the literature can be broadly classified into two groups. One category of the approaches is based on the sinogram processing also known as the pre-processing techniques and the other category of techniques perform processing on the 2-D reconstructed images, recognized as the post-processing techniques in the literature. The strength and weakness of these categories of approaches are yet to be explored from a common platform. Method In this paper, a comparative study of the two categories of ring artifact reduction techniques basically designed for the multi-slice CT instruments is presented from a common platform. For comparison, two representative algorithms from each of the two categories are selected from the published literature. A very recently reported state-of-the-art sinogram domain ring artifact correction method that classifies the ring artifacts according to their strength and then corrects the artifacts using class adaptive correction schemes is also included in this comparative study. The first sinogram domain correction method uses a wavelet based technique to detect the corrupted pixels and then using a simple linear interpolation technique estimates the responses of the bad pixels. The second sinogram based correction method performs all the filtering operations in the transform domain, i.e., in the wavelet and Fourier domain. On the other hand, the two post-processing based correction techniques actually operate on the polar transform domain of the reconstructed CT images. The first method extracts the ring artifact template vector using a homogeneity test and then corrects the CT images by subtracting the artifact template vector from the uncorrected images. The second post-processing based correction technique performs median and mean filtering on the reconstructed images to produce the corrected images. Results The performances of the comparing algorithms have been tested by using both quantitative and perceptual measures. For quantitative analysis, two different numerical performance indices are chosen. On the other hand, different types of artifact patterns, e.g., single/band ring, artifacts from defective and mis-calibrated detector elements, rings in highly structural object and also in hard object, rings from different flat-panel detectors are analyzed to perceptually investigate the strength and weakness of the five methods. An investigation has been also carried out to compare the efficacy of these algorithms in correcting the volume images from a cone beam CT with the parameters determined from one particular slice. Finally, the capability of each correction technique in retaining the image information (e.g., small object at the iso-center) accurately in the corrected CT image has been also tested. Conclusions The results show that the performances of the algorithms are limited and none is fully suitable for correcting different types of ring artifacts without introducing processing distortion to the image structure. To achieve the diagnostic quality of the corrected slices a combination of the two approaches (sinogram- and post-processing) can be used. Also the comparing methods are not suitable for correcting the volume images from a cone beam flat-panel detector based CT. PMID:21846411

Image processing methods in two and three dimensions used to animate remotely sensed data. [cloud cover

NASA Technical Reports Server (NTRS)

Hussey, K. J.; Hall, J. R.; Mortensen, R. A.

1986-01-01

Image processing methods and software used to animate nonimaging remotely sensed data on cloud cover are described. Three FORTRAN programs were written in the VICAR2/TAE image processing domain to perform 3D perspective rendering, to interactively select parameters controlling the projection, and to interpolate parameter sets for animation images between key frames. Operation of the 3D programs and transferring the images to film is automated using executive control language and custom hardware to link the computer and camera.

Automated Processing Workflow for Ambient Seismic Recordings

NASA Astrophysics Data System (ADS)

Girard, A. J.; Shragge, J.

2017-12-01

Structural imaging using body-wave energy present in ambient seismic data remains a challenging task, largely because these wave modes are commonly much weaker than surface wave energy. In a number of situations body-wave energy has been extracted successfully; however, (nearly) all successful body-wave extraction and imaging approaches have focused on cross-correlation processing. While this is useful for interferometric purposes, it can also lead to the inclusion of unwanted noise events that dominate the resulting stack, leaving body-wave energy overpowered by the coherent noise. Conversely, wave-equation imaging can be applied directly on non-correlated ambient data that has been preprocessed to mitigate unwanted energy (i.e., surface waves, burst-like and electromechanical noise) to enhance body-wave arrivals. Following this approach, though, requires a significant preprocessing effort on often Terabytes of ambient seismic data, which is expensive and requires automation to be a feasible approach. In this work we outline an automated processing workflow designed to optimize body wave energy from an ambient seismic data set acquired on a large-N array at a mine site near Lalor Lake, Manitoba, Canada. We show that processing ambient seismic data in the recording domain, rather than the cross-correlation domain, allows us to mitigate energy that is inappropriate for body-wave imaging. We first develop a method for window selection that automatically identifies and removes data contaminated by coherent high-energy bursts. We then apply time- and frequency-domain debursting techniques to mitigate the effects of remaining strong amplitude and/or monochromatic energy without severely degrading the overall waveforms. After each processing step we implement a QC check to investigate improvements in the convergence rates - and the emergence of reflection events - in the cross-correlation plus stack waveforms over hour-long windows. Overall, the QC analyses suggest that automated preprocessing of ambient seismic recordings in the recording domain successfully mitigates unwanted coherent noise events in both the time and frequency domain. Accordingly, we assert that this method is beneficial for direct wave-equation imaging with ambient seismic recordings.

Precise Aperture-Dependent Motion Compensation with Frequency Domain Fast Back-Projection Algorithm.

PubMed

Zhang, Man; Wang, Guanyong; Zhang, Lei

2017-10-26

Precise azimuth-variant motion compensation (MOCO) is an essential and difficult task for high-resolution synthetic aperture radar (SAR) imagery. In conventional post-filtering approaches, residual azimuth-variant motion errors are generally compensated through a set of spatial post-filters, where the coarse-focused image is segmented into overlapped blocks concerning the azimuth-dependent residual errors. However, image domain post-filtering approaches, such as precise topography- and aperture-dependent motion compensation algorithm (PTA), have difficulty of robustness in declining, when strong motion errors are involved in the coarse-focused image. In this case, in order to capture the complete motion blurring function within each image block, both the block size and the overlapped part need necessary extension leading to degeneration of efficiency and robustness inevitably. Herein, a frequency domain fast back-projection algorithm (FDFBPA) is introduced to deal with strong azimuth-variant motion errors. FDFBPA disposes of the azimuth-variant motion errors based on a precise azimuth spectrum expression in the azimuth wavenumber domain. First, a wavenumber domain sub-aperture processing strategy is introduced to accelerate computation. After that, the azimuth wavenumber spectrum is partitioned into a set of wavenumber blocks, and each block is formed into a sub-aperture coarse resolution image via the back-projection integral. Then, the sub-aperture images are straightforwardly fused together in azimuth wavenumber domain to obtain a full resolution image. Moreover, chirp-Z transform (CZT) is also introduced to implement the sub-aperture back-projection integral, increasing the efficiency of the algorithm. By disusing the image domain post-filtering strategy, robustness of the proposed algorithm is improved. Both simulation and real-measured data experiments demonstrate the effectiveness and superiority of the proposal.

Maritime Domain Awareness: C4I for the 1000 Ship Navy

DTIC Science & Technology

2009-12-04

unit action, provide unit sensed contacts, coordinate unit operations, process unit information, release image , and release contact report, Figure 33...Intelligence Tasking Request Intelligence Summary Release Unit Person Incident Release Unit Vessel Incident Process Intelligence Tasking Release Image ...xi LIST OF FIGURES Figure 1. Functional Problem Sequence Process Flow. ....................................................4 Figure 2. United

Analysis Of The IJCNN 2011 UTL Challenge

DTIC Science & Technology

2012-01-13

large datasets from various application domains: handwriting recognition, image recognition, video processing, text processing, and ecology. The goal...validation and final evaluation sets consist of 4096 examples each. Dataset Domain Features Sparsity Devel. Transf. AVICENNA Handwriting 120 0% 150205...documents [3]. Transfer learning methods could accelerate the application of handwriting recognizers to historical manuscript by reducing the need for

Magnetic domain observation of FeCo thin films fabricated by alternate monoatomic layer deposition

NASA Astrophysics Data System (ADS)

Ohtsuki, T.; Kojima, T.; Kotsugi, M.; Ohkochi, T.; Mizuguchi, M.; Takanashi, K.

2014-01-01

FeCo thin films are fabricated by alternate monoatomic layer deposition method on a Cu3Au buffer layer, which in-plane lattice constant is very close to the predicted value to obtain a large magnetic anisotropy constant. The variation of the in-plane lattice constant during the deposition process is investigated by reflection high-energy electron diffraction. The magnetic domain images are also observed by a photoelectron emission microscope in order to microscopically understand the magnetic structure. As a result, element-specific magnetic domain images show that Fe and Co magnetic moments align parallel. A series of images obtained with various azimuth reveal that the FeCo thin films show fourfold in-plane magnetic anisotropy along ⟨110⟩ direction, and that the magnetic domain structure is composed only of 90∘ wall.

Cognition-based development and evaluation of ergonomic user interfaces for medical image processing and archiving systems.

PubMed

Demiris, A M; Meinzer, H P

1997-01-01

Whether or not a computerized system enhances the conditions of work in the application domain, very much demands on the user interface. Graphical user interfaces seem to attract the interest of the users but mostly ignore some basic rules of visual information processing thus leading to systems which are difficult to use, lowering productivity and increasing working stress (cognitive and work load). In this work we present some fundamental ergonomic considerations and their application to the medical image processing and archiving domain. We introduce the extensions to an existing concept needed to control and guide the development of GUIs with respect to domain specific ergonomics. The suggested concept, called Model-View-Controller Constraints (MVCC), can be used to programmatically implement ergonomic constraints, and thus has some advantages over written style guides. We conclude with the presentation of existing norms and methods to evaluate user interfaces.

Measurement of smaller colon polyp in CT colonography images using morphological image processing.

PubMed

Manjunath, K N; Siddalingaswamy, P C; Prabhu, G K

2017-11-01

Automated measurement of the size and shape of colon polyps is one of the challenges in Computed tomography colonography (CTC). The objective of this retrospective study was to improve the sensitivity and specificity of smaller polyp measurement in CTC using image processing techniques. A domain knowledge-based method has been implemented with hybrid method of colon segmentation, morphological image processing operators for detecting the colonic structures, and the decision-making system for delineating the smaller polyp-based on a priori knowledge. The method was applied on 45 CTC dataset. The key finding was that the smaller polyps were accurately measured. In addition to 6-9 mm range, polyps of even <5 mm were also detected. The results were validated qualitatively and quantitatively using both 2D MPR and 3D view. Implementation was done on a high-performance computer with parallel processing. It takes [Formula: see text] min for measuring the smaller polyp in a dataset of 500 CTC images. With this method, [Formula: see text] and [Formula: see text] were achieved. The domain-based approach with morphological image processing has given good results. The smaller polyps were measured accurately which helps in making right clinical decisions. Qualitatively and quantitatively the results were acceptable when compared to the ground truth at [Formula: see text].

Color image encryption by using Yang-Gu mixture amplitude-phase retrieval algorithm in gyrator transform domain and two-dimensional Sine logistic modulation map

NASA Astrophysics Data System (ADS)

Sui, Liansheng; Liu, Benqing; Wang, Qiang; Li, Ye; Liang, Junli

2015-12-01

A color image encryption scheme is proposed based on Yang-Gu mixture amplitude-phase retrieval algorithm and two-coupled logistic map in gyrator transform domain. First, the color plaintext image is decomposed into red, green and blue components, which are scrambled individually by three random sequences generated by using the two-dimensional Sine logistic modulation map. Second, each scrambled component is encrypted into a real-valued function with stationary white noise distribution in the iterative amplitude-phase retrieval process in the gyrator transform domain, and then three obtained functions are considered as red, green and blue channels to form the color ciphertext image. Obviously, the ciphertext image is real-valued function and more convenient for storing and transmitting. In the encryption and decryption processes, the chaotic random phase mask generated based on logistic map is employed as the phase key, which means that only the initial values are used as private key and the cryptosystem has high convenience on key management. Meanwhile, the security of the cryptosystem is enhanced greatly because of high sensitivity of the private keys. Simulation results are presented to prove the security and robustness of the proposed scheme.

Simultaneous storage of medical images in the spatial and frequency domain: A comparative study

PubMed Central

Nayak, Jagadish; Bhat, P Subbanna; Acharya U, Rajendra; UC, Niranjan

2004-01-01

Background Digital watermarking is a technique of hiding specific identification data for copyright authentication. This technique is adapted here for interleaving patient information with medical images, to reduce storage and transmission overheads. Methods The patient information is encrypted before interleaving with images to ensure greater security. The bio-signals are compressed and subsequently interleaved with the image. This interleaving is carried out in the spatial domain and Frequency domain. The performance of interleaving in the spatial, Discrete Fourier Transform (DFT), Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) coefficients is studied. Differential pulse code modulation (DPCM) is employed for data compression as well as encryption and results are tabulated for a specific example. Results It can be seen from results, the process does not affect the picture quality. This is attributed to the fact that the change in LSB of a pixel changes its brightness by 1 part in 256. Spatial and DFT domain interleaving gave very less %NRMSE as compared to DCT and DWT domain. Conclusion The Results show that spatial domain the interleaving, the %NRMSE was less than 0.25% for 8-bit encoded pixel intensity. Among the frequency domain interleaving methods, DFT was found to be very efficient. PMID:15180899

Blind deconvolution of astronomical images with band limitation determined by optical system parameters

NASA Astrophysics Data System (ADS)

Luo, L.; Fan, M.; Shen, M. Z.

2007-07-01

Atmospheric turbulence greatly limits the spatial resolution of astronomical images acquired by the large ground-based telescope. The record image obtained from telescope was thought as a convolution result of the object function and the point spread function. The statistic relationship of the images measured data, the estimated object and point spread function was in accord with the Bayes conditional probability distribution, and the maximum-likelihood formulation was found. A blind deconvolution approach based on the maximum-likelihood estimation technique with real optical band limitation constraint is presented for removing the effect of atmospheric turbulence on this class images through the minimization of the convolution error function by use of the conjugation gradient optimization algorithm. As a result, the object function and the point spread function could be estimated from a few record images at the same time by the blind deconvolution algorithm. According to the principle of Fourier optics, the relationship between the telescope optical system parameters and the image band constraint in the frequency domain was formulated during the image processing transformation between the spatial domain and the frequency domain. The convergence of the algorithm was increased by use of having the estimated function variable (also is the object function and the point spread function) nonnegative and the point-spread function band limited. Avoiding Fourier transform frequency components beyond the cut off frequency lost during the image processing transformation when the size of the sampled image data, image spatial domain and frequency domain were the same respectively, the detector element (e.g. a pixels in the CCD) should be less than the quarter of the diffraction speckle diameter of the telescope for acquiring the images on the focal plane. The proposed method can easily be applied to the case of wide field-view turbulent-degraded images restoration because of no using the object support constraint in the algorithm. The performance validity of the method is examined by the computer simulation and the restoration of the real Alpha Psc astronomical image data. The results suggest that the blind deconvolution with the real optical band constraint can remove the effect of the atmospheric turbulence on the observed images and the spatial resolution of the object image can arrive at or exceed the diffraction-limited level.

Real-time processing for full-range Fourier-domain optical-coherence tomography with zero-filling interpolation using multiple graphic processing units.

PubMed

Watanabe, Yuuki; Maeno, Seiya; Aoshima, Kenji; Hasegawa, Haruyuki; Koseki, Hitoshi

2010-09-01

The real-time display of full-range, 2048?axial pixelx1024?lateral pixel, Fourier-domain optical-coherence tomography (FD-OCT) images is demonstrated. The required speed was achieved by using dual graphic processing units (GPUs) with many stream processors to realize highly parallel processing. We used a zero-filling technique, including a forward Fourier transform, a zero padding to increase the axial data-array size to 8192, an inverse-Fourier transform back to the spectral domain, a linear interpolation from wavelength to wavenumber, a lateral Hilbert transform to obtain the complex spectrum, a Fourier transform to obtain the axial profiles, and a log scaling. The data-transfer time of the frame grabber was 15.73?ms, and the processing time, which includes the data transfer between the GPU memory and the host computer, was 14.75?ms, for a total time shorter than the 36.70?ms frame-interval time using a line-scan CCD camera operated at 27.9?kHz. That is, our OCT system achieved a processed-image display rate of 27.23 frames/s.

Vivaldi: A Domain-Specific Language for Volume Processing and Visualization on Distributed Heterogeneous Systems.

PubMed

Choi, Hyungsuk; Choi, Woohyuk; Quan, Tran Minh; Hildebrand, David G C; Pfister, Hanspeter; Jeong, Won-Ki

2014-12-01

As the size of image data from microscopes and telescopes increases, the need for high-throughput processing and visualization of large volumetric data has become more pressing. At the same time, many-core processors and GPU accelerators are commonplace, making high-performance distributed heterogeneous computing systems affordable. However, effectively utilizing GPU clusters is difficult for novice programmers, and even experienced programmers often fail to fully leverage the computing power of new parallel architectures due to their steep learning curve and programming complexity. In this paper, we propose Vivaldi, a new domain-specific language for volume processing and visualization on distributed heterogeneous computing systems. Vivaldi's Python-like grammar and parallel processing abstractions provide flexible programming tools for non-experts to easily write high-performance parallel computing code. Vivaldi provides commonly used functions and numerical operators for customized visualization and high-throughput image processing applications. We demonstrate the performance and usability of Vivaldi on several examples ranging from volume rendering to image segmentation.

A Robust Image Watermarking in the Joint Time-Frequency Domain

NASA Astrophysics Data System (ADS)

Öztürk, Mahmut; Akan, Aydın; Çekiç, Yalçın

2010-12-01

With the rapid development of computers and internet applications, copyright protection of multimedia data has become an important problem. Watermarking techniques are proposed as a solution to copyright protection of digital media files. In this paper, a new, robust, and high-capacity watermarking method that is based on spatiofrequency (SF) representation is presented. We use the discrete evolutionary transform (DET) calculated by the Gabor expansion to represent an image in the joint SF domain. The watermark is embedded onto selected coefficients in the joint SF domain. Hence, by combining the advantages of spatial and spectral domain watermarking methods, a robust, invisible, secure, and high-capacity watermarking method is presented. A correlation-based detector is also proposed to detect and extract any possible watermarks on an image. The proposed watermarking method was tested on some commonly used test images under different signal processing attacks like additive noise, Wiener and Median filtering, JPEG compression, rotation, and cropping. Simulation results show that our method is robust against all of the attacks.

Differential morphology and image processing.

PubMed

Maragos, P

1996-01-01

Image processing via mathematical morphology has traditionally used geometry to intuitively understand morphological signal operators and set or lattice algebra to analyze them in the space domain. We provide a unified view and analytic tools for morphological image processing that is based on ideas from differential calculus and dynamical systems. This includes ideas on using partial differential or difference equations (PDEs) to model distance propagation or nonlinear multiscale processes in images. We briefly review some nonlinear difference equations that implement discrete distance transforms and relate them to numerical solutions of the eikonal equation of optics. We also review some nonlinear PDEs that model the evolution of multiscale morphological operators and use morphological derivatives. Among the new ideas presented, we develop some general 2-D max/min-sum difference equations that model the space dynamics of 2-D morphological systems (including the distance computations) and some nonlinear signal transforms, called slope transforms, that can analyze these systems in a transform domain in ways conceptually similar to the application of Fourier transforms to linear systems. Thus, distance transforms are shown to be bandpass slope filters. We view the analysis of the multiscale morphological PDEs and of the eikonal PDE solved via weighted distance transforms as a unified area in nonlinear image processing, which we call differential morphology, and briefly discuss its potential applications to image processing and computer vision.

Super-resolution reconstruction in frequency, image, and wavelet domains to reduce through-plane partial voluming in MRI

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gholipour, Ali, E-mail: ali.gholipour@childrens.harvard.edu; Afacan, Onur; Scherrer, Benoit

Purpose: To compare and evaluate the use of super-resolution reconstruction (SRR), in frequency, image, and wavelet domains, to reduce through-plane partial voluming effects in magnetic resonance imaging. Methods: The reconstruction of an isotropic high-resolution image from multiple thick-slice scans has been investigated through techniques in frequency, image, and wavelet domains. Experiments were carried out with thick-slice T2-weighted fast spin echo sequence on the Academic College of Radiology MRI phantom, where the reconstructed images were compared to a reference high-resolution scan using peak signal-to-noise ratio (PSNR), structural similarity image metric (SSIM), mutual information (MI), and the mean absolute error (MAE) ofmore » image intensity profiles. The application of super-resolution reconstruction was then examined in retrospective processing of clinical neuroimages of ten pediatric patients with tuberous sclerosis complex (TSC) to reduce through-plane partial voluming for improved 3D delineation and visualization of thin radial bands of white matter abnormalities. Results: Quantitative evaluation results show improvements in all evaluation metrics through super-resolution reconstruction in the frequency, image, and wavelet domains, with the highest values obtained from SRR in the image domain. The metric values for image-domain SRR versus the original axial, coronal, and sagittal images were PSNR = 32.26 vs 32.22, 32.16, 30.65; SSIM = 0.931 vs 0.922, 0.924, 0.918; MI = 0.871 vs 0.842, 0.844, 0.831; and MAE = 5.38 vs 7.34, 7.06, 6.19. All similarity metrics showed high correlations with expert ranking of image resolution with MI showing the highest correlation at 0.943. Qualitative assessment of the neuroimages of ten TSC patients through in-plane and out-of-plane visualization of structures showed the extent of partial voluming effect in a real clinical scenario and its reduction using SRR. Blinded expert evaluation of image resolution in resampled out-of-plane views consistently showed the superiority of SRR compared to original axial and coronal image acquisitions. Conclusions: Thick-slice 2D T2-weighted MRI scans are part of many routine clinical protocols due to their high signal-to-noise ratio, but are often severely affected by through-plane partial voluming effects. This study shows that while radiologic assessment is performed in 2D on thick-slice scans, super-resolution MRI reconstruction techniques can be used to fuse those scans to generate a high-resolution image with reduced partial voluming for improved postacquisition processing. Qualitative and quantitative evaluation showed the efficacy of all SRR techniques with the best results obtained from SRR in the image domain. The limitations of SRR techniques are uncertainties in modeling the slice profile, density compensation, quantization in resampling, and uncompensated motion between scans.« less

Super-resolution reconstruction in frequency, image, and wavelet domains to reduce through-plane partial voluming in MRI

PubMed Central

Gholipour, Ali; Afacan, Onur; Aganj, Iman; Scherrer, Benoit; Prabhu, Sanjay P.; Sahin, Mustafa; Warfield, Simon K.

2015-01-01

Purpose: To compare and evaluate the use of super-resolution reconstruction (SRR), in frequency, image, and wavelet domains, to reduce through-plane partial voluming effects in magnetic resonance imaging. Methods: The reconstruction of an isotropic high-resolution image from multiple thick-slice scans has been investigated through techniques in frequency, image, and wavelet domains. Experiments were carried out with thick-slice T2-weighted fast spin echo sequence on the Academic College of Radiology MRI phantom, where the reconstructed images were compared to a reference high-resolution scan using peak signal-to-noise ratio (PSNR), structural similarity image metric (SSIM), mutual information (MI), and the mean absolute error (MAE) of image intensity profiles. The application of super-resolution reconstruction was then examined in retrospective processing of clinical neuroimages of ten pediatric patients with tuberous sclerosis complex (TSC) to reduce through-plane partial voluming for improved 3D delineation and visualization of thin radial bands of white matter abnormalities. Results: Quantitative evaluation results show improvements in all evaluation metrics through super-resolution reconstruction in the frequency, image, and wavelet domains, with the highest values obtained from SRR in the image domain. The metric values for image-domain SRR versus the original axial, coronal, and sagittal images were PSNR = 32.26 vs 32.22, 32.16, 30.65; SSIM = 0.931 vs 0.922, 0.924, 0.918; MI = 0.871 vs 0.842, 0.844, 0.831; and MAE = 5.38 vs 7.34, 7.06, 6.19. All similarity metrics showed high correlations with expert ranking of image resolution with MI showing the highest correlation at 0.943. Qualitative assessment of the neuroimages of ten TSC patients through in-plane and out-of-plane visualization of structures showed the extent of partial voluming effect in a real clinical scenario and its reduction using SRR. Blinded expert evaluation of image resolution in resampled out-of-plane views consistently showed the superiority of SRR compared to original axial and coronal image acquisitions. Conclusions: Thick-slice 2D T2-weighted MRI scans are part of many routine clinical protocols due to their high signal-to-noise ratio, but are often severely affected by through-plane partial voluming effects. This study shows that while radiologic assessment is performed in 2D on thick-slice scans, super-resolution MRI reconstruction techniques can be used to fuse those scans to generate a high-resolution image with reduced partial voluming for improved postacquisition processing. Qualitative and quantitative evaluation showed the efficacy of all SRR techniques with the best results obtained from SRR in the image domain. The limitations of SRR techniques are uncertainties in modeling the slice profile, density compensation, quantization in resampling, and uncompensated motion between scans. PMID:26632048

Fission gas bubble identification using MATLAB's image processing toolbox

DOE Office of Scientific and Technical Information (OSTI.GOV)

Collette, R.

Automated image processing routines have the potential to aid in the fuel performance evaluation process by eliminating bias in human judgment that may vary from person-to-person or sample-to-sample. This study presents several MATLAB based image analysis routines designed for fission gas void identification in post-irradiation examination of uranium molybdenum (U–Mo) monolithic-type plate fuels. Frequency domain filtration, enlisted as a pre-processing technique, can eliminate artifacts from the image without compromising the critical features of interest. This process is coupled with a bilateral filter, an edge-preserving noise removal technique aimed at preparing the image for optimal segmentation. Adaptive thresholding proved to bemore » the most consistent gray-level feature segmentation technique for U–Mo fuel microstructures. The Sauvola adaptive threshold technique segments the image based on histogram weighting factors in stable contrast regions and local statistics in variable contrast regions. Once all processing is complete, the algorithm outputs the total fission gas void count, the mean void size, and the average porosity. The final results demonstrate an ability to extract fission gas void morphological data faster, more consistently, and at least as accurately as manual segmentation methods. - Highlights: •Automated image processing can aid in the fuel qualification process. •Routines are developed to characterize fission gas bubbles in irradiated U–Mo fuel. •Frequency domain filtration effectively eliminates FIB curtaining artifacts. •Adaptive thresholding proved to be the most accurate segmentation method. •The techniques established are ready to be applied to large scale data extraction testing.« less

Improved JPEG anti-forensics with better image visual quality and forensic undetectability.

PubMed

Singh, Gurinder; Singh, Kulbir

2017-08-01

There is an immediate need to validate the authenticity of digital images due to the availability of powerful image processing tools that can easily manipulate the digital image information without leaving any traces. The digital image forensics most often employs the tampering detectors based on JPEG compression. Therefore, to evaluate the competency of the JPEG forensic detectors, an anti-forensic technique is required. In this paper, two improved JPEG anti-forensic techniques are proposed to remove the blocking artifacts left by the JPEG compression in both spatial and DCT domain. In the proposed framework, the grainy noise left by the perceptual histogram smoothing in DCT domain can be reduced significantly by applying the proposed de-noising operation. Two types of denoising algorithms are proposed, one is based on the constrained minimization problem of total variation of energy and other on the normalized weighted function. Subsequently, an improved TV based deblocking operation is proposed to eliminate the blocking artifacts in the spatial domain. Then, a decalibration operation is applied to bring the processed image statistics back to its standard position. The experimental results show that the proposed anti-forensic approaches outperform the existing state-of-the-art techniques in achieving enhanced tradeoff between image visual quality and forensic undetectability, but with high computational cost. Copyright © 2017 Elsevier B.V. All rights reserved.

A novel ship CFAR detection algorithm based on adaptive parameter enhancement and wake-aided detection in SAR images

NASA Astrophysics Data System (ADS)

Meng, Siqi; Ren, Kan; Lu, Dongming; Gu, Guohua; Chen, Qian; Lu, Guojun

2018-03-01

Synthetic aperture radar (SAR) is an indispensable and useful method for marine monitoring. With the increase of SAR sensors, high resolution images can be acquired and contain more target structure information, such as more spatial details etc. This paper presents a novel adaptive parameter transform (APT) domain constant false alarm rate (CFAR) to highlight targets. The whole method is based on the APT domain value. Firstly, the image is mapped to the new transform domain by the algorithm. Secondly, the false candidate target pixels are screened out by the CFAR detector to highlight the target ships. Thirdly, the ship pixels are replaced by the homogeneous sea pixels. And then, the enhanced image is processed by Niblack algorithm to obtain the wake binary image. Finally, normalized Hough transform (NHT) is used to detect wakes in the binary image, as a verification of the presence of the ships. Experiments on real SAR images validate that the proposed transform does enhance the target structure and improve the contrast of the image. The algorithm has a good performance in the ship and ship wake detection.

Optimized Setup and Protocol for Magnetic Domain Imaging with In Situ Hysteresis Measurement

PubMed Central

Liu, Jun; Wilson, John; Davis, Claire; Peyton, Anthony

2017-01-01

This paper elaborates the sample preparation protocols required to obtain optimal domain patterns using the Bitter method, focusing on the extra steps compared to standard metallographic sample preparation procedures. The paper proposes a novel bespoke rig for dynamic domain imaging with in situ BH (magnetic hysteresis) measurements and elaborates the protocols for the sensor preparation and the use of the rig to ensure accurate BH measurement. The protocols for static and ordinary dynamic domain imaging (without in situ BH measurements) are also presented. The reported method takes advantage of the convenience and high sensitivity of the traditional Bitter method and enables in situ BH measurement without interrupting or interfering with the domain wall movement processes. This facilitates establishing a direct and quantitative link between the domain wall movement processes–microstructural feature interactions in ferritic steels with their BH loops. This method is anticipated to become a useful tool for the fundamental study of microstructure–magnetic property relationships in steels and to help interpret the electromagnetic sensor signals for non-destructive evaluation of steel microstructures. PMID:29155796

Magnetic domain observation of FeCo thin films fabricated by alternate monoatomic layer deposition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ohtsuki, T., E-mail: ohtsuki@spring8.or.jp; Kotsugi, M.; Ohkochi, T.

2014-01-28

FeCo thin films are fabricated by alternate monoatomic layer deposition method on a Cu{sub 3}Au buffer layer, which in-plane lattice constant is very close to the predicted value to obtain a large magnetic anisotropy constant. The variation of the in-plane lattice constant during the deposition process is investigated by reflection high-energy electron diffraction. The magnetic domain images are also observed by a photoelectron emission microscope in order to microscopically understand the magnetic structure. As a result, element-specific magnetic domain images show that Fe and Co magnetic moments align parallel. A series of images obtained with various azimuth reveal that themore » FeCo thin films show fourfold in-plane magnetic anisotropy along 〈110〉 direction, and that the magnetic domain structure is composed only of 90∘ wall.« less

A wavelet domain adaptive image watermarking method based on chaotic encryption

NASA Astrophysics Data System (ADS)

Wei, Fang; Liu, Jian; Cao, Hanqiang; Yang, Jun

2009-10-01

A digital watermarking technique is a specific branch of steganography, which can be used in various applications, provides a novel way to solve security problems for multimedia information. In this paper, we proposed a kind of wavelet domain adaptive image digital watermarking method using chaotic stream encrypt and human eye visual property. The secret information that can be seen as a watermarking is hidden into a host image, which can be publicly accessed, so the transportation of the secret information will not attract the attention of illegal receiver. The experimental results show that the method is invisible and robust against some image processing.

Characterization and Upscaling of Pore Scale Hydrodynamic Mass Transfer

NASA Astrophysics Data System (ADS)

Gouze, P.; Roubinet, D.; Dentz, M.; Planes, V.; Russian, A.

2017-12-01

Imaging reservoir rocks in 3D using X-ray microtomography with spatial resolution ranging from about 1 to 10 mm provides us a unique opportunity not only to characterize pore space geometry but also for simulating hydrodynamical processes. Yet, pores and throats displaying sizes smaller than the resolution cannot be distinguished on the images and must be assigned to a so called microporous phase during the process of image segmentation. Accordingly one simulated mass transfers caused by advection and diffusion in the connected pores (mobile domain) and diffusion in the microporous clusters (immobile domain) using Time Domain Random Walk (TDRW) and developed a set of metrics that can be used to monitor the different mechanisms of transport in the sample, the final objective being of proposing a simple but accurate upscaled 1D model in which the particle travel times in the mobile and immobile domain and the number of mobile-immobile transfer events (called trapping events) are independently distributed random variables characterized by PDFs. For TDRW the solute concentration is represented by the density distribution of non-interacting point-like solute particles which move due to advection and dispersion. The set of metrics derives from different spatial and temporal statistical analyses of the particle motion, and is used for characterizing the particles transport (i) in the mobile domain in relation with the velocity field properties, (ii) in the immobile domain in relation with the structure and the properties of microporous phase and at the mobile-immobile interface. We specifically focused on how to model the trapping frequency and rate into the immobile domain in relation with the structure and the spatial distribution of the mobile-immobile domain interface. This thorough analysis of the particle motion for both simple artificial structures and real rock images allowed us to derive the parametrization of the upscaled 1D model.

Optical imaging through dynamic turbid media using the Fourier-domain shower-curtain effect

PubMed Central

Edrei, Eitan; Scarcelli, Giuliano

2016-01-01

Several phenomena have been recently exploited to circumvent scattering and have succeeded in imaging or focusing light through turbid layers. However, the requirement for the turbid medium to be steady during the imaging process remains a fundamental limitation of these methods. Here we introduce an optical imaging modality that overcomes this challenge by taking advantage of the so-called shower-curtain effect, adapted to the spatial-frequency domain via speckle correlography. We present high resolution imaging of objects hidden behind millimeter-thick tissue or dense lens cataracts. We demonstrate our imaging technique to be insensitive to rapid medium movements (> 5 m/s) beyond any biologically-relevant motion. Furthermore, we show this method can be extended to several contrast mechanisms and imaging configurations. PMID:27347498

Gradient-based multiresolution image fusion.

PubMed

Petrović, Valdimir S; Xydeas, Costas S

2004-02-01

A novel approach to multiresolution signal-level image fusion is presented for accurately transferring visual information from any number of input image signals, into a single fused image without loss of information or the introduction of distortion. The proposed system uses a "fuse-then-decompose" technique realized through a novel, fusion/decomposition system architecture. In particular, information fusion is performed on a multiresolution gradient map representation domain of image signal information. At each resolution, input images are represented as gradient maps and combined to produce new, fused gradient maps. Fused gradient map signals are processed, using gradient filters derived from high-pass quadrature mirror filters to yield a fused multiresolution pyramid representation. The fused output image is obtained by applying, on the fused pyramid, a reconstruction process that is analogous to that of conventional discrete wavelet transform. This new gradient fusion significantly reduces the amount of distortion artefacts and the loss of contrast information usually observed in fused images obtained from conventional multiresolution fusion schemes. This is because fusion in the gradient map domain significantly improves the reliability of the feature selection and information fusion processes. Fusion performance is evaluated through informal visual inspection and subjective psychometric preference tests, as well as objective fusion performance measurements. Results clearly demonstrate the superiority of this new approach when compared to conventional fusion systems.

Curve and Polygon Evolution Techniques for Image Processing

DTIC Science & Technology

2002-01-01

iterative image registration technique with an application to stereo vision. IJCAI, pages 674–679, 1981. 127 [93] R . Malladi , J.A. Sethian, and B.C...Notation A digital image to be processed is a 2-Dimensional (2-D) function denoted by I , I : ! R , where R2 is the domain of the function. Processing a...function Io(x; y), which depends on two spatial variables, x 2 R , and y 2 R , via a partial differential equation (PDE) takes the form; It = A(I; Ix

ELAS: A powerful, general purpose image processing package

NASA Technical Reports Server (NTRS)

Walters, David; Rickman, Douglas

1991-01-01

ELAS is a software package which has been utilized as an image processing tool for more than a decade. It has been the source of several commercial packages. Now available on UNIX workstations it is a very powerful, flexible set of software. Applications at Stennis Space Center have included a very wide range of areas including medicine, forestry, geology, ecological modeling, and sonar imagery. It remains one of the most powerful image processing packages available, either commercially or in the public domain.

Fan beam image reconstruction with generalized Fourier slice theorem.

PubMed

Zhao, Shuangren; Yang, Kang; Yang, Kevin

2014-01-01

For parallel beam geometry the Fourier reconstruction works via the Fourier slice theorem (or central slice theorem, projection slice theorem). For fan beam situation, Fourier slice can be extended to a generalized Fourier slice theorem (GFST) for fan-beam image reconstruction. We have briefly introduced this method in a conference. This paper reintroduces the GFST method for fan beam geometry in details. The GFST method can be described as following: the Fourier plane is filled by adding up the contributions from all fanbeam projections individually; thereby the values in the Fourier plane are directly calculated for Cartesian coordinates such avoiding the interpolation from polar to Cartesian coordinates in the Fourier domain; inverse fast Fourier transform is applied to the image in Fourier plane and leads to a reconstructed image in spacial domain. The reconstructed image is compared between the result of the GFST method and the result from the filtered backprojection (FBP) method. The major differences of the GFST and the FBP methods are: (1) The interpolation process are at different data sets. The interpolation of the GFST method is at projection data. The interpolation of the FBP method is at filtered projection data. (2) The filtering process are done in different places. The filtering process of the GFST is at Fourier domain. The filtering process of the FBP method is the ramp filter which is done at projections. The resolution of ramp filter is variable with different location but the filter in the Fourier domain lead to resolution invariable with location. One advantage of the GFST method over the FBP method is in short scan situation, an exact solution can be obtained with the GFST method, but it can not be obtained with the FBP method. The calculation of both the GFST and the FBP methods are at O(N^3), where N is the number of pixel in one dimension.

Trends in optical coherence tomography applied to medical imaging

NASA Astrophysics Data System (ADS)

Podoleanu, Adrian G.

2014-01-01

The number of publications on optical coherence tomography (OCT) continues to double every three years. Traditionally applied to imaging the eye, OCT is now being extended to fields outside ophthalmology and optometry. Widening its applicability, progress in the core engine of the technology, and impact on development of novel optical sources, make OCT a very active and rapidly evolving field. Trends in the developments of different specific devices, such as optical sources, optical configurations and signal processing will be presented. Encompassing studies on both the configurations as well as on signal processing themes, current research in Kent looks at combining spectral domain with time domain imaging for long axial range and simultaneous imaging at several depths. Results of the collaborative work of the Applied Optics Group in Kent with organisers of this conference will be presented, with reference to 3D monitoring of abfraction.

Accelerated pharmacokinetic map determination for dynamic contrast enhanced MRI using frequency-domain based Tofts model.

PubMed

Vajuvalli, Nithin N; Nayak, Krupa N; Geethanath, Sairam

2014-01-01

Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE-MRI) is widely used in the diagnosis of cancer and is also a promising tool for monitoring tumor response to treatment. The Tofts model has become a standard for the analysis of DCE-MRI. The process of curve fitting employed in the Tofts equation to obtain the pharmacokinetic (PK) parameters is time-consuming for high resolution scans. Current work demonstrates a frequency-domain approach applied to the standard Tofts equation to speed-up the process of curve-fitting in order to obtain the pharmacokinetic parameters. The results obtained show that using the frequency domain approach, the process of curve fitting is computationally more efficient compared to the time-domain approach.

Privacy protection in surveillance systems based on JPEG DCT baseline compression and spectral domain watermarking

NASA Astrophysics Data System (ADS)

Sablik, Thomas; Velten, Jörg; Kummert, Anton

2015-03-01

An novel system for automatic privacy protection in digital media based on spectral domain watermarking and JPEG compression is described in the present paper. In a first step private areas are detected. Therefore a detection method is presented. The implemented method uses Haar cascades to detects faces. Integral images are used to speed up calculations and the detection. Multiple detections of one face are combined. Succeeding steps comprise embedding the data into the image as part of JPEG compression using spectral domain methods and protecting the area of privacy. The embedding process is integrated into and adapted to JPEG compression. A Spread Spectrum Watermarking method is used to embed the size and position of the private areas into the cover image. Different methods for embedding regarding their robustness are compared. Moreover the performance of the method concerning tampered images is presented.

Image denoising in mixed Poisson-Gaussian noise.

PubMed

Luisier, Florian; Blu, Thierry; Unser, Michael

2011-03-01

We propose a general methodology (PURE-LET) to design and optimize a wide class of transform-domain thresholding algorithms for denoising images corrupted by mixed Poisson-Gaussian noise. We express the denoising process as a linear expansion of thresholds (LET) that we optimize by relying on a purely data-adaptive unbiased estimate of the mean-squared error (MSE), derived in a non-Bayesian framework (PURE: Poisson-Gaussian unbiased risk estimate). We provide a practical approximation of this theoretical MSE estimate for the tractable optimization of arbitrary transform-domain thresholding. We then propose a pointwise estimator for undecimated filterbank transforms, which consists of subband-adaptive thresholding functions with signal-dependent thresholds that are globally optimized in the image domain. We finally demonstrate the potential of the proposed approach through extensive comparisons with state-of-the-art techniques that are specifically tailored to the estimation of Poisson intensities. We also present denoising results obtained on real images of low-count fluorescence microscopy.

Intermediate Palomar Transient Factory: Realtime Image Subtraction Pipeline

DOE PAGES

Cao, Yi; Nugent, Peter E.; Kasliwal, Mansi M.

2016-09-28

A fast-turnaround pipeline for realtime data reduction plays an essential role in discovering and permitting followup observations to young supernovae and fast-evolving transients in modern time-domain surveys. In this paper, we present the realtime image subtraction pipeline in the intermediate Palomar Transient Factory. By using highperformance computing, efficient databases, and machine-learning algorithms, this pipeline manages to reliably deliver transient candidates within 10 minutes of images being taken. Our experience in using high-performance computing resources to process big data in astronomy serves as a trailblazer to dealing with data from large-scale time-domain facilities in the near future.

Intermediate Palomar Transient Factory: Realtime Image Subtraction Pipeline

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cao, Yi; Nugent, Peter E.; Kasliwal, Mansi M.

A fast-turnaround pipeline for realtime data reduction plays an essential role in discovering and permitting followup observations to young supernovae and fast-evolving transients in modern time-domain surveys. In this paper, we present the realtime image subtraction pipeline in the intermediate Palomar Transient Factory. By using highperformance computing, efficient databases, and machine-learning algorithms, this pipeline manages to reliably deliver transient candidates within 10 minutes of images being taken. Our experience in using high-performance computing resources to process big data in astronomy serves as a trailblazer to dealing with data from large-scale time-domain facilities in the near future.

Computer model for harmonic ultrasound imaging.

PubMed

Li, Y; Zagzebski, J A

2000-01-01

Harmonic ultrasound imaging has received great attention from ultrasound scanner manufacturers and researchers. In this paper, we present a computer model that can generate realistic harmonic images. In this model, the incident ultrasound is modeled after the "KZK" equation, and the echo signal is modeled using linear propagation theory because the echo signal is much weaker than the incident pulse. Both time domain and frequency domain numerical solutions to the "KZK" equation were studied. Realistic harmonic images of spherical lesion phantoms were generated for scans by a circular transducer. This model can be a very useful tool for studying the harmonic buildup and dissipation processes in a nonlinear medium, and it can be used to investigate a wide variety of topics related to B-mode harmonic imaging.

Computer model for harmonic ultrasound imaging.

PubMed

Li, Y; Zagzebski, J A

2000-01-01

Harmonic ultrasound imaging has received great attention from ultrasound scanner manufacturers and researchers. Here, the authors present a computer model that can generate realistic harmonic images. In this model, the incident ultrasound is modeled after the "KZK" equation, and the echo signal is modeled using linear propagation theory because the echo signal is much weaker than the incident pulse. Both time domain and frequency domain numerical solutions to the "KZK" equation were studied. Realistic harmonic images of spherical lesion phantoms were generated for scans by a circular transducer. This model can be a very useful tool for studying the harmonic buildup and dissipation processes in a nonlinear medium, and it can be used to investigate a wide variety of topics related to B-mode harmonic imaging.

Advances in interpretation of subsurface processes with time-lapse electrical imaging

USGS Publications Warehouse

Singha, Kaminit; Day-Lewis, Frederick D.; Johnson, Tim B.; Slater, Lee D.

2015-01-01

Electrical geophysical methods, including electrical resistivity, time-domain induced polarization, and complex resistivity, have become commonly used to image the near subsurface. Here, we outline their utility for time-lapse imaging of hydrological, geochemical, and biogeochemical processes, focusing on new instrumentation, processing, and analysis techniques specific to monitoring. We review data collection procedures, parameters measured, and petrophysical relationships and then outline the state of the science with respect to inversion methodologies, including coupled inversion. We conclude by highlighting recent research focused on innovative applications of time-lapse imaging in hydrology, biology, ecology, and geochemistry, among other areas of interest.

Advances in interpretation of subsurface processes with time-lapse electrical imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Singha, Kamini; Day-Lewis, Frederick D.; Johnson, Timothy C.

2015-03-15

Electrical geophysical methods, including electrical resistivity, time-domain induced polarization, and complex resistivity, have become commonly used to image the near subsurface. Here, we outline their utility for time-lapse imaging of hydrological, geochemical, and biogeochemical processes, focusing on new instrumentation, processing, and analysis techniques specific to monitoring. We review data collection procedures, parameters measured, and petrophysical relationships and then outline the state of the science with respect to inversion methodologies, including coupled inversion. We conclude by highlighting recent research focused on innovative applications of time-lapse imaging in hydrology, biology, ecology, and geochemistry, among other areas of interest.

An Improved Filtering Method for Quantum Color Image in Frequency Domain

NASA Astrophysics Data System (ADS)

Li, Panchi; Xiao, Hong

2018-01-01

In this paper we investigate the use of quantum Fourier transform (QFT) in the field of image processing. We consider QFT-based color image filtering operations and their applications in image smoothing, sharpening, and selective filtering using quantum frequency domain filters. The underlying principle used for constructing the proposed quantum filters is to use the principle of the quantum Oracle to implement the filter function. Compared with the existing methods, our method is not only suitable for color images, but also can flexibly design the notch filters. We provide the quantum circuit that implements the filtering task and present the results of several simulation experiments on color images. The major advantages of the quantum frequency filtering lies in the exploitation of the efficient implementation of the quantum Fourier transform.

Low-rank and Adaptive Sparse Signal (LASSI) Models for Highly Accelerated Dynamic Imaging

PubMed Central

Ravishankar, Saiprasad; Moore, Brian E.; Nadakuditi, Raj Rao; Fessler, Jeffrey A.

2017-01-01

Sparsity-based approaches have been popular in many applications in image processing and imaging. Compressed sensing exploits the sparsity of images in a transform domain or dictionary to improve image recovery from undersampled measurements. In the context of inverse problems in dynamic imaging, recent research has demonstrated the promise of sparsity and low-rank techniques. For example, the patches of the underlying data are modeled as sparse in an adaptive dictionary domain, and the resulting image and dictionary estimation from undersampled measurements is called dictionary-blind compressed sensing, or the dynamic image sequence is modeled as a sum of low-rank and sparse (in some transform domain) components (L+S model) that are estimated from limited measurements. In this work, we investigate a data-adaptive extension of the L+S model, dubbed LASSI, where the temporal image sequence is decomposed into a low-rank component and a component whose spatiotemporal (3D) patches are sparse in some adaptive dictionary domain. We investigate various formulations and efficient methods for jointly estimating the underlying dynamic signal components and the spatiotemporal dictionary from limited measurements. We also obtain efficient sparsity penalized dictionary-blind compressed sensing methods as special cases of our LASSI approaches. Our numerical experiments demonstrate the promising performance of LASSI schemes for dynamic magnetic resonance image reconstruction from limited k-t space data compared to recent methods such as k-t SLR and L+S, and compared to the proposed dictionary-blind compressed sensing method. PMID:28092528

Low-Rank and Adaptive Sparse Signal (LASSI) Models for Highly Accelerated Dynamic Imaging.

PubMed

Ravishankar, Saiprasad; Moore, Brian E; Nadakuditi, Raj Rao; Fessler, Jeffrey A

2017-05-01

Sparsity-based approaches have been popular in many applications in image processing and imaging. Compressed sensing exploits the sparsity of images in a transform domain or dictionary to improve image recovery fromundersampledmeasurements. In the context of inverse problems in dynamic imaging, recent research has demonstrated the promise of sparsity and low-rank techniques. For example, the patches of the underlying data are modeled as sparse in an adaptive dictionary domain, and the resulting image and dictionary estimation from undersampled measurements is called dictionary-blind compressed sensing, or the dynamic image sequence is modeled as a sum of low-rank and sparse (in some transform domain) components (L+S model) that are estimated from limited measurements. In this work, we investigate a data-adaptive extension of the L+S model, dubbed LASSI, where the temporal image sequence is decomposed into a low-rank component and a component whose spatiotemporal (3D) patches are sparse in some adaptive dictionary domain. We investigate various formulations and efficient methods for jointly estimating the underlying dynamic signal components and the spatiotemporal dictionary from limited measurements. We also obtain efficient sparsity penalized dictionary-blind compressed sensing methods as special cases of our LASSI approaches. Our numerical experiments demonstrate the promising performance of LASSI schemes for dynamicmagnetic resonance image reconstruction from limited k-t space data compared to recent methods such as k-t SLR and L+S, and compared to the proposed dictionary-blind compressed sensing method.

Performance evaluation of canny edge detection on a tiled multicore architecture

NASA Astrophysics Data System (ADS)

Brethorst, Andrew Z.; Desai, Nehal; Enright, Douglas P.; Scrofano, Ronald

2011-01-01

In the last few years, a variety of multicore architectures have been used to parallelize image processing applications. In this paper, we focus on assessing the parallel speed-ups of different Canny edge detection parallelization strategies on the Tile64, a tiled multicore architecture developed by the Tilera Corporation. Included in these strategies are different ways Canny edge detection can be parallelized, as well as differences in data management. The two parallelization strategies examined were loop-level parallelism and domain decomposition. Loop-level parallelism is achieved through the use of OpenMP,1 and it is capable of parallelization across the range of values over which a loop iterates. Domain decomposition is the process of breaking down an image into subimages, where each subimage is processed independently, in parallel. The results of the two strategies show that for the same number of threads, programmer implemented, domain decomposition exhibits higher speed-ups than the compiler managed, loop-level parallelism implemented with OpenMP.

Neuroimaging Feature Terminology: A Controlled Terminology for the Annotation of Brain Imaging Features.

PubMed

Iyappan, Anandhi; Younesi, Erfan; Redolfi, Alberto; Vrooman, Henri; Khanna, Shashank; Frisoni, Giovanni B; Hofmann-Apitius, Martin

2017-01-01

Ontologies and terminologies are used for interoperability of knowledge and data in a standard manner among interdisciplinary research groups. Existing imaging ontologies capture general aspects of the imaging domain as a whole such as methodological concepts or calibrations of imaging instruments. However, none of the existing ontologies covers the diagnostic features measured by imaging technologies in the context of neurodegenerative diseases. Therefore, the Neuro-Imaging Feature Terminology (NIFT) was developed to organize the knowledge domain of measured brain features in association with neurodegenerative diseases by imaging technologies. The purpose is to identify quantitative imaging biomarkers that can be extracted from multi-modal brain imaging data. This terminology attempts to cover measured features and parameters in brain scans relevant to disease progression. In this paper, we demonstrate the systematic retrieval of measured indices from literature and how the extracted knowledge can be further used for disease modeling that integrates neuroimaging features with molecular processes.

3D wide field-of-view Gabor-domain optical coherence microscopy advancing real-time in-vivo imaging and metrology

NASA Astrophysics Data System (ADS)

Canavesi, Cristina; Cogliati, Andrea; Hayes, Adam; Tankam, Patrice; Santhanam, Anand; Rolland, Jannick P.

2017-02-01

Real-time volumetric high-definition wide-field-of-view in-vivo cellular imaging requires micron-scale resolution in 3D. Compactness of the handheld device and distortion-free images with cellular resolution are also critically required for onsite use in clinical applications. By integrating a custom liquid lens-based microscope and a dual-axis MEMS scanner in a compact handheld probe, Gabor-domain optical coherence microscopy (GD-OCM) breaks the lateral resolution limit of optical coherence tomography through depth, overcoming the tradeoff between numerical aperture and depth of focus, enabling advances in biotechnology. Furthermore, distortion-free imaging with no post-processing is achieved with a compact, lightweight handheld MEMS scanner that obtained a 12-fold reduction in volume and 17-fold reduction in weight over a previous dual-mirror galvanometer-based scanner. Approaching the holy grail of medical imaging - noninvasive real-time imaging with histologic resolution - GD-OCM demonstrates invariant resolution of 2 μm throughout a volume of 1 x 1 x 0.6 mm3, acquired and visualized in less than 2 minutes with parallel processing on graphics processing units. Results on the metrology of manufactured materials and imaging of human tissue with GD-OCM are presented.

A model-based scatter artifacts correction for cone beam CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhao, Wei; Zhu, Jun; Wang, Luyao

2016-04-15

Purpose: Due to the increased axial coverage of multislice computed tomography (CT) and the introduction of flat detectors, the size of x-ray illumination fields has grown dramatically, causing an increase in scatter radiation. For CT imaging, scatter is a significant issue that introduces shading artifact, streaks, as well as reduced contrast and Hounsfield Units (HU) accuracy. The purpose of this work is to provide a fast and accurate scatter artifacts correction algorithm for cone beam CT (CBCT) imaging. Methods: The method starts with an estimation of coarse scatter profiles for a set of CBCT data in either image domain ormore » projection domain. A denoising algorithm designed specifically for Poisson signals is then applied to derive the final scatter distribution. Qualitative and quantitative evaluations using thorax and abdomen phantoms with Monte Carlo (MC) simulations, experimental Catphan phantom data, and in vivo human data acquired for a clinical image guided radiation therapy were performed. Scatter correction in both projection domain and image domain was conducted and the influences of segmentation method, mismatched attenuation coefficients, and spectrum model as well as parameter selection were also investigated. Results: Results show that the proposed algorithm can significantly reduce scatter artifacts and recover the correct HU in either projection domain or image domain. For the MC thorax phantom study, four-components segmentation yields the best results, while the results of three-components segmentation are still acceptable. The parameters (iteration number K and weight β) affect the accuracy of the scatter correction and the results get improved as K and β increase. It was found that variations in attenuation coefficient accuracies only slightly impact the performance of the proposed processing. For the Catphan phantom data, the mean value over all pixels in the residual image is reduced from −21.8 to −0.2 HU and 0.7 HU for projection domain and image domain, respectively. The contrast of the in vivo human images is greatly improved after correction. Conclusions: The software-based technique has a number of advantages, such as high computational efficiency and accuracy, and the capability of performing scatter correction without modifying the clinical workflow (i.e., no extra scan/measurement data are needed) or modifying the imaging hardware. When implemented practically, this should improve the accuracy of CBCT image quantitation and significantly impact CBCT-based interventional procedures and adaptive radiation therapy.« less

Finding the Secret of Image Saliency in the Frequency Domain.

PubMed

Li, Jia; Duan, Ling-Yu; Chen, Xiaowu; Huang, Tiejun; Tian, Yonghong

2015-12-01

There are two sides to every story of visual saliency modeling in the frequency domain. On the one hand, image saliency can be effectively estimated by applying simple operations to the frequency spectrum. On the other hand, it is still unclear which part of the frequency spectrum contributes the most to popping-out targets and suppressing distractors. Toward this end, this paper tentatively explores the secret of image saliency in the frequency domain. From the results obtained in several qualitative and quantitative experiments, we find that the secret of visual saliency may mainly hide in the phases of intermediate frequencies. To explain this finding, we reinterpret the concept of discrete Fourier transform from the perspective of template-based contrast computation and thus develop several principles for designing the saliency detector in the frequency domain. Following these principles, we propose a novel approach to design the saliency detector under the assistance of prior knowledge obtained through both unsupervised and supervised learning processes. Experimental results on a public image benchmark show that the learned saliency detector outperforms 18 state-of-the-art approaches in predicting human fixations.

Region Segmentation in the Frequency Domain Applied to Upper Airway Real-Time Magnetic Resonance Images

PubMed Central

Narayanan, Shrikanth

2009-01-01

We describe a method for unsupervised region segmentation of an image using its spatial frequency domain representation. The algorithm was designed to process large sequences of real-time magnetic resonance (MR) images containing the 2-D midsagittal view of a human vocal tract airway. The segmentation algorithm uses an anatomically informed object model, whose fit to the observed image data is hierarchically optimized using a gradient descent procedure. The goal of the algorithm is to automatically extract the time-varying vocal tract outline and the position of the articulators to facilitate the study of the shaping of the vocal tract during speech production. PMID:19244005

Performance and scalability of Fourier domain optical coherence tomography acceleration using graphics processing units.

PubMed

Li, Jian; Bloch, Pavel; Xu, Jing; Sarunic, Marinko V; Shannon, Lesley

2011-05-01

Fourier domain optical coherence tomography (FD-OCT) provides faster line rates, better resolution, and higher sensitivity for noninvasive, in vivo biomedical imaging compared to traditional time domain OCT (TD-OCT). However, because the signal processing for FD-OCT is computationally intensive, real-time FD-OCT applications demand powerful computing platforms to deliver acceptable performance. Graphics processing units (GPUs) have been used as coprocessors to accelerate FD-OCT by leveraging their relatively simple programming model to exploit thread-level parallelism. Unfortunately, GPUs do not "share" memory with their host processors, requiring additional data transfers between the GPU and CPU. In this paper, we implement a complete FD-OCT accelerator on a consumer grade GPU/CPU platform. Our data acquisition system uses spectrometer-based detection and a dual-arm interferometer topology with numerical dispersion compensation for retinal imaging. We demonstrate that the maximum line rate is dictated by the memory transfer time and not the processing time due to the GPU platform's memory model. Finally, we discuss how the performance trends of GPU-based accelerators compare to the expected future requirements of FD-OCT data rates.

Development of an adaptive bilateral filter for evaluating color image difference

NASA Astrophysics Data System (ADS)

Wang, Zhaohui; Hardeberg, Jon Yngve

2012-04-01

Spatial filtering, which aims to mimic the contrast sensitivity function (CSF) of the human visual system (HVS), has previously been combined with color difference formulae for measuring color image reproduction errors. These spatial filters attenuate imperceptible information in images, unfortunately including high frequency edges, which are believed to be crucial in the process of scene analysis by the HVS. The adaptive bilateral filter represents a novel approach, which avoids the undesirable loss of edge information introduced by CSF-based filtering. The bilateral filter employs two Gaussian smoothing filters in different domains, i.e., spatial domain and intensity domain. We propose a method to decide the parameters, which are designed to be adaptive to the corresponding viewing conditions, and the quantity and homogeneity of information contained in an image. Experiments and discussions are given to support the proposal. A series of perceptual experiments were conducted to evaluate the performance of our approach. The experimental sample images were reproduced with variations in six image attributes: lightness, chroma, hue, compression, noise, and sharpness/blurriness. The Pearson's correlation values between the model-predicted image difference and the observed difference were employed to evaluate the performance, and compare it with that of spatial CIELAB and image appearance model.

A symmetrical image encryption scheme in wavelet and time domain

NASA Astrophysics Data System (ADS)

Luo, Yuling; Du, Minghui; Liu, Junxiu

2015-02-01

There has been an increasing concern for effective storages and secure transactions of multimedia information over the Internet. Then a great variety of encryption schemes have been proposed to ensure the information security while transmitting, but most of current approaches are designed to diffuse the data only in spatial domain which result in reducing storage efficiency. A lightweight image encryption strategy based on chaos is proposed in this paper. The encryption process is designed in transform domain. The original image is decomposed into approximation and detail components using integer wavelet transform (IWT); then as the more important component of the image, the approximation coefficients are diffused by secret keys generated from a spatiotemporal chaotic system followed by inverse IWT to construct the diffused image; finally a plain permutation is performed for diffusion image by the Logistic mapping in order to reduce the correlation between adjacent pixels further. Experimental results and performance analysis demonstrate the proposed scheme is an efficient, secure and robust encryption mechanism and it realizes effective coding compression to satisfy desirable storage.

Contrast in Terahertz Images of Archival Documents—Part II: Influence of Topographic Features

NASA Astrophysics Data System (ADS)

Bardon, Tiphaine; May, Robert K.; Taday, Philip F.; Strlič, Matija

2017-04-01

We investigate the potential of terahertz time-domain imaging in reflection mode to reveal archival information in documents in a non-invasive way. In particular, this study explores the parameters and signal processing tools that can be used to produce well-contrasted terahertz images of topographic features commonly found in archival documents, such as indentations left by a writing tool, as well as sieve lines. While the amplitude of the waveforms at a specific time delay can provide the most contrasted and legible images of topographic features on flat paper or parchment sheets, this parameter may not be suitable for documents that have a highly irregular surface, such as water- or fire-damaged documents. For analysis of such documents, cross-correlation of the time-domain signals can instead yield images with good contrast. Analysis of the frequency-domain representation of terahertz waveforms can also provide well-contrasted images of topographic features, with improved spatial resolution when utilising high-frequency content. Finally, we point out some of the limitations of these means of analysis for extracting information relating to topographic features of interest from documents.

Femtosecond Time-Resolved Photoelectron Imaging of Excited Doped Helium Nanodroplets

NASA Astrophysics Data System (ADS)

Saladrigas, Catherine; Bacellar, Camila; Leone, Stephen R.; Neumark, Daniel M.; Gessner, Oliver

2017-04-01

Helium nanodroplets are excellent matrices for high resolution spectroscopy and the study of ultracold chemistry. They are optically transparent. In their electronic ground state, interact very weakly with any atomic or molecular dopant. Electronically excited droplets, however, can strongly interact with dopants through a variety of relaxation mechanisms. Previously, these host-dopant interactions were studied in the energy domain, revealing Penning ionization processes enabled by energy transfer between the droplet host and atomic dopants. Using femtosecond time resolved XUV photoelectron imaging, we plan to perform complementary experiments in the time domain to gain deeper insight into the timescales of energy transfer processes and how they compete with internal droplet relaxation. First experiments will be performed using noble gas dopants, such as Kr and Ne, which will be compared to previous energy-domain studies. Femtosecond XUV pulses produced by high harmonic generation will be used to excite the droplets, IR and near-UV light will be used to monitor the relaxation dynamics. Using velocity map imaging, both photoelectron kinetic energies and angular distributions will be recorded as a function of time. Preliminary results and proposed experiments will be presented.

Musical Creativity “Revealed” in Brain Structure: Interplay between Motor, Default Mode, and Limbic Networks

PubMed Central

Bashwiner, David M.; Wertz, Christopher J.; Flores, Ranee A.; Jung, Rex E.

2016-01-01

Creative behaviors are among the most complex that humans engage in, involving not only highly intricate, domain-specific knowledge and skill, but also domain-general processing styles and the affective drive to create. This study presents structural imaging data indicating that musically creative people (as indicated by self-report) have greater cortical surface area or volume in a) regions associated with domain-specific higher-cognitive motor activity and sound processing (dorsal premotor cortex, supplementary and pre-supplementary motor areas, and planum temporale), b) domain-general creative-ideation regions associated with the default mode network (dorsomedial prefrontal cortex, middle temporal gyrus, and temporal pole), and c) emotion-related regions (orbitofrontal cortex, temporal pole, and amygdala). These findings suggest that domain-specific musical expertise, default-mode cognitive processing style, and intensity of emotional experience might all coordinate to motivate and facilitate the drive to create music. PMID:26888383

MULTIMODAL IMAGING OF DISEASE-ASSOCIATED PIGMENTARY CHANGES IN RETINITIS PIGMENTOSA.

PubMed

Schuerch, Kaspar; Marsiglia, Marcela; Lee, Winston; Tsang, Stephen H; Sparrow, Janet R

2016-12-01

Using multiple imaging modalities, we evaluated the changes in photoreceptor cells and retinal pigment epithelium (RPE) that are associated with bone spicule-shaped melanin pigmentation in retinitis pigmentosa. In a cohort of 60 patients with retinitis pigmentosa, short-wavelength autofluorescence, near-infrared autofluorescence (NIR-AF), NIR reflectance, spectral domain optical coherence tomography, and color fundus images were studied. Central AF rings were visible in both short-wavelength autofluorescence and NIR-AF images. Bone spicule pigmentation was nonreflective in NIR reflectance, hypoautofluorescent with short-wavelength autofluorescence and NIR-AF imaging, and presented as intraretinal hyperreflective foci in spectral domain optical coherence tomography images. In areas beyond the AF ring outer border, the photoreceptor ellipsoid zone band was absent in spectral domain optical coherence tomography and the visibility of choroidal vessels in short-wavelength autofluorescence, NIR-AF, and NIR reflectance images was indicative of reduced RPE pigmentation. Choroidal visibility was most pronounced in the zone approaching peripheral areas of bone spicule pigmentation; here RPE/Bruch membrane thinning became apparent in spectral domain optical coherence tomography. These findings are consistent with a process by which RPE cells vacate their monolayer and migrate into inner retina in response to photoreceptor cell degeneration. The remaining RPE spread undergo thinning and consequently become less pigmented. An explanation for the absence of NIR-AF melanin signal in relation to bone spicule pigmentation is not forthcoming.

Real-time calibration-free C-scan images of the eye fundus using Master Slave swept source optical coherence tomography

NASA Astrophysics Data System (ADS)

Bradu, Adrian; Kapinchev, Konstantin; Barnes, Fred; Garway-Heath, David F.; Rajendram, Ranjan; Keane, Pearce; Podoleanu, Adrian G.

2015-03-01

Recently, we introduced a novel Optical Coherence Tomography (OCT) method, termed as Master Slave OCT (MS-OCT), specialized for delivering en-face images. This method uses principles of spectral domain interfereometry in two stages. MS-OCT operates like a time domain OCT, selecting only signals from a chosen depth only while scanning the laser beam across the eye. Time domain OCT allows real time production of an en-face image, although relatively slowly. As a major advance, the Master Slave method allows collection of signals from any number of depths, as required by the user. The tremendous advantage in terms of parallel provision of data from numerous depths could not be fully employed by using multi core processors only. The data processing required to generate images at multiple depths simultaneously is not achievable with commodity multicore processors only. We compare here the major improvement in processing and display, brought about by using graphic cards. We demonstrate images obtained with a swept source at 100 kHz (which determines an acquisition time [Ta] for a frame of 200×200 pixels2 of Ta =1.6 s). By the end of the acquired frame being scanned, using our computing capacity, 4 simultaneous en-face images could be created in T = 0.8 s. We demonstrate that by using graphic cards, 32 en-face images can be displayed in Td 0.3 s. Other faster swept source engines can be used with no difference in terms of Td. With 32 images (or more), volumes can be created for 3D display, using en-face images, as opposed to the current technology where volumes are created using cross section OCT images.

Multi-functional angiographic OFDI using frequency-multiplexed dual-beam illumination

PubMed Central

Kim, SunHee; Park, Taejin; Jang, Sun-Joo; Nam, Ahhyun S.; Vakoc, Benjamin J.; Oh, Wang-Yuhl

2015-01-01

Detection of blood flow inside the tissue sample can be achieved by measuring the local change of complex signal over time in angiographic optical coherence tomography (OCT). In conventional angiographic OCT, the transverse displacement of the imaging beam during the time interval between a pair of OCT signal measurements must be significantly reduced to minimize the noise due to the beam scanning-induced phase decorrelation at the expense of the imaging speed. Recent introduction of dual-beam scan method either using polarization encoding or two identical imaging systems in spectral-domain (SD) OCT scheme shows potential for high-sensitivity vasculature imaging without suffering from spurious phase noise caused by the beam scanning-induced spatial decorrelation. In this paper, we present multi-functional angiographic optical frequency domain imaging (OFDI) using frequency-multiplexed dual-beam illumination. This frequency multiplexing scheme, utilizing unique features of OFDI, provides spatially separated dual imaging beams occupying distinct electrical frequency bands that can be demultiplexed in the frequency domain processing. We demonstrate the 3D multi-functional imaging of the normal mouse skin in the dorsal skin fold chamber visualizing distinct layer structures from the intensity imaging, information about mechanical integrity from the polarization-sensitive imaging, and depth-resolved microvasculature from the angiographic imaging that are simultaneously acquired and automatically co-registered. PMID:25968731

Integrating image processing and classification technology into automated polarizing film defect inspection

NASA Astrophysics Data System (ADS)

Kuo, Chung-Feng Jeffrey; Lai, Chun-Yu; Kao, Chih-Hsiang; Chiu, Chin-Hsun

2018-05-01

In order to improve the current manual inspection and classification process for polarizing film on production lines, this study proposes a high precision automated inspection and classification system for polarizing film, which is used for recognition and classification of four common defects: dent, foreign material, bright spot, and scratch. First, the median filter is used to remove the impulse noise in the defect image of polarizing film. The random noise in the background is smoothed by the improved anisotropic diffusion, while the edge detail of the defect region is sharpened. Next, the defect image is transformed by Fourier transform to the frequency domain, combined with a Butterworth high pass filter to sharpen the edge detail of the defect region, and brought back by inverse Fourier transform to the spatial domain to complete the image enhancement process. For image segmentation, the edge of the defect region is found by Canny edge detector, and then the complete defect region is obtained by two-stage morphology processing. For defect classification, the feature values, including maximum gray level, eccentricity, the contrast, and homogeneity of gray level co-occurrence matrix (GLCM) extracted from the images, are used as the input of the radial basis function neural network (RBFNN) and back-propagation neural network (BPNN) classifier, 96 defect images are then used as training samples, and 84 defect images are used as testing samples to validate the classification effect. The result shows that the classification accuracy by using RBFNN is 98.9%. Thus, our proposed system can be used by manufacturing companies for a higher yield rate and lower cost. The processing time of one single image is 2.57 seconds, thus meeting the practical application requirement of an industrial production line.

Evidential Reasoning in Expert Systems for Image Analysis.

DTIC Science & Technology

1985-02-01

techniques to image analysis (IA). There is growing evidence that these techniques offer significant improvements in image analysis , particularly in the...2) to provide a common framework for analysis, (3) to structure the ER process for major expert-system tasks in image analysis , and (4) to identify...approaches to three important tasks for expert systems in the domain of image analysis . This segment concluded with an assessment of the strengths

Thermal-induced domain wall motion of tip-inverted micro/nanodomains in near-stoichiometric LiNbO3 crystals

NASA Astrophysics Data System (ADS)

Liu, X. Y.; Kitamura, K.; Liu, Y. M.; Ohuchi, F. S.; Li, J. Y.

2011-09-01

Thermal-induced domain wall motion of tip-inverted micro/nanodomains in near-stoichiometric LiNbO3 single crystals was investigated using piezoresponse force microscopy (PFM). The domain wall motion was observed in PFM phase and amplitude images at room temperature after the sample was subjected to a thermal process at a heating temperature higher than 100 °C. In hexagonal domains with only y walls, predetermined nucleation with layer-by-layer growth is the main mechanism for the domain wall motion. In the domains composed of both x walls and y walls, the x walls are more mobile than the y walls, and the domain wall motion starts from the random nucleation of steps along the x walls that finally grow into y walls. The domain wall motion in the near-stoichiometric LiNbO3 crystal is attributed to the energy-preferable domain wall orientation, the pyroelectric effect, and the screening charge variation caused by the thermal process.

Optimization of energy window and evaluation of scatter compensation methods in MPS using the ideal observer with model mismatch

NASA Astrophysics Data System (ADS)

Ghaly, Michael; Links, Jonathan M.; Frey, Eric

2015-03-01

In this work, we used the ideal observer (IO) and IO with model mismatch (IO-MM) applied in the projection domain and an anthropomorphic Channelized Hotelling Observer (CHO) applied to reconstructed images to optimize the acquisition energy window width and evaluate various scatter compensation methods in the context of a myocardial perfusion SPECT defect detection task. The IO has perfect knowledge of the image formation process and thus reflects performance with perfect compensation for image-degrading factors. Thus, using the IO to optimize imaging systems could lead to suboptimal parameters compared to those optimized for humans interpreting SPECT images reconstructed with imperfect or no compensation. The IO-MM allows incorporating imperfect system models into the IO optimization process. We found that with near-perfect scatter compensation, the optimal energy window for the IO and CHO were similar; in its absence the IO-MM gave a better prediction of the optimal energy window for the CHO using different scatter compensation methods. These data suggest that the IO-MM may be useful for projection-domain optimization when model mismatch is significant, and that the IO is useful when followed by reconstruction with good models of the image formation process.

Striping artifact reduction in lunar orbiter mosaic images

USGS Publications Warehouse

Mlsna, P.A.; Becker, T.

2006-01-01

Photographic images of the moon from the 1960s Lunar Orbiter missions are being processed into maps for visual use. The analog nature of the images has produced numerous artifacts, the chief of which causes a vertical striping pattern in mosaic images formed from a series of filmstrips. Previous methods of stripe removal tended to introduce ringing and aliasing problems in the image data. This paper describes a recently developed alternative approach that succeeds at greatly reducing the striping artifacts while avoiding the creation of ringing and aliasing artifacts. The algorithm uses a one dimensional frequency domain step to deal with the periodic component of the striping artifact and a spatial domain step to handle the aperiodic residue. Several variations of the algorithm have been explored. Results, strengths, and remaining challenges are presented. ?? 2006 IEEE.

Determination of bulk domain structure and magnetization processes in bcc ferromagnetic alloys: Analysis of magnetostriction in F e83G a17

NASA Astrophysics Data System (ADS)

He, Yangkun; Coey, J. M. D.; Schaefer, Rudolf; Jiang, Chengbao

2018-01-01

The ground state of macroscopic samples of magnetically ordered materials is a domain state because of magnetostatic energy or entropy, yet we have limited experimental means for imaging the bulk domain structure and the magnetization process directly. The common methods available reveal the domains at the surface or in electron- or x-ray transparent lamellae, not those in the bulk. The magnetization curve just reflects the vector sum of the moments of all the domains in the sample, but magnetostriction curves are more informative. They are strongly influenced by the domain structure in the unmagnetized state and its evolution during the magnetization process in an applied field. Here we report a method of determining the bulk domain structure in a cubic magnetostrictive material by combining magneto-optic Kerr microscopy with magnetostriction and magnetization measurements on single crystals as a function of applied field. We analyze the magnetostriction of F e83G a17 crystals in terms of a domain structure that is greatly influenced by sample shape and heat treatment. Saturation magnetostriction measurements are used to determine the fraction of domains orientated along the three 〈100 〉 axes in the initial state. Domain wall motion and rotation process have characteristic signatures in the magnetostriction curves, including those associated with the Δ E effect and domain rotation through a 〈110 〉 auxetic direction.

Image reconstruction by domain-transform manifold learning.

PubMed

Zhu, Bo; Liu, Jeremiah Z; Cauley, Stephen F; Rosen, Bruce R; Rosen, Matthew S

2018-03-21

Image reconstruction is essential for imaging applications across the physical and life sciences, including optical and radar systems, magnetic resonance imaging, X-ray computed tomography, positron emission tomography, ultrasound imaging and radio astronomy. During image acquisition, the sensor encodes an intermediate representation of an object in the sensor domain, which is subsequently reconstructed into an image by an inversion of the encoding function. Image reconstruction is challenging because analytic knowledge of the exact inverse transform may not exist a priori, especially in the presence of sensor non-idealities and noise. Thus, the standard reconstruction approach involves approximating the inverse function with multiple ad hoc stages in a signal processing chain, the composition of which depends on the details of each acquisition strategy, and often requires expert parameter tuning to optimize reconstruction performance. Here we present a unified framework for image reconstruction-automated transform by manifold approximation (AUTOMAP)-which recasts image reconstruction as a data-driven supervised learning task that allows a mapping between the sensor and the image domain to emerge from an appropriate corpus of training data. We implement AUTOMAP with a deep neural network and exhibit its flexibility in learning reconstruction transforms for various magnetic resonance imaging acquisition strategies, using the same network architecture and hyperparameters. We further demonstrate that manifold learning during training results in sparse representations of domain transforms along low-dimensional data manifolds, and observe superior immunity to noise and a reduction in reconstruction artefacts compared with conventional handcrafted reconstruction methods. In addition to improving the reconstruction performance of existing acquisition methodologies, we anticipate that AUTOMAP and other learned reconstruction approaches will accelerate the development of new acquisition strategies across imaging modalities.

Image reconstruction by domain-transform manifold learning

NASA Astrophysics Data System (ADS)

Zhu, Bo; Liu, Jeremiah Z.; Cauley, Stephen F.; Rosen, Bruce R.; Rosen, Matthew S.

2018-03-01

Image reconstruction is essential for imaging applications across the physical and life sciences, including optical and radar systems, magnetic resonance imaging, X-ray computed tomography, positron emission tomography, ultrasound imaging and radio astronomy. During image acquisition, the sensor encodes an intermediate representation of an object in the sensor domain, which is subsequently reconstructed into an image by an inversion of the encoding function. Image reconstruction is challenging because analytic knowledge of the exact inverse transform may not exist a priori, especially in the presence of sensor non-idealities and noise. Thus, the standard reconstruction approach involves approximating the inverse function with multiple ad hoc stages in a signal processing chain, the composition of which depends on the details of each acquisition strategy, and often requires expert parameter tuning to optimize reconstruction performance. Here we present a unified framework for image reconstruction—automated transform by manifold approximation (AUTOMAP)—which recasts image reconstruction as a data-driven supervised learning task that allows a mapping between the sensor and the image domain to emerge from an appropriate corpus of training data. We implement AUTOMAP with a deep neural network and exhibit its flexibility in learning reconstruction transforms for various magnetic resonance imaging acquisition strategies, using the same network architecture and hyperparameters. We further demonstrate that manifold learning during training results in sparse representations of domain transforms along low-dimensional data manifolds, and observe superior immunity to noise and a reduction in reconstruction artefacts compared with conventional handcrafted reconstruction methods. In addition to improving the reconstruction performance of existing acquisition methodologies, we anticipate that AUTOMAP and other learned reconstruction approaches will accelerate the development of new acquisition strategies across imaging modalities.

Angle-domain common-image gathers from anisotropic Gaussian beam migration and its application to anisotropy-induced imaging errors analysis

NASA Astrophysics Data System (ADS)

Han, Jianguang; Wang, Yun; Yu, Changqing; Chen, Peng

2017-02-01

An approach for extracting angle-domain common-image gathers (ADCIGs) from anisotropic Gaussian beam prestack depth migration (GB-PSDM) is presented in this paper. The propagation angle is calculated in the process of migration using the real-value traveltime information of Gaussian beam. Based on the above, we further investigate the effects of anisotropy on GB-PSDM, where the corresponding ADCIGs are extracted to assess the quality of migration images. The test results of the VTI syncline model and the TTI thrust sheet model show that anisotropic parameters ɛ, δ, and tilt angle 𝜃, have a great influence on the accuracy of the migrated image in anisotropic media, and ignoring any one of them will cause obvious imaging errors. The anisotropic GB-PSDM with the true anisotropic parameters can obtain more accurate seismic images of subsurface structures in anisotropic media.

Fingerprint image enhancement by differential hysteresis processing.

PubMed

Blotta, Eduardo; Moler, Emilce

2004-05-10

A new method to enhance defective fingerprints images through image digital processing tools is presented in this work. When the fingerprints have been taken without any care, blurred and in some cases mostly illegible, as in the case presented here, their classification and comparison becomes nearly impossible. A combination of spatial domain filters, including a technique called differential hysteresis processing (DHP), is applied to improve these kind of images. This set of filtering methods proved to be satisfactory in a wide range of cases by uncovering hidden details that helped to identify persons. Dactyloscopy experts from Policia Federal Argentina and the EAAF have validated these results.

Temporal Processing of Dynamic Positron Emission Tomography via Principal Component Analysis in the Sinogram Domain

NASA Astrophysics Data System (ADS)

Chen, Zhe; Parker, B. J.; Feng, D. D.; Fulton, R.

2004-10-01

In this paper, we compare various temporal analysis schemes applied to dynamic PET for improved quantification, image quality and temporal compression purposes. We compare an optimal sampling schedule (OSS) design, principal component analysis (PCA) applied in the image domain, and principal component analysis applied in the sinogram domain; for region-of-interest quantification, sinogram-domain PCA is combined with the Huesman algorithm to quantify from the sinograms directly without requiring reconstruction of all PCA channels. Using a simulated phantom FDG brain study and three clinical studies, we evaluate the fidelity of the compressed data for estimation of local cerebral metabolic rate of glucose by a four-compartment model. Our results show that using a noise-normalized PCA in the sinogram domain gives similar compression ratio and quantitative accuracy to OSS, but with substantially better precision. These results indicate that sinogram-domain PCA for dynamic PET can be a useful preprocessing stage for PET compression and quantification applications.

Unsupervised domain adaptation for early detection of drought stress in hyperspectral images

NASA Astrophysics Data System (ADS)

Schmitter, P.; Steinrücken, J.; Römer, C.; Ballvora, A.; Léon, J.; Rascher, U.; Plümer, L.

2017-09-01

Hyperspectral images can be used to uncover physiological processes in plants if interpreted properly. Machine Learning methods such as Support Vector Machines (SVM) and Random Forests have been applied to estimate development of biomass and detect and predict plant diseases and drought stress. One basic requirement of machine learning implies, that training and testing is done in the same domain and the same distribution. Different genotypes, environmental conditions, illumination and sensors violate this requirement in most practical circumstances. Here, we present an approach, which enables the detection of physiological processes by transferring the prior knowledge within an existing model into a related target domain, where no label information is available. We propose a two-step transformation of the target features, which enables a direct application of an existing model. The transformation is evaluated by an objective function including additional prior knowledge about classification and physiological processes in plants. We have applied the approach to three sets of hyperspectral images, which were acquired with different plant species in different environments observed with different sensors. It is shown, that a classification model, derived on one of the sets, delivers satisfying classification results on the transformed features of the other data sets. Furthermore, in all cases early non-invasive detection of drought stress was possible.

Feature-Motivated Simplified Adaptive PCNN-Based Medical Image Fusion Algorithm in NSST Domain.

PubMed

Ganasala, Padma; Kumar, Vinod

2016-02-01

Multimodality medical image fusion plays a vital role in diagnosis, treatment planning, and follow-up studies of various diseases. It provides a composite image containing critical information of source images required for better localization and definition of different organs and lesions. In the state-of-the-art image fusion methods based on nonsubsampled shearlet transform (NSST) and pulse-coupled neural network (PCNN), authors have used normalized coefficient value to motivate the PCNN-processing both low-frequency (LF) and high-frequency (HF) sub-bands. This makes the fused image blurred and decreases its contrast. The main objective of this work is to design an image fusion method that gives the fused image with better contrast, more detail information, and suitable for clinical use. We propose a novel image fusion method utilizing feature-motivated adaptive PCNN in NSST domain for fusion of anatomical images. The basic PCNN model is simplified, and adaptive-linking strength is used. Different features are used to motivate the PCNN-processing LF and HF sub-bands. The proposed method is extended for fusion of functional image with an anatomical image in improved nonlinear intensity hue and saturation (INIHS) color model. Extensive fusion experiments have been performed on CT-MRI and SPECT-MRI datasets. Visual and quantitative analysis of experimental results proved that the proposed method provides satisfactory fusion outcome compared to other image fusion methods.

Noise analysis for near field 3-D FM-CW radar imaging systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sheen, David M.

2015-06-19

Near field radar imaging systems are used for several applications including concealed weapon detection in airports and other high-security venues. Despite the near-field operation, phase noise and thermal noise can limit the performance in several ways including reduction in system sensitivity and reduction of image dynamic range. In this paper, the effects of thermal noise, phase noise, and processing gain are analyzed in the context of a near field 3-D FM-CW imaging radar as might be used for concealed weapon detection. In addition to traditional frequency domain analysis, a time-domain simulation is employed to graphically demonstrate the effect of thesemore » noise sources on a fast-chirping FM-CW system.« less

Image Fusion Algorithms Using Human Visual System in Transform Domain

NASA Astrophysics Data System (ADS)

Vadhi, Radhika; Swamy Kilari, Veera; Samayamantula, Srinivas Kumar

2017-08-01

The endeavor of digital image fusion is to combine the important visual parts from various sources to advance the visibility eminence of the image. The fused image has a more visual quality than any source images. In this paper, the Human Visual System (HVS) weights are used in the transform domain to select appropriate information from various source images and then to attain a fused image. In this process, mainly two steps are involved. First, apply the DWT to the registered source images. Later, identify qualitative sub-bands using HVS weights. Hence, qualitative sub-bands are selected from different sources to form high quality HVS based fused image. The quality of the HVS based fused image is evaluated with general fusion metrics. The results show the superiority among the state-of-the art resolution Transforms (MRT) such as Discrete Wavelet Transform (DWT), Stationary Wavelet Transform (SWT), Contourlet Transform (CT), and Non Sub Sampled Contourlet Transform (NSCT) using maximum selection fusion rule.

The Hippocampus Supports Encoding of Between-Domain Associations within Working Memory

ERIC Educational Resources Information Center

Piekema, Carinne; Kessel, Roy P. C.; Rijpkema, Mark; Fernandez, Guillen

2009-01-01

It has been established that the medial temporal lobe, including the hippocampus, is crucial for associative memory. The aim of the current functional magnetic resonance imaging (fMRI) study was to investigate whether the hippocampus is differentially activated for associations between items processed in the same neocortical region (within-domain)…

Fluorescence diffuse tomography of small animals with DsRed2 fluorescent protein

NASA Astrophysics Data System (ADS)

Turchin, I. V.; Plehanov, V. I.; Orlova, A. G.; Kamenskiy, V. A.; Kleshnin, M. S.; Shirmanova, M. V.; Shakhova, N. M.; Balalaeva, I. V.; Savitskiy, A. P.

2006-05-01

Fluorescent compounds are used as markers to diagnose oncological diseases, to study molecular processes typical for carcinogenesis, and to investigate metastasis formation and tumor regress under the influence of therapeutics. Different types of tomography, such as continuous wave (CW), frequency-domain (FD), and time-domain (TD) tomography, allow fluorescence imaging of tumors located deep in human or animal tissue. In this work, preliminary results of the frequency domain fluorescent diffuse tomography (FDT) method in application to DsRed2 protein as a fluorescent agent are presented. For the first step of our experiments, we utilized low-frequency amplitude modulation (1 kHz) of second harmonic of Nd: YAG (532 nm). The transilluminative configuration was used in the setup. The results of post mortem experiments with capsules containing DsRed2 inserted inside the esophagus of a 3-day-old hairless rat to simulate tumor are shown. An algorithm of processing fluorescent images based on calculating the zero of maximum curvature has been applied to detect fluorescent inclusion boundaries in the image. This work demonstrates the potential capability of the FDT method for imaging deep fluorescent tumors in human tissue or animal models of human cancer. Improvement of the setup can be accomplished by using high-frequency modulation (using a 110-MHz acoustooptical modulator).

A Kinect based sign language recognition system using spatio-temporal features

NASA Astrophysics Data System (ADS)

Memiş, Abbas; Albayrak, Songül

2013-12-01

This paper presents a sign language recognition system that uses spatio-temporal features on RGB video images and depth maps for dynamic gestures of Turkish Sign Language. Proposed system uses motion differences and accumulation approach for temporal gesture analysis. Motion accumulation method, which is an effective method for temporal domain analysis of gestures, produces an accumulated motion image by combining differences of successive video frames. Then, 2D Discrete Cosine Transform (DCT) is applied to accumulated motion images and temporal domain features transformed into spatial domain. These processes are performed on both RGB images and depth maps separately. DCT coefficients that represent sign gestures are picked up via zigzag scanning and feature vectors are generated. In order to recognize sign gestures, K-Nearest Neighbor classifier with Manhattan distance is performed. Performance of the proposed sign language recognition system is evaluated on a sign database that contains 1002 isolated dynamic signs belongs to 111 words of Turkish Sign Language (TSL) in three different categories. Proposed sign language recognition system has promising success rates.

Level set segmentation of medical images based on local region statistics and maximum a posteriori probability.

PubMed

Cui, Wenchao; Wang, Yi; Lei, Tao; Fan, Yangyu; Feng, Yan

2013-01-01

This paper presents a variational level set method for simultaneous segmentation and bias field estimation of medical images with intensity inhomogeneity. In our model, the statistics of image intensities belonging to each different tissue in local regions are characterized by Gaussian distributions with different means and variances. According to maximum a posteriori probability (MAP) and Bayes' rule, we first derive a local objective function for image intensities in a neighborhood around each pixel. Then this local objective function is integrated with respect to the neighborhood center over the entire image domain to give a global criterion. In level set framework, this global criterion defines an energy in terms of the level set functions that represent a partition of the image domain and a bias field that accounts for the intensity inhomogeneity of the image. Therefore, image segmentation and bias field estimation are simultaneously achieved via a level set evolution process. Experimental results for synthetic and real images show desirable performances of our method.

Neuroimaging Feature Terminology: A Controlled Terminology for the Annotation of Brain Imaging Features

PubMed Central

Iyappan, Anandhi; Younesi, Erfan; Redolfi, Alberto; Vrooman, Henri; Khanna, Shashank; Frisoni, Giovanni B.; Hofmann-Apitius, Martin

2017-01-01

Ontologies and terminologies are used for interoperability of knowledge and data in a standard manner among interdisciplinary research groups. Existing imaging ontologies capture general aspects of the imaging domain as a whole such as methodological concepts or calibrations of imaging instruments. However, none of the existing ontologies covers the diagnostic features measured by imaging technologies in the context of neurodegenerative diseases. Therefore, the Neuro-Imaging Feature Terminology (NIFT) was developed to organize the knowledge domain of measured brain features in association with neurodegenerative diseases by imaging technologies. The purpose is to identify quantitative imaging biomarkers that can be extracted from multi-modal brain imaging data. This terminology attempts to cover measured features and parameters in brain scans relevant to disease progression. In this paper, we demonstrate the systematic retrieval of measured indices from literature and how the extracted knowledge can be further used for disease modeling that integrates neuroimaging features with molecular processes. PMID:28731430

Real-time blind image deconvolution based on coordinated framework of FPGA and DSP

NASA Astrophysics Data System (ADS)

Wang, Ze; Li, Hang; Zhou, Hua; Liu, Hongjun

2015-10-01

Image restoration takes a crucial place in several important application domains. With the increasing of computation requirement as the algorithms become much more complexity, there has been a significant rise in the need for accelerating implementation. In this paper, we focus on an efficient real-time image processing system for blind iterative deconvolution method by means of the Richardson-Lucy (R-L) algorithm. We study the characteristics of algorithm, and an image restoration processing system based on the coordinated framework of FPGA and DSP (CoFD) is presented. Single precision floating-point processing units with small-scale cascade and special FFT/IFFT processing modules are adopted to guarantee the accuracy of the processing. Finally, Comparing experiments are done. The system could process a blurred image of 128×128 pixels within 32 milliseconds, and is up to three or four times faster than the traditional multi-DSPs systems.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, Donald F.; Schulz, Carl; Konijnenburg, Marco

High-resolution Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometry imaging enables the spatial mapping and identification of biomolecules from complex surfaces. The need for long time-domain transients, and thus large raw file sizes, results in a large amount of raw data (“big data”) that must be processed efficiently and rapidly. This can be compounded by largearea imaging and/or high spatial resolution imaging. For FT-ICR, data processing and data reduction must not compromise the high mass resolution afforded by the mass spectrometer. The continuous mode “Mosaic Datacube” approach allows high mass resolution visualization (0.001 Da) of mass spectrometry imaging data, butmore » requires additional processing as compared to featurebased processing. We describe the use of distributed computing for processing of FT-ICR MS imaging datasets with generation of continuous mode Mosaic Datacubes for high mass resolution visualization. An eight-fold improvement in processing time is demonstrated using a Dutch nationally available cloud service.« less

Image/Time Series Mining Algorithms: Applications to Developmental Biology, Document Processing and Data Streams

ERIC Educational Resources Information Center

Tataw, Oben Moses

2013-01-01

Interdisciplinary research in computer science requires the development of computational techniques for practical application in different domains. This usually requires careful integration of different areas of technical expertise. This dissertation presents image and time series analysis algorithms, with practical interdisciplinary applications…

A frequency domain radar interferometric imaging (FII) technique based on high-resolution methods

NASA Astrophysics Data System (ADS)

Luce, H.; Yamamoto, M.; Fukao, S.; Helal, D.; Crochet, M.

2001-01-01

In the present work, we propose a frequency-domain interferometric imaging (FII) technique for a better knowledge of the vertical distribution of the atmospheric scatterers detected by MST radars. This is an extension of the dual frequency-domain interferometry (FDI) technique to multiple frequencies. Its objective is to reduce the ambiguity (resulting from the use of only two adjacent frequencies), inherent with the FDI technique. Different methods, commonly used in antenna array processing, are first described within the context of application to the FII technique. These methods are the Fourier-based imaging, the Capon's and the singular value decomposition method used with the MUSIC algorithm. Some preliminary simulations and tests performed on data collected with the middle and upper atmosphere (MU) radar (Shigaraki, Japan) are also presented. This work is a first step in the developments of the FII technique which seems to be very promising.

Orthographic Stereo Correlator on the Terrain Model for Apollo Metric Images

NASA Technical Reports Server (NTRS)

Kim, Taemin; Husmann, Kyle; Moratto, Zachary; Nefian, Ara V.

2011-01-01

A stereo correlation method on the object domain is proposed to generate the accurate and dense Digital Elevation Models (DEMs) from lunar orbital imagery. The NASA Ames Intelligent Robotics Group (IRG) aims to produce high-quality terrain reconstructions of the Moon from Apollo Metric Camera (AMC) data. In particular, IRG makes use of a stereo vision process, the Ames Stereo Pipeline (ASP), to automatically generate DEMs from consecutive AMC image pairs. Given camera parameters of an image pair from bundle adjustment in ASP, a correlation window is defined on the terrain with the predefined surface normal of a post rather than image domain. The squared error of back-projected images on the local terrain is minimized with respect to the post elevation. This single dimensional optimization is solved efficiently and improves the accuracy of the elevation estimate.

Imaging the eye fundus with real-time en-face spectral domain optical coherence tomography

PubMed Central

Bradu, Adrian; Podoleanu, Adrian Gh.

2014-01-01

Real-time display of processed en-face spectral domain optical coherence tomography (SD-OCT) images is important for diagnosis. However, due to many steps of data processing requirements, such as Fast Fourier transformation (FFT), data re-sampling, spectral shaping, apodization, zero padding, followed by software cut of the 3D volume acquired to produce an en-face slice, conventional high-speed SD-OCT cannot render an en-face OCT image in real time. Recently we demonstrated a Master/Slave (MS)-OCT method that is highly parallelizable, as it provides reflectivity values of points at depth within an A-scan in parallel. This allows direct production of en-face images. In addition, the MS-OCT method does not require data linearization, which further simplifies the processing. The computation in our previous paper was however time consuming. In this paper we present an optimized algorithm that can be used to provide en-face MS-OCT images much quicker. Using such an algorithm we demonstrate around 10 times faster production of sets of en-face OCT images than previously obtained as well as simultaneous real-time display of up to 4 en-face OCT images of 200 × 200 pixels2 from the fovea and the optic nerve of a volunteer. We also demonstrate 3D and B-scan OCT images obtained from sets of MS-OCT C-scans, i.e. with no FFT and no intermediate step of generation of A-scans. PMID:24761303

Sparsity Aware Adaptive Radar Sensor Imaging in Complex Scattering Environments

DTIC Science & Technology

2015-06-15

while meeting the requirement on the peak to average power ratio. Third, we study impact of waveform encoding on nonlinear electromagnetic tomographic...Enyue Lu. Time Domain Electromagnetic Tomography Using Propagation and Backpropagation Method, IEEE International Conference on Image Processing...Received Paper 3.00 4.00 Yuanwei Jin, Chengdon Dong, Enyue Lu. Waveform Encoding for Nonlinear Electromagnetic Tomographic Imaging, IEEE Global

Quantum image processing: A review of advances in its security technologies

NASA Astrophysics Data System (ADS)

Yan, Fei; Iliyasu, Abdullah M.; Le, Phuc Q.

In this review, we present an overview of the advances made in quantum image processing (QIP) comprising of the image representations, the operations realizable on them, and the likely protocols and algorithms for their applications. In particular, we focus on recent progresses on QIP-based security technologies including quantum watermarking, quantum image encryption, and quantum image steganography. This review is aimed at providing readers with a succinct, yet adequate compendium of the progresses made in the QIP sub-area. Hopefully, this effort will stimulate further interest aimed at the pursuit of more advanced algorithms and experimental validations for available technologies and extensions to other domains.

Real time display Fourier-domain OCT using multi-thread parallel computing with data vectorization

NASA Astrophysics Data System (ADS)

Eom, Tae Joong; Kim, Hoon Seop; Kim, Chul Min; Lee, Yeung Lak; Choi, Eun-Seo

2011-03-01

We demonstrate a real-time display of processed OCT images using multi-thread parallel computing with a quad-core CPU of a personal computer. The data of each A-line are treated as one vector to maximize the data translation rate between the cores of the CPU and RAM stored image data. A display rate of 29.9 frames/sec for processed OCT data (4096 FFT-size x 500 A-scans) is achieved in our system using a wavelength swept source with 52-kHz swept frequency. The data processing times of the OCT image and a Doppler OCT image with a 4-time average are 23.8 msec and 91.4 msec.

Relationships between digital signal processing and control and estimation theory

NASA Technical Reports Server (NTRS)

Willsky, A. S.

1978-01-01

Research areas associated with digital signal processing and control and estimation theory are identified. Particular attention is given to image processing, system identification problems (parameter identification, linear prediction, least squares, Kalman filtering), stability analyses (the use of the Liapunov theory, frequency domain criteria, passivity), and multiparameter systems, distributed processes, and random fields.

Speckle size in optical Fourier domain imaging

NASA Astrophysics Data System (ADS)

Lamouche, G.; Vergnole, S.; Bisaillon, C.-E.; Dufour, M.; Maciejko, R.; Monchalin, J.-P.

2007-06-01

As in conventional time-domain optical coherence tomography (OCT), speckle is inherent to any Optical Fourier Domain Imaging (OFDI) of biological tissue. OFDI is also known as swept-source OCT (SS-OCT). The axial speckle size is mainly determined by the OCT resolution length and the transverse speckle size by the focusing optics illuminating the sample. There is also a contribution from the sample related to the number of scatterers contained within the probed volume. In the OFDI data processing, there is some liberty in selecting the range of wavelengths used and this allows variation in the OCT resolution length. Consequently the probed volume can be varied. By performing measurements on an optical phantom with a controlled density of discrete scatterers and by changing the probed volume with different range of wavelengths in the OFDI data processing, there is an obvious change in the axial speckle size, but we show that there is also a less obvious variation in the transverse speckle size. This work contributes to a better understanding of speckle in OCT.

Body image in the person with a stoma.

PubMed

Cohen, A

1991-01-01

Body image is the mental picture one has of one's physical being that develops from birth and continues throughout life and is related to different factors affecting its formation and dynamics. A crisis such as the creation of a stoma leads to an alteration in body image and an awareness of the meaning of the change in appearance and function of an individual. The individual's behavior is examined in several domains: physical, mental, emotional, social, sexual, and economical. When one domain is disturbed the others will be influenced. A person's rehabilitation after ostomy surgery is a continuous process of adaptation and is directed toward returning to a normal way of life. Many factors affect this adaptation to an alteration in body image and are relevant to the patient and family. These factors include, but are not limited to, the disease process, treatment(s), and medical and nursing care in the hospital and community. Knowledge about actual and potential problems associated with an alteration in body image enables the nurse to assess the meaning of the alteration in body image for the individual patient and family, provide counseling before and after the surgery, and intervene so that the individual will be able to adapt to an alteration in body image and return to one's previous activities of daily living and lifestyle.

Detection and imaging of moving objects with SAR by a joint space-time-frequency processing

NASA Astrophysics Data System (ADS)

Barbarossa, Sergio; Farina, Alfonso

This paper proposes a joint spacetime-frequency processing scheme for the detection and imaging of moving targets by Synthetic Aperture Radars (SAR). The method is based on the availability of an array antenna. The signals received by the array elements are combined, in a spacetime processor, to cancel the clutter. Then, they are analyzed in the time-frequency domain, by computing their Wigner-Ville Distribution (WVD), in order to estimate the instantaneous frequency, to be used for the successive phase compensation, necessary to produce a high resolution image.

Controllable growth of shaped graphene domains by atmospheric pressure chemical vapour deposition

NASA Astrophysics Data System (ADS)

Fan, Lili; Li, Zhen; Li, Xiao; Wang, Kunlin; Zhong, Minlin; Wei, Jinquan; Wu, Dehai; Zhu, Hongwei

2011-12-01

Graphene domains in different shapes have been grown on copper substrates via atmospheric pressure chemical vapour deposition by controlling the growth process parameters. Under stabilized conditions, graphene domains tend to be six-fold symmetric hexagons under low flow rate methane with some domains in an irregular hexagonal shape. After further varying the growth duration, methane flow rate, and temperature, graphene domains have developed shapes from hexagon to shovel and dendrite. Two connecting modes, through overlap and merging of adjacent graphene domains, are proposed.Graphene domains in different shapes have been grown on copper substrates via atmospheric pressure chemical vapour deposition by controlling the growth process parameters. Under stabilized conditions, graphene domains tend to be six-fold symmetric hexagons under low flow rate methane with some domains in an irregular hexagonal shape. After further varying the growth duration, methane flow rate, and temperature, graphene domains have developed shapes from hexagon to shovel and dendrite. Two connecting modes, through overlap and merging of adjacent graphene domains, are proposed. Electronic supplementary information (ESI) available: Schematics of CVD setups for graphene growth, Raman spectra and SEM images. See DOI: 10.1039/c1nr11480h

Deep learning for low-dose CT

NASA Astrophysics Data System (ADS)

Chen, Hu; Zhang, Yi; Zhou, Jiliu; Wang, Ge

2017-09-01

Given the potential risk of X-ray radiation to the patient, low-dose CT has attracted a considerable interest in the medical imaging field. Currently, the main stream low-dose CT methods include vendor-specific sinogram domain filtration and iterative reconstruction algorithms, but they need to access raw data whose formats are not transparent to most users. Due to the difficulty of modeling the statistical characteristics in the image domain, the existing methods for directly processing reconstructed images cannot eliminate image noise very well while keeping structural details. Inspired by the idea of deep learning, here we combine the autoencoder, deconvolution network, and shortcut connections into the residual encoder-decoder convolutional neural network (RED-CNN) for low-dose CT imaging. After patch-based training, the proposed RED-CNN achieves a competitive performance relative to the-state-of-art methods. Especially, our method has been favorably evaluated in terms of noise suppression and structural preservation.

Impact of joint statistical dual-energy CT reconstruction of proton stopping power images: Comparison to image- and sinogram-domain material decomposition approaches.

PubMed

Zhang, Shuangyue; Han, Dong; Politte, David G; Williamson, Jeffrey F; O'Sullivan, Joseph A

2018-05-01

The purpose of this study was to assess the performance of a novel dual-energy CT (DECT) approach for proton stopping power ratio (SPR) mapping that integrates image reconstruction and material characterization using a joint statistical image reconstruction (JSIR) method based on a linear basis vector model (BVM). A systematic comparison between the JSIR-BVM method and previously described DECT image- and sinogram-domain decomposition approaches is also carried out on synthetic data. The JSIR-BVM method was implemented to estimate the electron densities and mean excitation energies (I-values) required by the Bethe equation for SPR mapping. In addition, image- and sinogram-domain DECT methods based on three available SPR models including BVM were implemented for comparison. The intrinsic SPR modeling accuracy of the three models was first validated. Synthetic DECT transmission sinograms of two 330 mm diameter phantoms each containing 17 soft and bony tissues (for a total of 34) of known composition were then generated with spectra of 90 and 140 kVp. The estimation accuracy of the reconstructed SPR images were evaluated for the seven investigated methods. The impact of phantom size and insert location on SPR estimation accuracy was also investigated. All three selected DECT-SPR models predict the SPR of all tissue types with less than 0.2% RMS errors under idealized conditions with no reconstruction uncertainties. When applied to synthetic sinograms, the JSIR-BVM method achieves the best performance with mean and RMS-average errors of less than 0.05% and 0.3%, respectively, for all noise levels, while the image- and sinogram-domain decomposition methods show increasing mean and RMS-average errors with increasing noise level. The JSIR-BVM method also reduces statistical SPR variation by sixfold compared to other methods. A 25% phantom diameter change causes up to 4% SPR differences for the image-domain decomposition approach, while the JSIR-BVM method and sinogram-domain decomposition methods are insensitive to size change. Among all the investigated methods, the JSIR-BVM method achieves the best performance for SPR estimation in our simulation phantom study. This novel method is robust with respect to sinogram noise and residual beam-hardening effects, yielding SPR estimation errors comparable to intrinsic BVM modeling error. In contrast, the achievable SPR estimation accuracy of the image- and sinogram-domain decomposition methods is dominated by the CT image intensity uncertainties introduced by the reconstruction and decomposition processes. © 2018 American Association of Physicists in Medicine.

Structure Constraints in a Constraint-Based Planner

NASA Technical Reports Server (NTRS)

Pang, Wan-Lin; Golden, Keith

2004-01-01

In this paper we report our work on a new constraint domain, where variables can take structured values. Earth-science data processing (ESDP) is a planning domain that requires the ability to represent and reason about complex constraints over structured data, such as satellite images. This paper reports on a constraint-based planner for ESDP and similar domains. We discuss our approach for translating a planning problem into a constraint satisfaction problem (CSP) and for representing and reasoning about structured objects and constraints over structures.

Non-invasive Florentine Renaissance Panel Painting Replica Structures Investigation by Using Terahertz Time-Domain Imaging (THz-TDI) Technique

NASA Astrophysics Data System (ADS)

Koch Dandolo, Corinna L.; Picollo, Marcello; Cucci, Costanza; Jepsen, Peter Uhd

2016-11-01

The potentials of the Terahertz Time-Domain Imaging (THz-TDI) technique for a non-invasive inspection of panel paintings have been considered in detail. The THz-TD data acquired on a replica of a panel painting made in imitation of Italian Renaissance panel paintings were processed in order to provide insights as to the limits and potentials of the technique in detecting different kinds of underdrawings and paint layers. Constituent layers, construction techniques, and anomalies were identified and localized by interpreting the extracted THz dielectric stratigraphy.

Development of a Time Domain Fluorimeter for Fluorescent Lifetime Multiplexing Analysis

PubMed Central

Weissleder, Ralph; Mahmood, Umar

2009-01-01

We show that a portable, inexpensive USB-powered time domain fluorimeter (TDF) and analysis scheme were developed for use in evaluating a new class of fluorescent lifetime multiplexed dyes. Fluorescent proteins, organic dyes, and quantum dots allow the labeling of more and more individual features within biological systems, but the wide absorption and emission spectra of these fluorophores limit the number of distinct processes which may be simultaneously imaged using spectral separation alone. By additionally separating reporters in a second dimension, fluorescent lifetime multiplexing provides a means to multiply the number of available imaging channels. PMID:19830273

Visualization of evolving laser-generated structures by frequency domain tomography

NASA Astrophysics Data System (ADS)

Chang, Yenyu; Li, Zhengyan; Wang, Xiaoming; Zgadzaj, Rafal; Downer, Michael

2011-10-01

We introduce frequency domain tomography (FDT) for single-shot visualization of time-evolving refractive index structures (e.g. laser wakefields, nonlinear index structures) moving at light-speed. Previous researchers demonstrated single-shot frequency domain holography (FDH), in which a probe-reference pulse pair co- propagates with the laser-generated structure, to obtain snapshot-like images. However, in FDH, information about the structure's evolution is averaged. To visualize an evolving structure, we use several frequency domain streak cameras (FDSCs), in each of which a probe-reference pulse pair propagates at an angle to the propagation direction of the laser-generated structure. The combination of several FDSCs constitutes the FDT system. We will present experimental results for a 4-probe FDT system that has imaged the whole-beam self-focusing of a pump pulse propagating through glass in a single laser shot. Combining temporal and angle multiplexing methods, we successfully processed data from four probe pulses in one spectrometer in a single-shot. The output of data processing is a multi-frame movie of the self- focusing pulse. Our results promise the possibility of visualizing evolving laser wakefield structures that underlie laser-plasma accelerators used for multi-GeV electron acceleration.

Laboratory analog and numerical study of groundwater flow and solute transport in a karst aquifer with conduit and matrix domains.

PubMed

Faulkner, Jonathan; Hu, Bill X; Kish, Stephen; Hua, Fei

2009-11-03

New mathematical and laboratory methods have been developed for simulating groundwater flow and solute transport in karst aquifers having conduits imbedded in a porous medium, such as limestone. The Stokes equations are used to model the flow in the conduits and the Darcy equation is used for the flow in the matrix. The Beavers-Joseph interface boundary conditions are adopted to describe the flow exchange at the interface boundary between the two domains. A laboratory analog is used to simulate the conduit and matrix domains of a karst aquifer. The conduit domain is located at the bottom of the transparent plexiglas laboratory analog and glass beads occupy the remaining space to represent the matrix domain. Water flows into and out of the two domains separately and each has its own supply and outflow reservoirs. Water and solute are exchanged through an interface between the two domains. Pressure transducers located within the matrix and conduit domains of the analog provide data that is processed and stored in digital format. Dye tracing experiments are recorded using time-lapse imaging. The data and images produced are analyzed by a spatial analysis program. The experiments provide not only hydraulic head distribution but also capture solute front images and mass exchange measurements between the conduit and matrix domains. In the experiment, we measure and record pressures, and quantify flow rates and solute transport. The results present a plausible argument that laboratory analogs can characterize groundwater water flow, solute transport, and mass exchange between the conduit and matrix domains in a karst aquifer. The analog validates the predictions of a numerical model and demonstrates the need of laboratory analogs to provide verification of proposed theories and the calibration of mathematical models.

Frequency division multiplexed multi-color fluorescence microscope system

NASA Astrophysics Data System (ADS)

Le, Vu Nam; Yang, Huai Dong; Zhang, Si Chun; Zhang, Xin Rong; Jin, Guo Fan

2017-10-01

Grayscale camera can only obtain gray scale image of object, while the multicolor imaging technology can obtain the color information to distinguish the sample structures which have the same shapes but in different colors. In fluorescence microscopy, the current method of multicolor imaging are flawed. Problem of these method is affecting the efficiency of fluorescence imaging, reducing the sampling rate of CCD etc. In this paper, we propose a novel multiple color fluorescence microscopy imaging method which based on the Frequency division multiplexing (FDM) technology, by modulating the excitation lights and demodulating the fluorescence signal in frequency domain. This method uses periodic functions with different frequency to modulate amplitude of each excitation lights, and then combine these beams for illumination in a fluorescence microscopy imaging system. The imaging system will detect a multicolor fluorescence image by a grayscale camera. During the data processing, the signal obtained by each pixel of the camera will be processed with discrete Fourier transform, decomposed by color in the frequency domain and then used inverse discrete Fourier transform. After using this process for signals from all of the pixels, monochrome images of each color on the image plane can be obtained and multicolor image is also acquired. Based on this method, this paper has constructed and set up a two-color fluorescence microscope system with two excitation wavelengths of 488 nm and 639 nm. By using this system to observe the linearly movement of two kinds of fluorescent microspheres, after the data processing, we obtain a two-color fluorescence dynamic video which is consistent with the original image. This experiment shows that the dynamic phenomenon of multicolor fluorescent biological samples can be generally observed by this method. Compared with the current methods, this method can obtain the image signals of each color at the same time, and the color video's frame rate is consistent with the frame rate of the camera. The optical system is simpler and does not need extra color separation element. In addition, this method has a good filtering effect on the ambient light or other light signals which are not affected by the modulation process.

New scheme for image edge detection using the switching mechanism of nonlinear optical material

NASA Astrophysics Data System (ADS)

Pahari, Nirmalya; Mukhopadhyay, Sourangshu

2006-03-01

The limitations of electronics in conducting parallel arithmetic, algebraic, and logic processing are well known. Very high-speed (terahertz) performance cannot be expected in conventional electronic mechanisms. To achieve such performance we can introduce optics instead of electronics for information processing, computing, and data handling. Nonlinear optical material (NOM) is a successful candidate in this regard to play a major role in the domain of optically controlled switching systems. The character of some NOMs is such as to reflect the probe beam in the presence of two read beams (or pump beams) exciting the material from opposite directions, using the principle of four-wave mixing. In image processing, edge extraction from an image is an important and essential task. Several optical methods of digital image processing are used for properly evaluating the image edges. We propose here a new method of image edge detection, extraction, and enhancement by use of AND-based switching operations with NOM. In this process we have used the optically inverted image of a supplied image. This can be obtained by the EXOR switching operation of the NOM.

Implementation issues of the nearfield equivalent source imaging microphone array

NASA Astrophysics Data System (ADS)

Bai, Mingsian R.; Lin, Jia-Hong; Tseng, Chih-Wen

2011-01-01

This paper revisits a nearfield microphone array technique termed nearfield equivalent source imaging (NESI) proposed previously. In particular, various issues concerning the implementation of the NESI algorithm are examined. The NESI can be implemented in both the time domain and the frequency domain. Acoustical variables including sound pressure, particle velocity, active intensity and sound power are calculated by using multichannel inverse filters. Issues concerning sensor deployment are also investigated for the nearfield array. The uniform array outperformed a random array previously optimized for far-field imaging, which contradicts the conventional wisdom in far-field arrays. For applications in which only a patch array with scarce sensors is available, a virtual microphone approach is employed to ameliorate edge effects using extrapolation and to improve imaging resolution using interpolation. To enhance the processing efficiency of the time-domain NESI, an eigensystem realization algorithm (ERA) is developed. Several filtering methods are compared in terms of computational complexity. Significant saving on computations can be achieved using ERA and the frequency-domain NESI, as compared to the traditional method. The NESI technique was also experimentally validated using practical sources including a 125 cc scooter and a wooden box model with a loudspeaker fitted inside. The NESI technique proved effective in identifying broadband and non-stationary sources produced by the sources.

AstroImageJ: Image Processing and Photometric Extraction for Ultra-precise Astronomical Light Curves

NASA Astrophysics Data System (ADS)

Collins, Karen A.; Kielkopf, John F.; Stassun, Keivan G.; Hessman, Frederic V.

2017-02-01

ImageJ is a graphical user interface (GUI) driven, public domain, Java-based, software package for general image processing traditionally used mainly in life sciences fields. The image processing capabilities of ImageJ are useful and extendable to other scientific fields. Here we present AstroImageJ (AIJ), which provides an astronomy specific image display environment and tools for astronomy specific image calibration and data reduction. Although AIJ maintains the general purpose image processing capabilities of ImageJ, AIJ is streamlined for time-series differential photometry, light curve detrending and fitting, and light curve plotting, especially for applications requiring ultra-precise light curves (e.g., exoplanet transits). AIJ reads and writes standard Flexible Image Transport System (FITS) files, as well as other common image formats, provides FITS header viewing and editing, and is World Coordinate System aware, including an automated interface to the astrometry.net web portal for plate solving images. AIJ provides research grade image calibration and analysis tools with a GUI driven approach, and easily installed cross-platform compatibility. It enables new users, even at the level of undergraduate student, high school student, or amateur astronomer, to quickly start processing, modeling, and plotting astronomical image data with one tightly integrated software package.

The Zombie Plot: A Simple Graphic Method for Visualizing the Efficacy of a Diagnostic Test.

PubMed

Richardson, Michael L

2016-08-09

One of the most important jobs of a radiologist is to pick the most appropriate imaging test for a particular clinical situation. Making a proper selection sometimes requires statistical analysis. The objective of this article is to introduce a simple graphic technique, an ROC plot that has been divided into zones of mostly bad imaging efficacy (ZOMBIE, hereafter referred to as the "zombie plot"), that transforms information about imaging efficacy from the numeric domain into the visual domain. The numeric rationale for the use of zombie plots is given, as are several examples of the clinical use of these plots. Two online calculators are described that simplify the process of producing a zombie plot.

Quantitative Frequency-Domain Passive Cavitation Imaging

PubMed Central

Haworth, Kevin J.; Bader, Kenneth B.; Rich, Kyle T.; Holland, Christy K.; Mast, T. Douglas

2017-01-01

Passive cavitation detection has been an instrumental technique for measuring cavitation dynamics, elucidating concomitant bioeffects, and guiding ultrasound therapies. Recently, techniques have been developed to create images of cavitation activity to provide investigators with a more complete set of information. These techniques use arrays to record and subsequently beamform received cavitation emissions, rather than processing emissions received on a single-element transducer. In this paper, the methods for performing frequency-domain delay, sum, and integrate passive imaging are outlined. The method can be applied to any passively acquired acoustic scattering or emissions, including cavitation emissions. In order to compare data across different systems, techniques for normalizing Fourier transformed data and converting the data to the acoustic energy received by the array are described. A discussion of hardware requirements and alternative imaging approaches are additionally outlined. Examples are provided in MATLAB. PMID:27992331

Hardware architecture design of image restoration based on time-frequency domain computation

NASA Astrophysics Data System (ADS)

Wen, Bo; Zhang, Jing; Jiao, Zipeng

2013-10-01

The image restoration algorithms based on time-frequency domain computation is high maturity and applied widely in engineering. To solve the high-speed implementation of these algorithms, the TFDC hardware architecture is proposed. Firstly, the main module is designed, by analyzing the common processing and numerical calculation. Then, to improve the commonality, the iteration control module is planed for iterative algorithms. In addition, to reduce the computational cost and memory requirements, the necessary optimizations are suggested for the time-consuming module, which include two-dimensional FFT/IFFT and the plural calculation. Eventually, the TFDC hardware architecture is adopted for hardware design of real-time image restoration system. The result proves that, the TFDC hardware architecture and its optimizations can be applied to image restoration algorithms based on TFDC, with good algorithm commonality, hardware realizability and high efficiency.

Investigation into process-induced de-aggregation of cohesive micronised API particles.

PubMed

Hoffmann, Magnus; Wray, Patrick S; Gamble, John F; Tobyn, Mike

2015-09-30

The aim of this study was to assess the impact of unit processes on the de-aggregation of a cohesive micronised API within a pharmaceutical formulation using near-infrared chemical imaging. The impact on the primary API particles was also investigated using an image-based particle characterization system with integrated Raman analysis. The blended material was shown to contain large, API rich domains which were distributed in-homogeneously across the sample, suggesting that the blending process was not aggressive enough to disperse aggregates of micronised drug particles. Cone milling, routinely used to improve the homogeneity of such cohesive formulations, was observed to substantially reduce the number and size of API rich domains; however, several smaller API domains survived the milling process. Conveyance of the cone milled formulation through the Alexanderwerk WP120 powder feed system completely dispersed all remaining aggregates. Importantly, powder feed transmission of the un-milled formulation was observed to produce an equally homogeneous API distribution. The size of the micronised primary drug particles remained unchanged during powder feed transmission. These findings provide further evidence that this powder feed system does induce shear, and is in fact better able to disperse aggregates of a cohesive micronised API within a blend than the blend-mill-blend step. Crown Copyright © 2015. Published by Elsevier B.V. All rights reserved.

Brain connectivity study of joint attention using frequency-domain optical imaging technique

NASA Astrophysics Data System (ADS)

Chaudhary, Ujwal; Zhu, Banghe; Godavarty, Anuradha

2010-02-01

Autism is a socio-communication brain development disorder. It is marked by degeneration in the ability to respond to joint attention skill task, from as early as 12 to 18 months of age. This trait is used to distinguish autistic from nonautistic populations. In this study, diffuse optical imaging is being used to study brain connectivity for the first time in response to joint attention experience in normal adults. The prefrontal region of the brain was non-invasively imaged using a frequency-domain based optical imager. The imaging studies were performed on 11 normal right-handed adults and optical measurements were acquired in response to joint-attention based video clips. While the intensity-based optical data provides information about the hemodynamic response of the underlying neural process, the time-dependent phase-based optical data has the potential to explicate the directional information on the activation of the brain. Thus brain connectivity studies are performed by computing covariance/correlations between spatial units using this frequency-domain based optical measurements. The preliminary results indicate that the extent of synchrony and directional variation in the pattern of activation varies in the left and right frontal cortex. The results have significant implication for research in neural pathways associated with autism that can be mapped using diffuse optical imaging tools in the future.

An efficient depth map preprocessing method based on structure-aided domain transform smoothing for 3D view generation

PubMed Central

Ma, Liyan; Qiu, Bo; Cui, Mingyue; Ding, Jianwei

2017-01-01

Depth image-based rendering (DIBR), which is used to render virtual views with a color image and the corresponding depth map, is one of the key techniques in the 2D to 3D conversion process. Due to the absence of knowledge about the 3D structure of a scene and its corresponding texture, DIBR in the 2D to 3D conversion process, inevitably leads to holes in the resulting 3D image as a result of newly-exposed areas. In this paper, we proposed a structure-aided depth map preprocessing framework in the transformed domain, which is inspired by recently proposed domain transform for its low complexity and high efficiency. Firstly, our framework integrates hybrid constraints including scene structure, edge consistency and visual saliency information in the transformed domain to improve the performance of depth map preprocess in an implicit way. Then, adaptive smooth localization is cooperated and realized in the proposed framework to further reduce over-smoothness and enhance optimization in the non-hole regions. Different from the other similar methods, the proposed method can simultaneously achieve the effects of hole filling, edge correction and local smoothing for typical depth maps in a united framework. Thanks to these advantages, it can yield visually satisfactory results with less computational complexity for high quality 2D to 3D conversion. Numerical experimental results demonstrate the excellent performances of the proposed method. PMID:28407027

3D frequency-domain ultrasound waveform tomography breast imaging

NASA Astrophysics Data System (ADS)

Sandhu, Gursharan Yash; West, Erik; Li, Cuiping; Roy, Olivier; Duric, Neb

2017-03-01

Frequency-domain ultrasound waveform tomography is a promising method for the visualization and characterization of breast disease. It has previously been shown to accurately reconstruct the sound speed distributions of breasts of varying densities. The reconstructed images show detailed morphological and quantitative information that can help differentiate different types of breast disease including benign and malignant lesions. The attenuation properties of an ex vivo phantom have also been assessed. However, the reconstruction algorithms assumed a 2D geometry while the actual data acquisition process was not. Although clinically useful sound speed images can be reconstructed assuming this mismatched geometry, artifacts from the reconstruction process exist within the reconstructed images. This is especially true for registration across different modalities and when the 2D assumption is violated. For example, this happens when a patient's breast is rapidly sloping. It is also true for attenuation imaging where energy lost or gained out of the plane gets transformed into artifacts within the image space. In this paper, we will briefly review ultrasound waveform tomography techniques, give motivation for pursuing the 3D method, discuss the 3D reconstruction algorithm, present the results of 3D forward modeling, show the mismatch that is induced by the violation of 3D modeling via numerical simulations, and present a 3D inversion of a numerical phantom.

In-vivo, real-time cross-sectional images of retina using a GPU enhanced master slave optical coherence tomography system

NASA Astrophysics Data System (ADS)

Bradu, Adrian; Kapinchev, Konstantin; Barnes, Frederick; Podoleanu, Adrian

2016-03-01

In our previous reports we demonstrated a novel Fourier domain optical coherence tomography method, Master Slave optical coherence tomography (MS-OCT), that does not require resampling of data and can deliver en-face images from several depths simultaneously. While ideally suited for delivering information from a selected depth, the MS-OCT has been so far inferior to the conventional FFT based OCT in terms of time of producing cross section images. Here, we demonstrate that by taking advantage of the parallel processing capabilities offered by the MS-OCT method, cross-sectional OCT images of the human retina can be produced in real-time by assembling several T-scans from different depths. We analyze the conditions that ensure a real-time B-scan imaging operation, and demonstrate in-vivo real-time images from human fovea and the optic nerve, of comparable resolution and sensitivity to those produced using the traditional Fourier domain based method.

A novel encryption scheme for high-contrast image data in the Fresnelet domain

PubMed Central

Bibi, Nargis; Farwa, Shabieh; Jahngir, Adnan; Usman, Muhammad

2018-01-01

In this paper, a unique and more distinctive encryption algorithm is proposed. This is based on the complexity of highly nonlinear S box in Flesnelet domain. The nonlinear pattern is transformed further to enhance the confusion in the dummy data using Fresnelet technique. The security level of the encrypted image boosts using the algebra of Galois field in Fresnelet domain. At first level, the Fresnelet transform is used to propagate the given information with desired wavelength at specified distance. It decomposes given secret data into four complex subbands. These complex sub-bands are separated into two components of real subband data and imaginary subband data. At second level, the net subband data, produced at the first level, is deteriorated to non-linear diffused pattern using the unique S-box defined on the Galois field F28. In the diffusion process, the permuted image is substituted via dynamic algebraic S-box substitution. We prove through various analysis techniques that the proposed scheme enhances the cipher security level, extensively. PMID:29608609

Frequency-Domain Streak Camera and Tomography for Ultrafast Imaging of Evolving and Channeled Plasma Accelerator Structures

NASA Astrophysics Data System (ADS)

Li, Zhengyan; Zgadzaj, Rafal; Wang, Xiaoming; Reed, Stephen; Dong, Peng; Downer, Michael C.

2010-11-01

We demonstrate a prototype Frequency Domain Streak Camera (FDSC) that can capture the picosecond time evolution of the plasma accelerator structure in a single shot. In our prototype Frequency-Domain Streak Camera, a probe pulse propagates obliquely to a sub-picosecond pump pulse that creates an evolving nonlinear index "bubble" in fused silica glass, supplementing a conventional Frequency Domain Holographic (FDH) probe-reference pair that co-propagates with the "bubble". Frequency Domain Tomography (FDT) generalizes Frequency-Domain Streak Camera by probing the "bubble" from multiple angles and reconstructing its morphology and evolution using algorithms similar to those used in medical CAT scans. Multiplexing methods (Temporal Multiplexing and Angular Multiplexing) improve data storage and processing capability, demonstrating a compact Frequency Domain Tomography system with a single spectrometer.

Advanced magneto-optical microscopy: Imaging from picoseconds to centimeters - imaging spin waves and temperature distributions (invited)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Urs, Necdet Onur; Mozooni, Babak; Kustov, Mikhail

2016-05-15

Recent developments in the observation of magnetic domains and domain walls by wide-field optical microscopy based on the magneto-optical Kerr, Faraday, Voigt, and Gradient effect are reviewed. Emphasis is given to the existence of higher order magneto-optical effects for advanced magnetic imaging. Fundamental concepts and advances in methodology are discussed that allow for imaging of magnetic domains on various length and time scales. Time-resolved imaging of electric field induced domain wall rotation is shown. Visualization of magnetization dynamics down to picosecond temporal resolution for the imaging of spin-waves and magneto-optical multi-effect domain imaging techniques for obtaining vectorial information are demonstrated.more » Beyond conventional domain imaging, the use of a magneto-optical indicator technique for local temperature sensing is shown.« less

Angle-domain inverse scattering migration/inversion in isotropic media

NASA Astrophysics Data System (ADS)

Li, Wuqun; Mao, Weijian; Li, Xuelei; Ouyang, Wei; Liang, Quan

2018-07-01

The classical seismic asymptotic inversion can be transformed into a problem of inversion of generalized Radon transform (GRT). In such methods, the combined parameters are linearly attached to the scattered wave-field by Born approximation and recovered by applying an inverse GRT operator to the scattered wave-field data. Typical GRT-style true-amplitude inversion procedure contains an amplitude compensation process after the weighted migration via dividing an illumination associated matrix whose elements are integrals of scattering angles. It is intuitional to some extent that performs the generalized linear inversion and the inversion of GRT together by this process for direct inversion. However, it is imprecise to carry out such operation when the illumination at the image point is limited, which easily leads to the inaccuracy and instability of the matrix. This paper formulates the GRT true-amplitude inversion framework in an angle-domain version, which naturally degrades the external integral term related to the illumination in the conventional case. We solve the linearized integral equation for combined parameters of different fixed scattering angle values. With this step, we obtain high-quality angle-domain common-image gathers (CIGs) in the migration loop which provide correct amplitude-versus-angle (AVA) behavior and reasonable illumination range for subsurface image points. Then we deal with the over-determined problem to solve each parameter in the combination by a standard optimization operation. The angle-domain GRT inversion method keeps away from calculating the inaccurate and unstable illumination matrix. Compared with the conventional method, the angle-domain method can obtain more accurate amplitude information and wider amplitude-preserved range. Several model tests demonstrate the effectiveness and practicability.

Secretion of CyaA-PrtB and HlyA-PrtB fusion proteins in Escherichia coli: involvement of the glycine-rich repeat domain of Erwinia chrysanthemi protease B.

PubMed Central

Létoffé, S; Wandersman, C

1992-01-01

Protease B from Erwinia chrysanthemi was shown previously to have a C-terminal secretion signal located downstream of a domain that contains six glycine-rich repeats. This domain is conserved in all known bacterial proteins secreted by the signal peptide-independent pathway. The role of these repeats in the secretion process is controversial. We compared the secretion processes of various heterologous polypeptides fused either directly to the signal or separated from it by the glycine-rich domain. Although the repeats are not involved in the secretion of small truncated protease B carboxy-terminal peptides, they are required for the secretion of higher-molecular-weight fusion proteins. Secretion efficiency was also dependent on the size of the passenger polypeptide. Images PMID:1629152

Spatial-frequency composite watermarking for digital image copyright protection

NASA Astrophysics Data System (ADS)

Su, Po-Chyi; Kuo, C.-C. Jay

2000-05-01

Digital watermarks can be classified into two categories according to the embedding and retrieval domain, i.e. spatial- and frequency-domain watermarks. Because the two watermarks have different characteristics and limitations, combination of them can have various interesting properties when applied to different applications. In this research, we examine two spatial-frequency composite watermarking schemes. In both cases, a frequency-domain watermarking technique is applied as a baseline structure in the system. The embedded frequency- domain watermark is robust against filtering and compression. A spatial-domain watermarking scheme is then built to compensate some deficiency of the frequency-domain scheme. The first composite scheme is to embed a robust watermark in images to convey copyright or author information. The frequency-domain watermark contains owner's identification number while the spatial-domain watermark is embedded for image registration to resist cropping attack. The second composite scheme is to embed fragile watermark for image authentication. The spatial-domain watermark helps in locating the tampered part of the image while the frequency-domain watermark indicates the source of the image and prevents double watermarking attack. Experimental results show that the two watermarks do not interfere with each other and different functionalities can be achieved. Watermarks in both domains are detected without resorting to the original image. Furthermore, the resulting watermarked image can still preserve high fidelity without serious visual degradation.

Growing Mathematical Understanding through Collective Image Making, Collective Image Having, and Collective Property Noticing

ERIC Educational Resources Information Center

Martin, Lyndon C.; Towers, Jo

2015-01-01

In the research reported in this paper, we develop a theoretical perspective to describe and account for the growth of collective mathematical understanding. We discuss collective processes in mathematics, drawing in particular on theoretical work in the domains of improvisational jazz and theatre. Using examples of data from a study of elementary…

DHMI: dynamic holographic microscopy interface

NASA Astrophysics Data System (ADS)

He, Xuefei; Zheng, Yujie; Lee, Woei Ming

2016-12-01

Digital holographic microscopy (DHM) is a powerful in-vitro biological imaging tool. In this paper, we report a fully automated off-axis digital holographic microscopy system completed with a graphical user interface in the Matlab environment. The interface primarily includes Fourier domain processing, phase reconstruction, aberration compensation and autofocusing. A variety of imaging operations such as region of interest selection, de-noising mode (filtering and averaging), low frame rate imaging for immediate reconstruction and high frame rate imaging routine ( 27 fps) are implemented to facilitate ease of use.

Long-term behavior understanding based on the expert-based combination of short-term observations in high-resolution CCTV

NASA Astrophysics Data System (ADS)

Schutte, Klamer; Burghouts, Gertjan; van der Stap, Nanda; Westerwoudt, Victor; Bouma, Henri; Kruithof, Maarten; Baan, Jan; ten Hove, Johan-Martijn

2016-10-01

The bottleneck in situation awareness is no longer in the sensing domain but rather in the data interpretation domain, since the number of sensors is rapidly increasing and it is not affordable to increase human data-analysis capacity at the same rate. Automatic image analysis can assist a human analyst by alerting when an event of interest occurs. However, common state-of-the-art image recognition systems learn representations in high-dimensional feature spaces, which makes them less suitable to generate a user-comprehensive message. Such data-driven approaches rely on large amounts of training data, which is often not available for quite rare but high-impact incidents in the security domain. The key contribution of this paper is that we present a novel real-time system for image understanding based on generic instantaneous low-level processing components (symbols) and flexible user-definable and user-understandable combinations of these components (sentences) at a higher level for the recognition of specific relevant events in the security domain. We show that the detection of an event of interest can be enhanced by utilizing recognition of multiple short-term preparatory actions.

Optical coherence tomography imaging based on non-harmonic analysis

NASA Astrophysics Data System (ADS)

Cao, Xu; Hirobayashi, Shigeki; Chong, Changho; Morosawa, Atsushi; Totsuka, Koki; Suzuki, Takuya

2009-11-01

A new processing technique called Non-Harmonic Analysis (NHA) is proposed for OCT imaging. Conventional Fourier-Domain OCT relies on the FFT calculation which depends on the window function and length. Axial resolution is counter proportional to the frame length of FFT that is limited by the swept range of the swept source in SS-OCT, or the pixel counts of CCD in SD-OCT degraded in FD-OCT. However, NHA process is intrinsically free from this trade-offs; NHA can resolve high frequency without being influenced by window function or frame length of sampled data. In this study, NHA process is explained and applied to OCT imaging and compared with OCT images based on FFT. In order to validate the benefit of NHA in OCT, we carried out OCT imaging based on NHA with the three different sample of onion-skin,human-skin and pig-eye. The results show that NHA process can realize practical image resolution that is equivalent to 100nm swept range only with less than half-reduced wavelength range.

Multi-template image matching using alpha-rooted biquaternion phase correlation with application to logo recognition

NASA Astrophysics Data System (ADS)

DelMarco, Stephen

2011-06-01

Hypercomplex approaches are seeing increased application to signal and image processing problems. The use of multicomponent hypercomplex numbers, such as quaternions, enables the simultaneous co-processing of multiple signal or image components. This joint processing capability can provide improved exploitation of the information contained in the data, thereby leading to improved performance in detection and recognition problems. In this paper, we apply hypercomplex processing techniques to the logo image recognition problem. Specifically, we develop an image matcher by generalizing classical phase correlation to the biquaternion case. We further incorporate biquaternion Fourier domain alpha-rooting enhancement to create Alpha-Rooted Biquaternion Phase Correlation (ARBPC). We present the mathematical properties which justify use of ARBPC as an image matcher. We present numerical performance results of a logo verification problem using real-world logo data, demonstrating the performance improvement obtained using the hypercomplex approach. We compare results of the hypercomplex approach to standard multi-template matching approaches.

Stochastic Seismic Inversion and Migration for Offshore Site Investigation in the Northern Gulf of Mexico

NASA Astrophysics Data System (ADS)

Son, J.; Medina-Cetina, Z.

2017-12-01

We discuss the comparison between deterministic and stochastic optimization approaches to the nonlinear geophysical full-waveform inverse problem, based on the seismic survey data from Mississippi Canyon in the Northern Gulf of Mexico. Since the subsea engineering and offshore construction projects actively require reliable ground models from various site investigations, the primary goal of this study is to reconstruct the accurate subsurface information of the soil and rock material profiles under the seafloor. The shallow sediment layers have naturally formed heterogeneous formations which may cause unwanted marine landslides or foundation failures of underwater infrastructure. We chose the quasi-Newton and simulated annealing as deterministic and stochastic optimization algorithms respectively. Seismic forward modeling based on finite difference method with absorbing boundary condition implements the iterative simulations in the inverse modeling. We briefly report on numerical experiments using a synthetic data as an offshore ground model which contains shallow artificial target profiles of geomaterials under the seafloor. We apply the seismic migration processing and generate Voronoi tessellation on two-dimensional space-domain to improve the computational efficiency of the imaging stratigraphical velocity model reconstruction. We then report on the detail of a field data implementation, which shows the complex geologic structures in the Northern Gulf of Mexico. Lastly, we compare the new inverted image of subsurface site profiles in the space-domain with the previously processed seismic image in the time-domain at the same location. Overall, stochastic optimization for seismic inversion with migration and Voronoi tessellation show significant promise to improve the subsurface imaging of ground models and improve the computational efficiency required for the full waveform inversion. We anticipate that by improving the inversion process of shallow layers from geophysical data will better support the offshore site investigation.

Human Expertise Helps Computer Classify Images

NASA Technical Reports Server (NTRS)

Rorvig, Mark E.

1991-01-01

Two-domain method of computational classification of images requires less computation than other methods for computational recognition, matching, or classification of images or patterns. Does not require explicit computational matching of features, and incorporates human expertise without requiring translation of mental processes of classification into language comprehensible to computer. Conceived to "train" computer to analyze photomicrographs of microscope-slide specimens of leucocytes from human peripheral blood to distinguish between specimens from healthy and specimens from traumatized patients.

Testbed Experiment for SPIDER: A Photonic Integrated Circuit-based Interferometric imaging system

NASA Astrophysics Data System (ADS)

Badham, K.; Duncan, A.; Kendrick, R. L.; Wuchenich, D.; Ogden, C.; Chriqui, G.; Thurman, S. T.; Su, T.; Lai, W.; Chun, J.; Li, S.; Liu, G.; Yoo, S. J. B.

The Lockheed Martin Advanced Technology Center (LM ATC) and the University of California at Davis (UC Davis) are developing an electro-optical (EO) imaging sensor called SPIDER (Segmented Planar Imaging Detector for Electro-optical Reconnaissance) that seeks to provide a 10x to 100x size, weight, and power (SWaP) reduction alternative to the traditional bulky optical telescope and focal-plane detector array. The substantial reductions in SWaP would reduce cost and/or provide higher resolution by enabling a larger-aperture imager in a constrained volume. Our SPIDER imager replaces the traditional optical telescope and digital focal plane detector array with a densely packed interferometer array based on emerging photonic integrated circuit (PIC) technologies that samples the object being imaged in the Fourier domain (i.e., spatial frequency domain), and then reconstructs an image. Our approach replaces the large optics and structures required by a conventional telescope with PICs that are accommodated by standard lithographic fabrication techniques (e.g., complementary metal-oxide-semiconductor (CMOS) fabrication). The standard EO payload integration and test process that involves precision alignment and test of optical components to form a diffraction limited telescope is, therefore, replaced by in-process integration and test as part of the PIC fabrication, which substantially reduces associated schedule and cost. In this paper we describe the photonic integrated circuit design and the testbed used to create the first images of extended scenes. We summarize the image reconstruction steps and present the final images. We also describe our next generation PIC design for a larger (16x area, 4x field of view) image.

Image tools for UNIX

NASA Technical Reports Server (NTRS)

Banks, David C.

1994-01-01

This talk features two simple and useful tools for digital image processing in the UNIX environment. They are xv and pbmplus. The xv image viewer which runs under the X window system reads images in a number of different file formats and writes them out in different formats. The view area supports a pop-up control panel. The 'algorithms' menu lets you blur an image. The xv control panel also activates the color editor which displays the image's color map (if one exists). The xv image viewer is available through the internet. The pbmplus package is a set of tools designed to perform image processing from within a UNIX shell. The acronym 'pbm' stands for portable bit map. Like xv, the pbm plus tool can convert images from and to many different file formats. The source code and manual pages for pbmplus are also available through the internet. This software is in the public domain.

Resin embedded multicycle imaging (REMI): a tool to evaluate protein domains.

PubMed

Busse, B L; Bezrukov, L; Blank, P S; Zimmerberg, J

2016-08-08

Protein complexes associated with cellular processes comprise a significant fraction of all biology, but our understanding of their heterogeneous organization remains inadequate, particularly for physiological densities of multiple protein species. Towards resolving this limitation, we here present a new technique based on resin-embedded multicycle imaging (REMI) of proteins in-situ. By stabilizing protein structure and antigenicity in acrylic resins, affinity labels were repeatedly applied, imaged, removed, and replaced. In principle, an arbitrarily large number of proteins of interest may be imaged on the same specimen with subsequent digital overlay. A series of novel preparative methods were developed to address the problem of imaging multiple protein species in areas of the plasma membrane or volumes of cytoplasm of individual cells. For multiplexed examination of antibody staining we used straightforward computational techniques to align sequential images, and super-resolution microscopy was used to further define membrane protein colocalization. We give one example of a fibroblast membrane with eight multiplexed proteins. A simple statistical analysis of this limited membrane proteomic dataset is sufficient to demonstrate the analytical power contributed by additional imaged proteins when studying membrane protein domains.

SCIFIO: an extensible framework to support scientific image formats.

PubMed

Hiner, Mark C; Rueden, Curtis T; Eliceiri, Kevin W

2016-12-07

No gold standard exists in the world of scientific image acquisition; a proliferation of instruments each with its own proprietary data format has made out-of-the-box sharing of that data nearly impossible. In the field of light microscopy, the Bio-Formats library was designed to translate such proprietary data formats to a common, open-source schema, enabling sharing and reproduction of scientific results. While Bio-Formats has proved successful for microscopy images, the greater scientific community was lacking a domain-independent framework for format translation. SCIFIO (SCientific Image Format Input and Output) is presented as a freely available, open-source library unifying the mechanisms of reading and writing image data. The core of SCIFIO is its modular definition of formats, the design of which clearly outlines the components of image I/O to encourage extensibility, facilitated by the dynamic discovery of the SciJava plugin framework. SCIFIO is structured to support coexistence of multiple domain-specific open exchange formats, such as Bio-Formats' OME-TIFF, within a unified environment. SCIFIO is a freely available software library developed to standardize the process of reading and writing scientific image formats.

Sonar Imaging of Elastic Fluid-Filled Cylindrical Shells.

NASA Astrophysics Data System (ADS)

Dodd, Stirling Scott

1995-01-01

Previously a method of describing spherical acoustic waves in cylindrical coordinates was applied to the problem of point source scattering by an elastic infinite fluid -filled cylindrical shell (S. Dodd and C. Loeffler, J. Acoust. Soc. Am. 97, 3284(A) (1995)). This method is applied to numerically model monostatic oblique incidence scattering from a truncated cylinder by a narrow-beam high-frequency imaging sonar. The narrow beam solution results from integrating the point source solution over the spatial extent of a line source and line receiver. The cylinder truncation is treated by the method of images, and assumes that the reflection coefficient at the truncation is unity. The scattering form functions, calculated using this method, are applied as filters to a narrow bandwidth, high ka pulse to find the time domain scattering response. The time domain pulses are further processed and displayed in the form of a sonar image. These images compare favorably to experimentally obtained images (G. Kaduchak and C. Loeffler, J. Acoust. Soc. Am. 97, 3289(A) (1995)). The impact of the s_{ rm o} and a_{rm o} Lamb waves is vividly apparent in the images.

Resin embedded multicycle imaging (REMI): a tool to evaluate protein domains

PubMed Central

Busse, B. L.; Bezrukov, L.; Blank, P. S.; Zimmerberg, J.

2016-01-01

Protein complexes associated with cellular processes comprise a significant fraction of all biology, but our understanding of their heterogeneous organization remains inadequate, particularly for physiological densities of multiple protein species. Towards resolving this limitation, we here present a new technique based on resin-embedded multicycle imaging (REMI) of proteins in-situ. By stabilizing protein structure and antigenicity in acrylic resins, affinity labels were repeatedly applied, imaged, removed, and replaced. In principle, an arbitrarily large number of proteins of interest may be imaged on the same specimen with subsequent digital overlay. A series of novel preparative methods were developed to address the problem of imaging multiple protein species in areas of the plasma membrane or volumes of cytoplasm of individual cells. For multiplexed examination of antibody staining we used straightforward computational techniques to align sequential images, and super-resolution microscopy was used to further define membrane protein colocalization. We give one example of a fibroblast membrane with eight multiplexed proteins. A simple statistical analysis of this limited membrane proteomic dataset is sufficient to demonstrate the analytical power contributed by additional imaged proteins when studying membrane protein domains. PMID:27499335

Ferroelectric Domain Structure and Local Piezoelectric Properties of Lead-Free (Ka0.5Na0.5)NbO3 and BiFeO3-Based Piezoelectric Ceramics

PubMed Central

Alikin, Denis; Turygin, Anton; Kholkin, Andrei; Shur, Vladimir

2017-01-01

Recent advances in the development of novel methods for the local characterization of ferroelectric domains open up new opportunities not only to image, but also to control and to create desired domain configurations (domain engineering). The morphotropic and polymorphic phase boundaries that are frequently used to increase the electromechanical and dielectric performance of ferroelectric ceramics have a tremendous effect on the domain structure, which can serve as a signature of complex polarization states and link local and macroscopic piezoelectric and dielectric responses. This is especially important for the study of lead-free ferroelectric ceramics, which is currently replacing traditional lead-containing materials, and great efforts are devoted to increasing their performance to match that of lead zirconate titanate (PZT). In this work, we provide a short overview of the recent progress in the imaging of domain structure in two major families of ceramic lead-free systems based on BiFeO3 (BFO) and (Ka0.5Na0.5)NbO3 (KNN). This can be used as a guideline for the understanding of domain processes in lead-free piezoelectric ceramics and provide further insight into the mechanisms of structure–property relationship in these technologically important material families. PMID:28772408

Using Neural Pattern Classifiers to Quantify the Modularity of Conflict–Control Mechanisms in the Human Brain

PubMed Central

Jiang, Jiefeng; Egner, Tobias

2014-01-01

Resolving conflicting sensory and motor representations is a core function of cognitive control, but it remains uncertain to what degree control over different sources of conflict is implemented by shared (domain general) or distinct (domain specific) neural resources. Behavioral data suggest conflict–control to be domain specific, but results from neuroimaging studies have been ambivalent. Here, we employed multivoxel pattern analyses that can decode a brain region's informational content, allowing us to distinguish incidental activation overlap from actual shared information processing. We trained independent sets of “searchlight” classifiers on functional magnetic resonance imaging data to decode control processes associated with stimulus-conflict (Stroop task) and ideomotor-conflict (Simon task). Quantifying the proportion of domain-specific searchlights (capable of decoding only one type of conflict) and domain-general searchlights (capable of decoding both conflict types) in each subject, we found both domain-specific and domain-general searchlights, though the former were more common. When mapping anatomical loci of these searchlights across subjects, neural substrates of stimulus- and ideomotor-specific conflict–control were found to be anatomically consistent across subjects, whereas the substrates of domain-general conflict–control were not. Overall, these findings suggest a hybrid neural architecture of conflict–control that entails both modular (domain specific) and global (domain general) components. PMID:23402762

Frequency-Domain Streak Camera and Tomography for Ultrafast Imaging of Evolving and Channeled Plasma Accelerator Structures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li Zhengyan; Zgadzaj, Rafal; Wang Xiaoming

2010-11-04

We demonstrate a prototype Frequency Domain Streak Camera (FDSC) that can capture the picosecond time evolution of the plasma accelerator structure in a single shot. In our prototype Frequency-Domain Streak Camera, a probe pulse propagates obliquely to a sub-picosecond pump pulse that creates an evolving nonlinear index 'bubble' in fused silica glass, supplementing a conventional Frequency Domain Holographic (FDH) probe-reference pair that co-propagates with the 'bubble'. Frequency Domain Tomography (FDT) generalizes Frequency-Domain Streak Camera by probing the 'bubble' from multiple angles and reconstructing its morphology and evolution using algorithms similar to those used in medical CAT scans. Multiplexing methods (Temporalmore » Multiplexing and Angular Multiplexing) improve data storage and processing capability, demonstrating a compact Frequency Domain Tomography system with a single spectrometer.« less

The representation of conceptual knowledge: visual, auditory, and olfactory imagery compared with semantic processing.

PubMed

Palmiero, Massimiliano; Di Matteo, Rosalia; Belardinelli, Marta Olivetti

2014-05-01

Two experiments comparing imaginative processing in different modalities and semantic processing were carried out to investigate the issue of whether conceptual knowledge can be represented in different format. Participants were asked to judge the similarity between visual images, auditory images, and olfactory images in the imaginative block, if two items belonged to the same category in the semantic block. Items were verbally cued in both experiments. The degree of similarity between the imaginative and semantic items was changed across experiments. Experiment 1 showed that the semantic processing was faster than the visual and the auditory imaginative processing, whereas no differentiation was possible between the semantic processing and the olfactory imaginative processing. Experiment 2 revealed that only the visual imaginative processing could be differentiated from the semantic processing in terms of accuracy. These results showed that the visual and auditory imaginative processing can be differentiated from the semantic processing, although both visual and auditory images strongly rely on semantic representations. On the contrary, no differentiation is possible within the olfactory domain. Results are discussed in the frame of the imagery debate.

Video multiple watermarking technique based on image interlacing using DWT.

PubMed

Ibrahim, Mohamed M; Abdel Kader, Neamat S; Zorkany, M

2014-01-01

Digital watermarking is one of the important techniques to secure digital media files in the domains of data authentication and copyright protection. In the nonblind watermarking systems, the need of the original host file in the watermark recovery operation makes an overhead over the system resources, doubles memory capacity, and doubles communications bandwidth. In this paper, a robust video multiple watermarking technique is proposed to solve this problem. This technique is based on image interlacing. In this technique, three-level discrete wavelet transform (DWT) is used as a watermark embedding/extracting domain, Arnold transform is used as a watermark encryption/decryption method, and different types of media (gray image, color image, and video) are used as watermarks. The robustness of this technique is tested by applying different types of attacks such as: geometric, noising, format-compression, and image-processing attacks. The simulation results show the effectiveness and good performance of the proposed technique in saving system resources, memory capacity, and communications bandwidth.

Rayleigh-wave dispersive energy imaging using a high-resolution linear radon transform

USGS Publications Warehouse

Luo, Y.; Xia, J.; Miller, R.D.; Xu, Y.; Liu, J.; Liu, Q.

2008-01-01

Multichannel Analysis of Surface Waves (MASW) analysis is an efficient tool to obtain the vertical shear-wave profile. One of the key steps in the MASW method is to generate an image of dispersive energy in the frequency-velocity domain, so dispersion curves can be determined by picking peaks of dispersion energy. In this paper, we propose to image Rayleigh-wave dispersive energy by high-resolution linear Radon transform (LRT). The shot gather is first transformed along the time direction to the frequency domain and then the Rayleigh-wave dispersive energy can be imaged by high-resolution LRT using a weighted preconditioned conjugate gradient algorithm. Synthetic data with a set of linear events are presented to show the process of generating dispersive energy. Results of synthetic and real-world examples demonstrate that, compared with the slant stacking algorithm, high-resolution LRT can improve the resolution of images of dispersion energy by more than 50%. ?? Birkhaueser 2008.

A Low Power Digital Accumulation Technique for Digital-Domain CMOS TDI Image Sensor.

PubMed

Yu, Changwei; Nie, Kaiming; Xu, Jiangtao; Gao, Jing

2016-09-23

In this paper, an accumulation technique suitable for digital domain CMOS time delay integration (TDI) image sensors is proposed to reduce power consumption without degrading the rate of imaging. In terms of the slight variations of quantization codes among different pixel exposures towards the same object, the pixel array is divided into two groups: one is for coarse quantization of high bits only, and the other one is for fine quantization of low bits. Then, the complete quantization codes are composed of both results from the coarse-and-fine quantization. The equivalent operation comparably reduces the total required bit numbers of the quantization. In the 0.18 µm CMOS process, two versions of 16-stage digital domain CMOS TDI image sensor chains based on a 10-bit successive approximate register (SAR) analog-to-digital converter (ADC), with and without the proposed technique, are designed. The simulation results show that the average power consumption of slices of the two versions are 6 . 47 × 10 - 8 J/line and 7 . 4 × 10 - 8 J/line, respectively. Meanwhile, the linearity of the two versions are 99.74% and 99.99%, respectively.

An efficient multiple exposure image fusion in JPEG domain

NASA Astrophysics Data System (ADS)

Hebbalaguppe, Ramya; Kakarala, Ramakrishna

2012-01-01

In this paper, we describe a method to fuse multiple images taken with varying exposure times in the JPEG domain. The proposed algorithm finds its application in HDR image acquisition and image stabilization for hand-held devices like mobile phones, music players with cameras, digital cameras etc. Image acquisition at low light typically results in blurry and noisy images for hand-held camera's. Altering camera settings like ISO sensitivity, exposure times and aperture for low light image capture results in noise amplification, motion blur and reduction of depth-of-field respectively. The purpose of fusing multiple exposures is to combine the sharp details of the shorter exposure images with high signal-to-noise-ratio (SNR) of the longer exposure images. The algorithm requires only a single pass over all images, making it efficient. It comprises of - sigmoidal boosting of shorter exposed images, image fusion, artifact removal and saturation detection. Algorithm does not need more memory than a single JPEG macro block to be kept in memory making it feasible to be implemented as the part of a digital cameras hardware image processing engine. The Artifact removal step reuses the JPEGs built-in frequency analysis and hence benefits from the considerable optimization and design experience that is available for JPEG.

Remote-sensing image encryption in hybrid domains

NASA Astrophysics Data System (ADS)

Zhang, Xiaoqiang; Zhu, Guiliang; Ma, Shilong

2012-04-01

Remote-sensing technology plays an important role in military and industrial fields. Remote-sensing image is the main means of acquiring information from satellites, which always contain some confidential information. To securely transmit and store remote-sensing images, we propose a new image encryption algorithm in hybrid domains. This algorithm makes full use of the advantages of image encryption in both spatial domain and transform domain. First, the low-pass subband coefficients of image DWT (discrete wavelet transform) decomposition are sorted by a PWLCM system in transform domain. Second, the image after IDWT (inverse discrete wavelet transform) reconstruction is diffused with 2D (two-dimensional) Logistic map and XOR operation in spatial domain. The experiment results and algorithm analyses show that the new algorithm possesses a large key space and can resist brute-force, statistical and differential attacks. Meanwhile, the proposed algorithm has the desirable encryption efficiency to satisfy requirements in practice.

Nanoscopic studies of domain structure dynamics in ferroelectric La:HfO2 capacitors

NASA Astrophysics Data System (ADS)

Buragohain, P.; Richter, C.; Schenk, T.; Lu, H.; Mikolajick, T.; Schroeder, U.; Gruverman, A.

2018-05-01

Visualization of domain structure evolution under an electrical bias has been carried out in ferroelectric La:HfO2 capacitors by a combination of Piezoresponse Force Microscopy (PFM) and pulse switching techniques to study the nanoscopic mechanism of polarization reversal and the wake-up process. It has been directly shown that the main mechanism behind the transformation of the polarization hysteretic behavior and an increase in the remanent polarization value upon the alternating current cycling is electrically induced domain de-pinning. PFM imaging and local spectroscopy revealed asymmetric switching in the La:HfO2 capacitors due to a significant imprint likely caused by the different boundary conditions at the top and bottom interfaces. Domain switching kinetics can be well-described by the nucleation limited switching model characterized by a broad distribution of the local switching times. It has been found that the domain velocity varies significantly throughout the switching process indicating strong interaction with structural defects.

Visual based laser speckle pattern recognition method for structural health monitoring

NASA Astrophysics Data System (ADS)

Park, Kyeongtaek; Torbol, Marco

2017-04-01

This study performed the system identification of a target structure by analyzing the laser speckle pattern taken by a camera. The laser speckle pattern is generated by the diffuse reflection of the laser beam on a rough surface of the target structure. The camera, equipped with a red filter, records the scattered speckle particles of the laser light in real time and the raw speckle image of the pixel data is fed to the graphic processing unit (GPU) in the system. The algorithm for laser speckle contrast analysis (LASCA) computes: the laser speckle contrast images and the laser speckle flow images. The k-mean clustering algorithm is used to classify the pixels in each frame and the clusters' centroids, which function as virtual sensors, track the displacement between different frames in time domain. The fast Fourier transform (FFT) and the frequency domain decomposition (FDD) compute the modal properties of the structure: natural frequencies and damping ratios. This study takes advantage of the large scale computational capability of GPU. The algorithm is written in Compute Unifies Device Architecture (CUDA C) that allows the processing of speckle images in real time.

Enhanced visualization of abnormalities in digital-mammographic images

NASA Astrophysics Data System (ADS)

Young, Susan S.; Moore, William E.

2002-05-01

This paper describes two new presentation methods that are intended to improve the ability of radiologists to visualize abnormalities in mammograms by enhancing the appearance of the breast parenchyma pattern relative to the fatty-tissue surroundings. The first method, referred to as mountain- view, is obtained via multiscale edge decomposition through filter banks. The image is displayed in a multiscale edge domain that causes the image to have a topographic-like appearance. The second method displays the image in the intensity domain and is referred to as contrast-enhancement presentation. The input image is first passed through a decomposition filter bank to produce a filtered output (Id). The image at the lowest resolution is processed using a LUT (look-up table) to produce a tone scaled image (I'). The LUT is designed to optimally map the code value range corresponding to the parenchyma pattern in the mammographic image into the dynamic range of the output medium. The algorithm uses a contrast weight control mechanism to produce the desired weight factors to enhance the edge information corresponding to the parenchyma pattern. The output image is formed using a reconstruction filter bank through I' and enhanced Id.

Quantitative image fusion in infrared radiometry

NASA Astrophysics Data System (ADS)

Romm, Iliya; Cukurel, Beni

2018-05-01

Towards high-accuracy infrared radiance estimates, measurement practices and processing techniques aimed to achieve quantitative image fusion using a set of multi-exposure images of a static scene are reviewed. The conventional non-uniformity correction technique is extended, as the original is incompatible with quantitative fusion. Recognizing the inherent limitations of even the extended non-uniformity correction, an alternative measurement methodology, which relies on estimates of the detector bias using self-calibration, is developed. Combining data from multi-exposure images, two novel image fusion techniques that ultimately provide high tonal fidelity of a photoquantity are considered: ‘subtract-then-fuse’, which conducts image subtraction in the camera output domain and partially negates the bias frame contribution common to both the dark and scene frames; and ‘fuse-then-subtract’, which reconstructs the bias frame explicitly and conducts image fusion independently for the dark and the scene frames, followed by subtraction in the photoquantity domain. The performances of the different techniques are evaluated for various synthetic and experimental data, identifying the factors contributing to potential degradation of the image quality. The findings reflect the superiority of the ‘fuse-then-subtract’ approach, conducting image fusion via per-pixel nonlinear weighted least squares optimization.

Secret shared multiple-image encryption based on row scanning compressive ghost imaging and phase retrieval in the Fresnel domain

NASA Astrophysics Data System (ADS)

Li, Xianye; Meng, Xiangfeng; Wang, Yurong; Yang, Xiulun; Yin, Yongkai; Peng, Xiang; He, Wenqi; Dong, Guoyan; Chen, Hongyi

2017-09-01

A multiple-image encryption method is proposed that is based on row scanning compressive ghost imaging, (t, n) threshold secret sharing, and phase retrieval in the Fresnel domain. In the encryption process, after wavelet transform and Arnold transform of the target image, the ciphertext matrix can be first detected using a bucket detector. Based on a (t, n) threshold secret sharing algorithm, the measurement key used in the row scanning compressive ghost imaging can be decomposed and shared into two pairs of sub-keys, which are then reconstructed using two phase-only mask (POM) keys with fixed pixel values, placed in the input plane and transform plane 2 of the phase retrieval scheme, respectively; and the other POM key in the transform plane 1 can be generated and updated by the iterative encoding of each plaintext image. In each iteration, the target image acts as the input amplitude constraint in the input plane. During decryption, each plaintext image possessing all the correct keys can be successfully decrypted by measurement key regeneration, compression algorithm reconstruction, inverse wavelet transformation, and Fresnel transformation. Theoretical analysis and numerical simulations both verify the feasibility of the proposed method.

Improved Plane-Wave Ultrasound Beamforming by Incorporating Angular Weighting and Coherent Compounding in Fourier Domain.

PubMed

Chen, Chuan; Hendriks, Gijs A G M; van Sloun, Ruud J G; Hansen, Hendrik H G; de Korte, Chris L

2018-05-01

In this paper, a novel processing framework is introduced for Fourier-domain beamforming of plane-wave ultrasound data, which incorporates coherent compounding and angular weighting in the Fourier domain. Angular weighting implies spectral weighting by a 2-D steering-angle-dependent filtering template. The design of this filter is also optimized as part of this paper. Two widely used Fourier-domain plane-wave ultrasound beamforming methods, i.e., Lu's f-k and Stolt's f-k methods, were integrated in the framework. To enable coherent compounding in Fourier domain for the Stolt's f-k method, the original Stolt's f-k method was modified to achieve alignment of the spectra for different steering angles in k-space. The performance of the framework was compared for both methods with and without angular weighting using experimentally obtained data sets (phantom and in vivo), and data sets (phantom) provided by the IEEE IUS 2016 plane-wave beamforming challenge. The addition of angular weighting enhanced the image contrast while preserving image resolution. This resulted in images of equal quality as those obtained by conventionally used delay-and-sum (DAS) beamforming with apodization and coherent compounding. Given the lower computational load of the proposed framework compared to DAS, to our knowledge it can, therefore, be concluded that it outperforms commonly used beamforming methods such as Stolt's f-k, Lu's f-k, and DAS.

Sortase A-mediated site-specific labeling of camelid single-domain antibody-fragments: a versatile strategy for multiple molecular imaging modalities.

PubMed

Massa, Sam; Vikani, Niravkumar; Betti, Cecilia; Ballet, Steven; Vanderhaegen, Saskia; Steyaert, Jan; Descamps, Benedicte; Vanhove, Christian; Bunschoten, Anton; van Leeuwen, Fijs W B; Hernot, Sophie; Caveliers, Vicky; Lahoutte, Tony; Muyldermans, Serge; Xavier, Catarina; Devoogdt, Nick

2016-09-01

A generic site-specific conjugation method that generates a homogeneous product is of utmost importance in tracer development for molecular imaging and therapy. We explored the protein-ligation capacity of the enzyme Sortase A to label camelid single-domain antibody-fragments, also known as nanobodies. The versatility of the approach was demonstrated by conjugating independently three different imaging probes: the chelating agents CHX-A"-DTPA and NOTA for single-photon emission computed tomography (SPECT) with indium-111 and positron emission tomography (PET) with gallium-68, respectively, and the fluorescent dye Cy5 for fluorescence reflectance imaging (FRI). After a straightforward purification process, homogeneous single-conjugated tracer populations were obtained in high yield (30-50%). The enzymatic conjugation did not affect the affinity of the tracers, nor the radiolabeling efficiency or spectral characteristics. In vivo, the tracers enabled the visualization of human epidermal growth factor receptor 2 (HER2) expressing BT474M1-tumors with high contrast and specificity as soon as 1 h post injection in all three imaging modalities. These data demonstrate Sortase A-mediated conjugation as a valuable strategy for the development of site-specifically labeled camelid single-domain antibody-fragments for use in multiple molecular imaging modalities. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Feasibility demonstration of frequency domain terahertz imaging in breast cancer margin determination

NASA Astrophysics Data System (ADS)

Yngvesson, Sigfrid K.; St. Peter, Benjamin; Siqueira, Paul; Kelly, Patrick; Glick, Stephen; Karellas, Andrew; Khan, Ashraf

2012-03-01

In breast conservation surgery, surgeons attempt to remove malignant tissue along with a surrounding margin of healthy tissue. Subsequent pathological analysis determines if those margins are clear of malignant tissue, a process that typically requires at least one day. Only then can it be determined whether a follow-up surgery is necessary. This possibility of re-excision is undesirable in terms of reducing patient morbidity, emotional stress and healthcare. It has been shown that terahertz (THz) images of breast specimens can accurately differentiate between breast carcinoma, normal fibroglandular tissue, and adipose tissue. That study employed the Time-Domain Spectroscopy (TDS) technique. We are instead developing a new technique, Frequency-Domain Terahertz Imaging (FDTI). In this joint project between UMass/Amherst and UMass Medical School/Worcester (UMMS), we are investigating the feasibility of the FDTI technique for THz reflection imaging of breast cancer margins. Our system, which produces mechanically scanned images of size 2cm x 2cm, uses a THz gas laser. The system is calibrated with mixtures of water and ethanol and reflection coefficients as low as 1% have been measured. Images from phantoms and specimens cut from breast cancer lumpectomies at UMMS will be presented. Finally, there will be a discussion of a possible transition of this FDTI setup to a compact and inexpensive CMOS THz camera for use in the operating room.

Using component technologies for web based wavelet enhanced mammographic image visualization.

PubMed

Sakellaropoulos, P; Costaridou, L; Panayiotakis, G

2000-01-01

The poor contrast detectability of mammography can be dealt with by domain specific software visualization tools. Remote desktop client access and time performance limitations of a previously reported visualization tool are addressed, aiming at more efficient visualization of mammographic image resources existing in web or PACS image servers. This effort is also motivated by the fact that at present, web browsers do not support domain-specific medical image visualization. To deal with desktop client access the tool was redesigned by exploring component technologies, enabling the integration of stand alone domain specific mammographic image functionality in a web browsing environment (web adaptation). The integration method is based on ActiveX Document Server technology. ActiveX Document is a part of Object Linking and Embedding (OLE) extensible systems object technology, offering new services in existing applications. The standard DICOM 3.0 part 10 compatible image-format specification Papyrus 3.0 is supported, in addition to standard digitization formats such as TIFF. The visualization functionality of the tool has been enhanced by including a fast wavelet transform implementation, which allows for real time wavelet based contrast enhancement and denoising operations. Initial use of the tool with mammograms of various breast structures demonstrated its potential in improving visualization of diagnostic mammographic features. Web adaptation and real time wavelet processing enhance the potential of the previously reported tool in remote diagnosis and education in mammography.

Statistical characterization of portal images and noise from portal imaging systems.

PubMed

González-López, Antonio; Morales-Sánchez, Juan; Verdú-Monedero, Rafael; Larrey-Ruiz, Jorge

2013-06-01

In this paper, we consider the statistical characteristics of the so-called portal images, which are acquired prior to the radiotherapy treatment, as well as the noise that present the portal imaging systems, in order to analyze whether the well-known noise and image features in other image modalities, such as natural image, can be found in the portal imaging modality. The study is carried out in the spatial image domain, in the Fourier domain, and finally in the wavelet domain. The probability density of the noise in the spatial image domain, the power spectral densities of the image and noise, and the marginal, joint, and conditional statistical distributions of the wavelet coefficients are estimated. Moreover, the statistical dependencies between noise and signal are investigated. The obtained results are compared with practical and useful references, like the characteristics of the natural image and the white noise. Finally, we discuss the implication of the results obtained in several noise reduction methods that operate in the wavelet domain.

A Review of Algorithms for Segmentation of Optical Coherence Tomography from Retina

PubMed Central

Kafieh, Raheleh; Rabbani, Hossein; Kermani, Saeed

2013-01-01

Optical coherence tomography (OCT) is a recently established imaging technique to describe different information about the internal structures of an object and to image various aspects of biological tissues. OCT image segmentation is mostly introduced on retinal OCT to localize the intra-retinal boundaries. Here, we review some of the important image segmentation methods for processing retinal OCT images. We may classify the OCT segmentation approaches into five distinct groups according to the image domain subjected to the segmentation algorithm. Current researches in OCT segmentation are mostly based on improving the accuracy and precision, and on reducing the required processing time. There is no doubt that current 3-D imaging modalities are now moving the research projects toward volume segmentation along with 3-D rendering and visualization. It is also important to develop robust methods capable of dealing with pathologic cases in OCT imaging. PMID:24083137

Neural network face recognition using wavelets

NASA Astrophysics Data System (ADS)

Karunaratne, Passant V.; Jouny, Ismail I.

1997-04-01

The recognition of human faces is a phenomenon that has been mastered by the human visual system and that has been researched extensively in the domain of computer neural networks and image processing. This research is involved in the study of neural networks and wavelet image processing techniques in the application of human face recognition. The objective of the system is to acquire a digitized still image of a human face, carry out pre-processing on the image as required, an then, given a prior database of images of possible individuals, be able to recognize the individual in the image. The pre-processing segment of the system includes several procedures, namely image compression, denoising, and feature extraction. The image processing is carried out using Daubechies wavelets. Once the images have been passed through the wavelet-based image processor they can be efficiently analyzed by means of a neural network. A back- propagation neural network is used for the recognition segment of the system. The main constraints of the system is with regard to the characteristics of the images being processed. The system should be able to carry out effective recognition of the human faces irrespective of the individual's facial-expression, presence of extraneous objects such as head-gear or spectacles, and face/head orientation. A potential application of this face recognition system would be as a secondary verification method in an automated teller machine.

Content-based retrieval of historical Ottoman documents stored as textual images.

PubMed

Saykol, Ediz; Sinop, Ali Kemal; Güdükbay, Ugur; Ulusoy, Ozgür; Cetin, A Enis

2004-03-01

There is an accelerating demand to access the visual content of documents stored in historical and cultural archives. Availability of electronic imaging tools and effective image processing techniques makes it feasible to process the multimedia data in large databases. In this paper, a framework for content-based retrieval of historical documents in the Ottoman Empire archives is presented. The documents are stored as textual images, which are compressed by constructing a library of symbols occurring in a document, and the symbols in the original image are then replaced with pointers into the codebook to obtain a compressed representation of the image. The features in wavelet and spatial domain based on angular and distance span of shapes are used to extract the symbols. In order to make content-based retrieval in historical archives, a query is specified as a rectangular region in an input image and the same symbol-extraction process is applied to the query region. The queries are processed on the codebook of documents and the query images are identified in the resulting documents using the pointers in textual images. The querying process does not require decompression of images. The new content-based retrieval framework is also applicable to many other document archives using different scripts.

Application of off-line image processing for optimization in chest computed radiography using a low cost system.

PubMed

Muhogora, Wilbroad E; Msaki, Peter; Padovani, Renato

2015-03-08

 The objective of this study was to improve the visibility of anatomical details by applying off-line postimage processing in chest computed radiography (CR). Four spatial domain-based external image processing techniques were developed by using MATLAB software version 7.0.0.19920 (R14) and image processing tools. The developed techniques were implemented to sample images and their visual appearances confirmed by two consultant radiologists to be clinically adequate. The techniques were then applied to 200 chest clinical images and randomized with other 100 images previously processed online. These 300 images were presented to three experienced radiologists for image quality assessment using standard quality criteria. The mean and ranges of the average scores for three radiologists were characterized for each of the developed technique and imaging system. The Mann-Whitney U-test was used to test the difference of details visibility between the images processed using each of the developed techniques and the corresponding images processed using default algorithms. The results show that the visibility of anatomical features improved significantly (0.005 ≤ p ≤ 0.02) with combinations of intensity values adjustment and/or spatial linear filtering techniques for images acquired using 60 ≤ kVp ≤ 70. However, there was no improvement for images acquired using 102 ≤ kVp ≤ 107 (0.127 ≤ p ≤ 0.48). In conclusion, the use of external image processing for optimization can be effective in chest CR, but should be implemented in consultations with the radiologists.

Experimental observation of spatial quantum noise reduction below the standard quantum limit with bright twin beams of light

NASA Astrophysics Data System (ADS)

Kumar, Ashok; Nunley, Hayden; Marino, Alberto

2016-05-01

Quantum noise reduction (QNR) below the standard quantum limit (SQL) has been a subject of interest for the past two to three decades due to its wide range of applications in quantum metrology and quantum information processing. To date, most of the attention has focused on the study of QNR in the temporal domain. However, many areas in quantum optics, specifically in quantum imaging, could benefit from QNR not only in the temporal domain but also in the spatial domain. With the use of a high quantum efficiency electron multiplier charge coupled device (EMCCD) camera, we have observed spatial QNR below the SQL in bright narrowband twin light beams generated through a four-wave mixing (FWM) process in hot rubidium atoms. Owing to momentum conservation in this process, the twin beams are momentum correlated. This leads to spatial quantum correlations and spatial QNR. Our preliminary results show a spatial QNR of over 2 dB with respect to the SQL. Unlike previous results on spatial QNR with faint and broadband photon pairs from parametric down conversion (PDC), we demonstrate spatial QNR with spectrally and spatially narrowband bright light beams. The results obtained will be useful for atom light interaction based quantum protocols and quantum imaging. Work supported by the W.M. Keck Foundation.

Power spectral ensity of markov texture fields

NASA Technical Reports Server (NTRS)

Shanmugan, K. S.; Holtzman, J. C.

1984-01-01

Texture is an important image characteristic. A variety of spatial domain techniques were proposed for extracting and utilizing textural features for segmenting and classifying images. for the most part, these spatial domain techniques are ad hos in nature. A markov random field model for image texture is discussed. A frequency domain description of image texture is derived in terms of the power spectral density. This model is used for designing optimum frequency domain filters for enhancing, restoring and segmenting images based on their textural properties.

Matrix decomposition graphics processing unit solver for Poisson image editing

NASA Astrophysics Data System (ADS)

Lei, Zhao; Wei, Li

2012-10-01

In recent years, gradient-domain methods have been widely discussed in the image processing field, including seamless cloning and image stitching. These algorithms are commonly carried out by solving a large sparse linear system: the Poisson equation. However, solving the Poisson equation is a computational and memory intensive task which makes it not suitable for real-time image editing. A new matrix decomposition graphics processing unit (GPU) solver (MDGS) is proposed to settle the problem. A matrix decomposition method is used to distribute the work among GPU threads, so that MDGS will take full advantage of the computing power of current GPUs. Additionally, MDGS is a hybrid solver (combines both the direct and iterative techniques) and has two-level architecture. These enable MDGS to generate identical solutions with those of the common Poisson methods and achieve high convergence rate in most cases. This approach is advantageous in terms of parallelizability, enabling real-time image processing, low memory-taken and extensive applications.

Qualitative Constraint Reasoning For Image Understanding

NASA Astrophysics Data System (ADS)

Perry, John L.

1987-05-01

Military planners and analysts are exceedingly concerned with increasing the effectiveness of command and control (C2) processes for battlefield management (BM). A variety of technical approaches have been taken in this effort. These approaches are intended to support and assist commanders in situation assessment, course of action generation and evaluation, and other C2 decision-making tasks. A specific task within this technology support includes the ability to effectively gather information concerning opposing forces and plan/replan tactical maneuvers. Much of the information that is gathered is image-derived, along with collateral data supporting this visual imagery. In this paper, we intend to describe a process called qualitative constraint reasoning (QCR) which is being developed as a mechanism for reasoning in the mid to high level vision domain. The essential element of QCR is the abstraction process. One of the factors that is unique to QCR is the level at which the abstraction process occurs relative to the problem domain. The computational mechanisms used in QCR belong to a general class of problem called the consistent labeling problem. The success of QCR is its ability to abstract out from a visual domain a structure appropriate for applying the labeling procedure. An example will be given that will exemplify the abstraction process for a battlefield management application. Exploratory activities are underway for investigating the suitability of QCR approach for the battlefield scenario. Further research is required to investigate the utility of QCR in a more complex battlefield environment.

White matter correlates of cognitive domains in normal aging with diffusion tensor imaging.

PubMed

Sasson, Efrat; Doniger, Glen M; Pasternak, Ofer; Tarrasch, Ricardo; Assaf, Yaniv

2013-01-01

The ability to perform complex as well as simple cognitive tasks engages a network of brain regions that is mediated by the white matter fiber bundles connecting them. Different cognitive tasks employ distinctive white matter fiber bundles. The temporal lobe and its projections subserve a variety of key functions known to deteriorate during aging. In a cohort of 52 healthy subjects (ages 25-82 years), we performed voxel-wise regression analysis correlating performance in higher-order cognitive domains (executive function, information processing speed, and memory) with white matter integrity, as measured by diffusion tensor imaging (DTI) fiber tracking in the temporal lobe projections [uncinate fasciculus (UF), fornix, cingulum, inferior longitudinal fasciculus (ILF), and superior longitudinal fasciculus (SLF)]. The fiber tracts were spatially registered and statistical parametric maps were produced to spatially localize the significant correlations. Results showed that performance in the executive function domain is correlated with DTI parameters in the left SLF and right UF; performance in the information processing speed domain is correlated with fractional anisotropy (FA) in the left cingulum, left fornix, right and left ILF and SLF; and the memory domain shows significant correlations with DTI parameters in the right fornix, right cingulum, left ILF, left SLF and right UF. These findings suggest that DTI tractography enables anatomical definition of region of interest (ROI) for correlation of behavioral parameters with diffusion indices, and functionality can be correlated with white matter integrity.

Determination of Hydrodynamic Parameters on Two--Phase Flow Gas - Liquid in Pipes with Different Inclination Angles Using Image Processing Algorithm

NASA Astrophysics Data System (ADS)

Montoya, Gustavo; Valecillos, María; Romero, Carlos; Gonzáles, Dosinda

2009-11-01

In the present research a digital image processing-based automated algorithm was developed in order to determine the phase's height, hold up, and statistical distribution of the drop size in a two-phase system water-air using pipes with 0 , 10 , and 90 of inclination. Digital images were acquired with a high speed camera (up to 4500fps), using an equipment that consist of a system with three acrylic pipes with diameters of 1.905, 3.175, and 4.445 cm. Each pipe is arranged in two sections of 8 m of length. Various flow patterns were visualized for different superficial velocities of water and air. Finally, using the image processing program designed in Matlab/Simulink^, the captured images were processed to establish the parameters previously mentioned. The image processing algorithm is based in the frequency domain analysis of the source pictures, which allows to find the phase as the edge between the water and air, through a Sobel filter that extracts the high frequency components of the image. The drop size was found using the calculation of the Feret diameter. Three flow patterns were observed: Annular, ST, and ST&MI.

Ultrasound breast imaging using frequency domain reverse time migration

NASA Astrophysics Data System (ADS)

Roy, O.; Zuberi, M. A. H.; Pratt, R. G.; Duric, N.

2016-04-01

Conventional ultrasonography reconstruction techniques, such as B-mode, are based on a simple wave propagation model derived from a high frequency approximation. Therefore, to minimize model mismatch, the central frequency of the input pulse is typically chosen between 3 and 15 megahertz. Despite the increase in theoretical resolution, operating at higher frequencies comes at the cost of lower signal-to-noise ratio. This ultimately degrades the image contrast and overall quality at higher imaging depths. To address this issue, we investigate a reflection imaging technique, known as reverse time migration, which uses a more accurate propagation model for reconstruction. We present preliminary simulation results as well as physical phantom image reconstructions obtained using data acquired with a breast imaging ultrasound tomography prototype. The original reconstructions are filtered to remove low-wavenumber artifacts that arise due to the inclusion of the direct arrivals. We demonstrate the advantage of using an accurate sound speed model in the reverse time migration process. We also explain how the increase in computational complexity can be mitigated using a frequency domain approach and a parallel computing platform.

Computational Imaging in Demanding Conditions

DTIC Science & Technology

2015-11-18

spatiotemporal domain where such blur is not present.  Detailed Accomplishments:  ● Removing  Atmospheric   Turbulence  via Space-Invariant  Deconvolution:  ○ To...given image sequence distorted by  atmospheric   turbulence . This approach  reduces the space and time-varying deblurring problem to a shift invariant...SUBJECT TERMS Image processing, Computational imaging, turbulence , blur, enhancement 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18

Fission gas bubble identification using MATLAB's image processing toolbox

DOE Office of Scientific and Technical Information (OSTI.GOV)

Collette, R.; King, J.; Keiser, Jr., D.

Automated image processing routines have the potential to aid in the fuel performance evaluation process by eliminating bias in human judgment that may vary from person-to-person or sample-to-sample. In addition, this study presents several MATLAB based image analysis routines designed for fission gas void identification in post-irradiation examination of uranium molybdenum (U–Mo) monolithic-type plate fuels. Frequency domain filtration, enlisted as a pre-processing technique, can eliminate artifacts from the image without compromising the critical features of interest. This process is coupled with a bilateral filter, an edge-preserving noise removal technique aimed at preparing the image for optimal segmentation. Adaptive thresholding provedmore » to be the most consistent gray-level feature segmentation technique for U–Mo fuel microstructures. The Sauvola adaptive threshold technique segments the image based on histogram weighting factors in stable contrast regions and local statistics in variable contrast regions. Once all processing is complete, the algorithm outputs the total fission gas void count, the mean void size, and the average porosity. The final results demonstrate an ability to extract fission gas void morphological data faster, more consistently, and at least as accurately as manual segmentation methods.« less

Fission gas bubble identification using MATLAB's image processing toolbox

DOE PAGES

Collette, R.; King, J.; Keiser, Jr., D.; ...

2016-06-08

Automated image processing routines have the potential to aid in the fuel performance evaluation process by eliminating bias in human judgment that may vary from person-to-person or sample-to-sample. In addition, this study presents several MATLAB based image analysis routines designed for fission gas void identification in post-irradiation examination of uranium molybdenum (U–Mo) monolithic-type plate fuels. Frequency domain filtration, enlisted as a pre-processing technique, can eliminate artifacts from the image without compromising the critical features of interest. This process is coupled with a bilateral filter, an edge-preserving noise removal technique aimed at preparing the image for optimal segmentation. Adaptive thresholding provedmore » to be the most consistent gray-level feature segmentation technique for U–Mo fuel microstructures. The Sauvola adaptive threshold technique segments the image based on histogram weighting factors in stable contrast regions and local statistics in variable contrast regions. Once all processing is complete, the algorithm outputs the total fission gas void count, the mean void size, and the average porosity. The final results demonstrate an ability to extract fission gas void morphological data faster, more consistently, and at least as accurately as manual segmentation methods.« less

Motion-compensated hand-held common-path Fourier-domain optical coherence tomography probe for image-guided intervention

NASA Astrophysics Data System (ADS)

Huang, Yong; Song, Cheol; Liu, Xuan; Kang, Jin U.

2013-03-01

A motion-compensated hand-held common-path Fourier-domain optical coherence tomography imaging probe has been developed for image guided intervention during microsurgery. A hand-held prototype instrument was designed and fabricated by integrating an imaging fiber probe inside a stainless steel needle which is attached to the ceramic shaft of a piezoelectric motor housed in an aluminum handle. The fiber probe obtains A-scan images. The distance information was extracted from the A-scans to track the sample surface distance and a fixed distance was maintained by a feedback motor control which effectively compensated hand tremor and target movements in the axial direction. Graphical user interface, real-time data processing, and visualization based on a CPU-GPU hybrid programming architecture were developed and used in the implantation of this system. To validate the system, free-hand optical coherence tomography images using various samples were obtained. The system can be easily integrated into microsurgical tools and robotics for a wide range of clinical applications. Such tools could offer physicians the freedom to easily image sites of interest with reduced risk and higher image quality.

In vivo three-dimensional imaging of human corneal nerves using Fourier-domain optical coherence tomography

NASA Astrophysics Data System (ADS)

Shin, Jun Geun; Hwang, Ho Sik; Eom, Tae Joong; Lee, Byeong Ha

2017-01-01

We have employed Fourier-domain optical coherence tomography (FD-OCT) to achieve corneal nerve imaging, which could be useful in surgical planning and refractive surgery. Because the three-dimensional (3-D) images of the corneal nerves were acquired in vivo, unintentional movement of the subject during the measurement led to imaging artifacts. These artifacts were compensated for with a series of signal processing techniques, namely realigning A-scan images to flatten the boundary and cross-correlating adjacent B-scan images. To overcome the undesirably large signal from scattering at the corneal surface and iris, volume rendering and maximum intensity projections were performed with only the data taken in the stromal region of the cornea, which is located between 200 and 500 μm from the corneal surface. The 3-D volume imaging of a 10×10 mm2 area took 9.8 s, which is slightly shorter than the normal tear breakup time. This allowed us to image the branched and threadlike corneal nerve bundles within the human eye. The experimental results show that FD-OCT systems have the potential to be useful in clinical investigations of corneal nerves and by minimizing nerve injury during clinical or surgical procedures.

Computational analysis of Pelton bucket tip erosion using digital image processing

NASA Astrophysics Data System (ADS)

Shrestha, Bim Prasad; Gautam, Bijaya; Bajracharya, Tri Ratna

2008-03-01

Erosion of hydro turbine components through sand laden river is one of the biggest problems in Himalayas. Even with sediment trapping systems, complete removal of fine sediment from water is impossible and uneconomical; hence most of the turbine components in Himalayan Rivers are exposed to sand laden water and subject to erode. Pelton bucket which are being wildly used in different hydropower generation plant undergoes erosion on the continuous presence of sand particles in water. The subsequent erosion causes increase in splitter thickness, which is supposed to be theoretically zero. This increase in splitter thickness gives rise to back hitting of water followed by decrease in turbine efficiency. This paper describes the process of measurement of sharp edges like bucket tip using digital image processing. Image of each bucket is captured and allowed to run for 72 hours; sand concentration in water hitting the bucket is closely controlled and monitored. Later, the image of the test bucket is taken in the same condition. The process is repeated for 10 times. In this paper digital image processing which encompasses processes that performs image enhancement in both spatial and frequency domain. In addition, the processes that extract attributes from images, up to and including the measurement of splitter's tip. Processing of image has been done in MATLAB 6.5 platform. The result shows that quantitative measurement of edge erosion of sharp edges could accurately be detected and the erosion profile could be generated using image processing technique.

Stereo matching and view interpolation based on image domain triangulation.

PubMed

Fickel, Guilherme Pinto; Jung, Claudio R; Malzbender, Tom; Samadani, Ramin; Culbertson, Bruce

2013-09-01

This paper presents a new approach for stereo matching and view interpolation problems based on triangular tessellations suitable for a linear array of rectified cameras. The domain of the reference image is initially partitioned into triangular regions using edge and scale information, aiming to place vertices along image edges and increase the number of triangles in textured regions. A region-based matching algorithm is then used to find an initial disparity for each triangle, and a refinement stage is applied to change the disparity at the vertices of the triangles, generating a piecewise linear disparity map. A simple post-processing procedure is applied to connect triangles with similar disparities generating a full 3D mesh related to each camera (view), which are used to generate new synthesized views along the linear camera array. With the proposed framework, view interpolation reduces to the trivial task of rendering polygonal meshes, which can be done very fast, particularly when GPUs are employed. Furthermore, the generated views are hole-free, unlike most point-based view interpolation schemes that require some kind of post-processing procedures to fill holes.

Cross-Domain Shoe Retrieval with a Semantic Hierarchy of Attribute Classification Network.

PubMed

Zhan, Huijing; Shi, Boxin; Kot, Alex C

2017-08-04

Cross-domain shoe image retrieval is a challenging problem, because the query photo from the street domain (daily life scenario) and the reference photo in the online domain (online shop images) have significant visual differences due to the viewpoint and scale variation, self-occlusion, and cluttered background. This paper proposes the Semantic Hierarchy Of attributE Convolutional Neural Network (SHOE-CNN) with a three-level feature representation for discriminative shoe feature expression and efficient retrieval. The SHOE-CNN with its newly designed loss function systematically merges semantic attributes of closer visual appearances to prevent shoe images with the obvious visual differences being confused with each other; the features extracted from image, region, and part levels effectively match the shoe images across different domains. We collect a large-scale shoe dataset composed of 14341 street domain and 12652 corresponding online domain images with fine-grained attributes to train our network and evaluate our system. The top-20 retrieval accuracy improves significantly over the solution with the pre-trained CNN features.

Angle-domain common imaging gather extraction via Kirchhoff prestack depth migration based on a traveltime table in transversely isotropic media

NASA Astrophysics Data System (ADS)

Liu, Shaoyong; Gu, Hanming; Tang, Yongjie; Bingkai, Han; Wang, Huazhong; Liu, Dingjin

2018-04-01

Angle-domain common image-point gathers (ADCIGs) can alleviate the limitations of common image-point gathers in an offset domain, and have been widely used for velocity inversion and amplitude variation with angle (AVA) analysis. We propose an effective algorithm for generating ADCIGs in transversely isotropic (TI) media based on the gradient of traveltime by Kirchhoff pre-stack depth migration (KPSDM), as the dynamic programming method for computing the traveltime in TI media would not suffer from the limitation of shadow zones and traveltime interpolation. Meanwhile, we present a specific implementation strategy for ADCIG extraction via KPSDM. Three major steps are included in the presented strategy: (1) traveltime computation using a dynamic programming approach in TI media; (2) slowness vector calculation by the gradient of a traveltime table calculated previously; (3) construction of illumination vectors and subsurface angles in the migration process. Numerical examples are included to demonstrate the effectiveness of our approach, which henceforce shows its potential application for subsequent tomographic velocity inversion and AVA.

Relative expertise affects N170 during selective attention to superimposed face-character images.

PubMed

Ip, Chengteng; Wang, Hailing; Fu, Shimin

2017-07-01

It remains unclear whether the N170 of ERPs reflects domain-specific or domain-general visual object processing. In this study, we used superimposed images of a face and a Chinese character such that participants' relative expertise for the two object types was either similar (Experiment 1 and 2) or different (Experiment 3). Experiment 1 showed that N170 amplitude was larger when participants attended to the character instead of the face of a face-character combination. This result was unchanged in Experiment 2, in which task difficulty was selectively increased for the face component of the combined stimuli. Experiment 3 showed that, although this N170 enhancement for attending to characters relative to faces persisted for false characters with recognizable parts, it disappeared for unrecognizable characters. Therefore, N170 amplitude was significantly greater for Chinese characters than for faces presented within a combined image, independent of the relative task difficulty. This result strongly calls N170 face selectivity into question, demonstrating that, contrary to the expectations established by a domain-specific account, N170 is modulated by expertise. © 2017 Society for Psychophysiological Research.

Novel Fourier-domain constraint for fast phase retrieval in coherent diffraction imaging.

PubMed

Latychevskaia, Tatiana; Longchamp, Jean-Nicolas; Fink, Hans-Werner

2011-09-26

Coherent diffraction imaging (CDI) for visualizing objects at atomic resolution has been realized as a promising tool for imaging single molecules. Drawbacks of CDI are associated with the difficulty of the numerical phase retrieval from experimental diffraction patterns; a fact which stimulated search for better numerical methods and alternative experimental techniques. Common phase retrieval methods are based on iterative procedures which propagate the complex-valued wave between object and detector plane. Constraints in both, the object and the detector plane are applied. While the constraint in the detector plane employed in most phase retrieval methods requires the amplitude of the complex wave to be equal to the squared root of the measured intensity, we propose a novel Fourier-domain constraint, based on an analogy to holography. Our method allows achieving a low-resolution reconstruction already in the first step followed by a high-resolution reconstruction after further steps. In comparison to conventional schemes this Fourier-domain constraint results in a fast and reliable convergence of the iterative reconstruction process. © 2011 Optical Society of America

Custom large scale integrated circuits for spaceborne SAR processors

NASA Technical Reports Server (NTRS)

Tyree, V. C.

1978-01-01

The application of modern LSI technology to the development of a time-domain azimuth correlator for SAR processing is discussed. General design requirements for azimuth correlators for missions such as SEASAT-A, Venus orbital imaging radar (VOIR), and shuttle imaging radar (SIR) are summarized. Several azimuth correlator architectures that are suitable for implementation using custom LSI devices are described. Technical factors pertaining to selection of appropriate LSI technologies are discussed, and the maturity of alternative technologies for spacecraft applications are reported in the context of expected space mission launch dates. The preliminary design of a custom LSI time-domain azimuth correlator device (ACD) being developed for use in future SAR processors is detailed.

An image-domain, contrast material extraction method for Dual-Energy CT

PubMed Central

Lambert, Jack W.; Sun, Yuxin; Gould, Robert G.; Ohliger, Michael A.; Li, Zhixi; Yeh, Benjamin M.

2016-01-01

Objectives Conventional material decomposition techniques for dual-energy CT (DECT) assume mass or volume conservation, where the CT number of each voxel is fully assigned to predefined materials. We present an image-domain contrast material extraction process (CMEP) method that preferentially extracts contrast-producing materials while leaving the remaining image intact. Materials and Methods Image processing freeware (Fiji) is used to perform consecutive arithmetic operations on a dual-energy ratio map to generate masks, which are then applied to the original images to generate material-specific images. First, a low-energy image is divided by a high-energy image to generate a ratio map. The ratio map is then split into material-specific masks. Ratio intervals known to correspond to particular materials (e.g. iodine, calcium) are assigned a multiplier of 1, while ratio values in between these intervals are assigned linear gradients from 0 to 1. The masks are then multiplied by an original CT image to produce material-specific images. The method was tested quantitatively at Dual-Source (DSCT) and Rapid kVp-Switching CT (RSCT) with phantoms using pure and mixed formulations of tungsten, calcium and iodine. Errors were evaluated by comparing the known material concentrations with those derived from the CMEP material-specific images. Further qualitative evaluation was performed in vivo at RSCT with a rabbit model using identical CMEP parameters to the phantom. Orally administered tungsten, vascularly administered iodine, and skeletal calcium were used as the three contrast materials. Results All five material combinations; tungsten, iodine and calcium, and mixtures of tungsten-calcium and iodine-calcium, showed distinct dual-energy ratios, largely independent of material concentration at both DSCT and RSCT. The CMEP was successful in both phantoms and in vivo. For pure contrast materials in the phantom, the maximum error between the known and CMEP-derived material concentrations was 0.9 mg/mL, 24.9 mg/mL and 0.4 mg/mL for iodine, calcium and tungsten respectively. Mixtures of iodine and calcium showed the highest discrepancies, which reflected the sensitivity of iodine to the image-type chosen for the extraction of the final material-specific image. The rabbit model was able to clearly show the three extracted material phases, vascular iodine, oral tungsten and skeletal calcium. Some skeletal calcium was misassigned to the extracted iodine image, however this did not impede the depiction of the vasculature. Conclusions The CMEP is a straightforward, image domain approach to extract material signal at dual-energy CT. It has particular value for separation of experimental high-Z contrast elements from conventional iodine contrast or calcium, even when the exact attenuation coefficient profiles of desired contrast materials may be unknown. The CMEP is readily implemented in the image-domain within freeware, and can be adapted for use with images from multiple vendors. PMID:27875338

Quantitative Vectorial Magnetic Imaging of Multi Domain Rock Forming Minerals using Nitrogen-Vacancy Centers in Diamond

NASA Astrophysics Data System (ADS)

Shaar, R.; Farchi, E.; Farfurnik, D.; Ebert, Y.; Haim, G.; Bar-Gill, N.

2017-12-01

Magnetization in rock samples is crucial for paleomagnetometry research, as it harbors valuable geological information on long term processes, such as tectonic movements and the formation of oceans and continents. Nevertheless, current techniques are limited in their ability to measure high spatial resolution and high-sensitivity quantitative vectorial magnetic signatures from individual minerals and micrometer scale samples. As a result, our understanding of bulk rock magnetization is limited, specifically for the case of multi-domain minerals. In this work we use a newly developed nitrogen-vacancy magnetic microscope, capable of quantitative vectorial magnetic imaging with optical resolution. We demonstrate direct imaging of the vectorial magnetic field of a single, multi-domain dendritic magnetite, as well as the measurement and calculation of the weak magnetic moments of an individual grain on the micron scale. Our results were measured in a standoff distance of 3-10 μm, with 350 nm spatial resolution, magnetic sensitivity of 6 μT/√(Hz) and a field of view of 35 μm. The results presented here show the capabilities and the future potential of NV microscopy in measuring the magnetic signals of individual micrometer scale grains. These outcomes pave the way for future applications in paleomagnetometry, and for the fundamental understanding of magnetization in multi-domain samples.

Accurate determination of the diffusion coefficient of proteins by Fourier analysis with whole column imaging detection.

PubMed

Zarabadi, Atefeh S; Pawliszyn, Janusz

2015-02-17

Analysis in the frequency domain is considered a powerful tool to elicit precise information from spectroscopic signals. In this study, the Fourier transformation technique is employed to determine the diffusion coefficient (D) of a number of proteins in the frequency domain. Analytical approaches are investigated for determination of D from both experimental and data treatment viewpoints. The diffusion process is modeled to calculate diffusion coefficients based on the Fourier transformation solution to Fick's law equation, and its results are compared to time domain results. The simulations characterize optimum spatial and temporal conditions and demonstrate the noise tolerance of the method. The proposed model is validated by its application for the electropherograms from the diffusion path of a set of proteins. Real-time dynamic scanning is conducted to monitor dispersion by employing whole column imaging detection technology in combination with capillary isoelectric focusing (CIEF) and the imaging plug flow (iPF) experiment. These experimental techniques provide different peak shapes, which are utilized to demonstrate the Fourier transformation ability in extracting diffusion coefficients out of irregular shape signals. Experimental results confirmed that the Fourier transformation procedure substantially enhanced the accuracy of the determined values compared to those obtained in the time domain.

Holographic imaging based on time-domain data of natural-fiber-containing materials

DOEpatents

Bunch, Kyle J.; McMakin, Douglas L.

2012-09-04

Methods and apparatuses for imaging material properties in natural-fiber-containing materials can utilize time-domain data. In particular, images can be constructed that provide quantified measures of localized moisture content. For example, one or more antennas and at least one transceiver can be configured to collect time-domain data from radiation interacting with the natural-fiber-containing materials. The antennas and the transceivers are configured to transmit and receive electromagnetic radiation at one or more frequencies, which are between 50 MHz and 1 THz, according to a time-domain impulse function. A computing device is configured to transform the time-domain data to frequency-domain data, to apply a synthetic imaging algorithm for constructing a three-dimensional image of the natural-fiber-containing materials, and to provide a quantified measure of localized moisture content based on a pre-determined correlation of moisture content to frequency-domain data.

Bio-inspired multi-mode optic flow sensors for micro air vehicles

NASA Astrophysics Data System (ADS)

Park, Seokjun; Choi, Jaehyuk; Cho, Jihyun; Yoon, Euisik

2013-06-01

Monitoring wide-field surrounding information is essential for vision-based autonomous navigation in micro-air-vehicles (MAV). Our image-cube (iCube) module, which consists of multiple sensors that are facing different angles in 3-D space, can be applied to the wide-field of view optic flows estimation (μ-Compound eyes) and to attitude control (μ- Ocelli) in the Micro Autonomous Systems and Technology (MAST) platforms. In this paper, we report an analog/digital (A/D) mixed-mode optic-flow sensor, which generates both optic flows and normal images in different modes for μ- Compound eyes and μ-Ocelli applications. The sensor employs a time-stamp based optic flow algorithm which is modified from the conventional EMD (Elementary Motion Detector) algorithm to give an optimum partitioning of hardware blocks in analog and digital domains as well as adequate allocation of pixel-level, column-parallel, and chip-level signal processing. Temporal filtering, which may require huge hardware resources if implemented in digital domain, is remained in a pixel-level analog processing unit. The rest of the blocks, including feature detection and timestamp latching, are implemented using digital circuits in a column-parallel processing unit. Finally, time-stamp information is decoded into velocity from look-up tables, multiplications, and simple subtraction circuits in a chip-level processing unit, thus significantly reducing core digital processing power consumption. In the normal image mode, the sensor generates 8-b digital images using single slope ADCs in the column unit. In the optic flow mode, the sensor estimates 8-b 1-D optic flows from the integrated mixed-mode algorithm core and 2-D optic flows with an external timestamp processing, respectively.

Functional Spectral Domain Optical Coherence Tomography imaging

NASA Astrophysics Data System (ADS)

Bower, Bradley A.

Spectral Domain Optical Coherence Tomography (SDOCT) is a high-speed, high resolution imaging modality capable of structural and functional characterization of tissue microstructure. SDOCT fills a niche between histology and ultrasound imaging, providing non-contact, non-invasive backscattering amplitude and phase from a sample. Due to the translucent nature of the tissue, ophthalmic imaging is an ideal space for SDOCT imaging. Structural imaging of the retina has provided new insights into ophthalmic disease. The phase component of SDOCT images remains largely underexplored, though. While Doppler SDOCT has been explored in a research setting, it has yet to gain traction in the clinic. Other, functional exploitations of the phase are possible and necessary to expand the utility of SDOCT. Spectral Domain Phase Microscopy (SDPM) is an extension of SDOCT that is capable of resolving sub-wavelength displacements within a focal volume. Application of sub-wavelength displacement measurement imaging could provide a new method for non-invasive optophysiological measurement. This body of work encompasses both hardware and software design and development for implementation of SDOCT. Structural imaging was proven in both the lab and the clinic. Coarse phase changes associated with Doppler flow frequency shifts were recorded and a study was conducted to validate Doppler measurement. Fine phase changes were explored through SDPM applications. Preliminary optophysiology data was acquired to study the potential of sub-wavelength measurements in the retina. To remove the complexity associated with in-vivo human retinal imaging, a first principles approach using isolated nerve samples was applied using standard SDPM and a depthencoded technique for measuring conduction velocity. Results from amplitude as well as both coarse and fine phase processing are presented. In-vivo optophysiology using SDPM is a promising avenue for exploration, and projects furthering or extending this body of work are discussed.

Temporal Processing Capacity in High-Level Visual Cortex Is Domain Specific.

PubMed

Stigliani, Anthony; Weiner, Kevin S; Grill-Spector, Kalanit

2015-09-09

Prevailing hierarchical models propose that temporal processing capacity--the amount of information that a brain region processes in a unit time--decreases at higher stages in the ventral stream regardless of domain. However, it is unknown if temporal processing capacities are domain general or domain specific in human high-level visual cortex. Using a novel fMRI paradigm, we measured temporal capacities of functional regions in high-level visual cortex. Contrary to hierarchical models, our data reveal domain-specific processing capacities as follows: (1) regions processing information from different domains have differential temporal capacities within each stage of the visual hierarchy and (2) domain-specific regions display the same temporal capacity regardless of their position in the processing hierarchy. In general, character-selective regions have the lowest capacity, face- and place-selective regions have an intermediate capacity, and body-selective regions have the highest capacity. Notably, domain-specific temporal processing capacities are not apparent in V1 and have perceptual implications. Behavioral testing revealed that the encoding capacity of body images is higher than that of characters, faces, and places, and there is a correspondence between peak encoding rates and cortical capacities for characters and bodies. The present evidence supports a model in which the natural statistics of temporal information in the visual world may affect domain-specific temporal processing and encoding capacities. These findings suggest that the functional organization of high-level visual cortex may be constrained by temporal characteristics of stimuli in the natural world, and this temporal capacity is a characteristic of domain-specific networks in high-level visual cortex. Significance statement: Visual stimuli bombard us at different rates every day. For example, words and scenes are typically stationary and vary at slow rates. In contrast, bodies are dynamic and typically change at faster rates. Using a novel fMRI paradigm, we measured temporal processing capacities of functional regions in human high-level visual cortex. Contrary to prevailing theories, we find that different regions have different processing capacities, which have behavioral implications. In general, character-selective regions have the lowest capacity, face- and place-selective regions have an intermediate capacity, and body-selective regions have the highest capacity. These results suggest that temporal processing capacity is a characteristic of domain-specific networks in high-level visual cortex and contributes to the segregation of cortical regions. Copyright © 2015 the authors 0270-6474/15/3512412-13$15.00/0.

Empirical projection-based basis-component decomposition method

NASA Astrophysics Data System (ADS)

Brendel, Bernhard; Roessl, Ewald; Schlomka, Jens-Peter; Proksa, Roland

2009-02-01

Advances in the development of semiconductor based, photon-counting x-ray detectors stimulate research in the domain of energy-resolving pre-clinical and clinical computed tomography (CT). For counting detectors acquiring x-ray attenuation in at least three different energy windows, an extended basis component decomposition can be performed in which in addition to the conventional approach of Alvarez and Macovski a third basis component is introduced, e.g., a gadolinium based CT contrast material. After the decomposition of the measured projection data into the basis component projections, conventional filtered-backprojection reconstruction is performed to obtain the basis-component images. In recent work, this basis component decomposition was obtained by maximizing the likelihood-function of the measurements. This procedure is time consuming and often unstable for excessively noisy data or low intrinsic energy resolution of the detector. Therefore, alternative procedures are of interest. Here, we introduce a generalization of the idea of empirical dual-energy processing published by Stenner et al. to multi-energy, photon-counting CT raw data. Instead of working in the image-domain, we use prior spectral knowledge about the acquisition system (tube spectra, bin sensitivities) to parameterize the line-integrals of the basis component decomposition directly in the projection domain. We compare this empirical approach with the maximum-likelihood (ML) approach considering image noise and image bias (artifacts) and see that only moderate noise increase is to be expected for small bias in the empirical approach. Given the drastic reduction of pre-processing time, the empirical approach is considered a viable alternative to the ML approach.

A Spatiotemporal Clustering Approach to Maritime Domain Awareness

DTIC Science & Technology

2013-09-01

1997. [25] M. E. Celebi, “Effective initialization of k-means for color quantization,” 16th IEEE International Conference on Image Processing (ICIP...release; distribution is unlimited 12b. DISTRIBUTION CODE 13. ABSTRACT (maximum 200 words) Spatiotemporal clustering is the process of grouping...Department of Electrical and Computer Engineering iv THIS PAGE INTENTIONALLY LEFT BLANK v ABSTRACT Spatiotemporal clustering is the process of

Statistical CT noise reduction with multiscale decomposition and penalized weighted least squares in the projection domain

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tang Shaojie; Tang Xiangyang; School of Automation, Xi'an University of Posts and Telecommunications, Xi'an, Shaanxi 710121

2012-09-15

Purposes: The suppression of noise in x-ray computed tomography (CT) imaging is of clinical relevance for diagnostic image quality and the potential for radiation dose saving. Toward this purpose, statistical noise reduction methods in either the image or projection domain have been proposed, which employ a multiscale decomposition to enhance the performance of noise suppression while maintaining image sharpness. Recognizing the advantages of noise suppression in the projection domain, the authors propose a projection domain multiscale penalized weighted least squares (PWLS) method, in which the angular sampling rate is explicitly taken into consideration to account for the possible variation ofmore » interview sampling rate in advanced clinical or preclinical applications. Methods: The projection domain multiscale PWLS method is derived by converting an isotropic diffusion partial differential equation in the image domain into the projection domain, wherein a multiscale decomposition is carried out. With adoption of the Markov random field or soft thresholding objective function, the projection domain multiscale PWLS method deals with noise at each scale. To compensate for the degradation in image sharpness caused by the projection domain multiscale PWLS method, an edge enhancement is carried out following the noise reduction. The performance of the proposed method is experimentally evaluated and verified using the projection data simulated by computer and acquired by a CT scanner. Results: The preliminary results show that the proposed projection domain multiscale PWLS method outperforms the projection domain single-scale PWLS method and the image domain multiscale anisotropic diffusion method in noise reduction. In addition, the proposed method can preserve image sharpness very well while the occurrence of 'salt-and-pepper' noise and mosaic artifacts can be avoided. Conclusions: Since the interview sampling rate is taken into account in the projection domain multiscale decomposition, the proposed method is anticipated to be useful in advanced clinical and preclinical applications where the interview sampling rate varies.« less

An image processing study of a reentrant discotic cholesteric - biaxial cholesteric phase transition

NASA Astrophysics Data System (ADS)

Luders, D. D.; Zoner, G. A.; Santos, O. R.; Braga, W. S.; Sampaio, A. R.; Kimura, N. M.; Palangana, A. J.; Simões, M.

2018-04-01

In this work, we study and characterize the cholesteric sequence of phases (ChDr - ChB - ChD), where the first ChDr is the reentrant cholesteric discotic phase, ChB is the cholesteric biaxial phase and the second ChD is the cholesteric discotic phase. This sequence of phases is studied through polarized light microscopy and image processing technique, where, for the first time, the domains and borders of these transitions are established and characterized. They are also investigated and optically characterized throughout their textures.

IMAGESEER - IMAGEs for Education and Research

NASA Technical Reports Server (NTRS)

Le Moigne, Jacqueline; Grubb, Thomas; Milner, Barbara

2012-01-01

IMAGESEER is a new Web portal that brings easy access to NASA image data for non-NASA researchers, educators, and students. The IMAGESEER Web site and database are specifically designed to be utilized by the university community, to enable teaching image processing (IP) techniques on NASA data, as well as to provide reference benchmark data to validate new IP algorithms. Along with the data and a Web user interface front-end, basic knowledge of the application domains, benchmark information, and specific NASA IP challenges (or case studies) are provided.

Iteration and superposition encryption scheme for image sequences based on multi-dimensional keys

NASA Astrophysics Data System (ADS)

Han, Chao; Shen, Yuzhen; Ma, Wenlin

2017-12-01

An iteration and superposition encryption scheme for image sequences based on multi-dimensional keys is proposed for high security, big capacity and low noise information transmission. Multiple images to be encrypted are transformed into phase-only images with the iterative algorithm and then are encrypted by different random phase, respectively. The encrypted phase-only images are performed by inverse Fourier transform, respectively, thus new object functions are generated. The new functions are located in different blocks and padded zero for a sparse distribution, then they propagate to a specific region at different distances by angular spectrum diffraction, respectively and are superposed in order to form a single image. The single image is multiplied with a random phase in the frequency domain and then the phase part of the frequency spectrums is truncated and the amplitude information is reserved. The random phase, propagation distances, truncated phase information in frequency domain are employed as multiple dimensional keys. The iteration processing and sparse distribution greatly reduce the crosstalk among the multiple encryption images. The superposition of image sequences greatly improves the capacity of encrypted information. Several numerical experiments based on a designed optical system demonstrate that the proposed scheme can enhance encrypted information capacity and make image transmission at a highly desired security level.

Limitations in imaging common conjunctival and corneal pathologies with fourier-domain optical coherence tomography.

PubMed

Demirci, Hakan; Steen, Daniel W

2014-01-01

To describe the limitations of Fourier-domain optical coherence tomography (OCT) in imaging common conjunctival and corneal pathology. Retrospective, single-center case series of 40 patients with conjunctival and cornea pathology. Fourier-domain OCT imaged laser in situ keratomileusis (LASIK) flaps in detail, including its relation to other corneal structures and abnormalities. Similarly, in infectious or degenerative corneal disorders, Fourier-domain OCT successfully showed the extent of infiltration or material deposition, which appeared as hyper-reflective areas. In cases with pterygium, the underlying cornea could not be imaged. All cases of common conjunctival pathologies, such as nevus or pinguecula, were successfully imaged in detail. Nevi, scleritis, pterygium, pinguecula, and subconjunctival hemorrhage were hyper-reflective lesions, while cysts and lymphangiectasia were hyporeflective. The details of the underlying sclera were not uniformly imaged in conjunctival pathologies. Fourier-domain OCT imaged the trabeculectomy bleb in detail, whereas the details of structures of the anterior chamber angle were not routinely visualized in all cases. Light scatter through vascularized, densely inflamed, or thick lesions limits the imaging capabilities of Fourier-domain anterior segment OCT.

Bulk magnetic domain structures visualized by neutron dark-field imaging

NASA Astrophysics Data System (ADS)

Grünzweig, C.; David, C.; Bunk, O.; Dierolf, M.; Frei, G.; Kühne, G.; Schäfer, R.; Pofahl, S.; Rønnow, H. M. R.; Pfeiffer, F.

2008-09-01

We report on how a neutron grating interferometer can yield projection images of the internal domain structure in bulk ferromagnetic samples. The image contrast relies on the ultrasmall angle scattering of unpolarized neutrons at domain wall structures in the specimen. The results show the basic domains of (110)-oriented sheets in an FeSi test sample. The obtained domain structures could be correlated with surface sensitive magneto-optical Kerr effect micrographs.

Distinct self-interaction domains promote Multi Sex Combs accumulation in and formation of the Drosophila histone locus body

PubMed Central

Terzo, Esteban A.; Lyons, Shawn M.; Poulton, John S.; Temple, Brenda R. S.; Marzluff, William F.; Duronio, Robert J.

2015-01-01

Nuclear bodies (NBs) are structures that concentrate proteins, RNAs, and ribonucleoproteins that perform functions essential to gene expression. How NBs assemble is not well understood. We studied the Drosophila histone locus body (HLB), a NB that concentrates factors required for histone mRNA biosynthesis at the replication-dependent histone gene locus. We coupled biochemical analysis with confocal imaging of both fixed and live tissues to demonstrate that the Drosophila Multi Sex Combs (Mxc) protein contains multiple domains necessary for HLB assembly. An important feature of this assembly process is the self-interaction of Mxc via two conserved N-terminal domains: a LisH domain and a novel self-interaction facilitator (SIF) domain immediately downstream of the LisH domain. Molecular modeling suggests that the LisH and SIF domains directly interact, and mutation of either the LisH or the SIF domain severely impairs Mxc function in vivo, resulting in reduced histone mRNA accumulation. A region of Mxc between amino acids 721 and 1481 is also necessary for HLB assembly independent of the LisH and SIF domains. Finally, the C-terminal 195 amino acids of Mxc are required for recruiting FLASH, an essential histone mRNA-processing factor, to the HLB. We conclude that multiple domains of the Mxc protein promote HLB assembly in order to concentrate factors required for histone mRNA biosynthesis. PMID:25694448

Using neural pattern classifiers to quantify the modularity of conflict-control mechanisms in the human brain.

PubMed

Jiang, Jiefeng; Egner, Tobias

2014-07-01

Resolving conflicting sensory and motor representations is a core function of cognitive control, but it remains uncertain to what degree control over different sources of conflict is implemented by shared (domain general) or distinct (domain specific) neural resources. Behavioral data suggest conflict-control to be domain specific, but results from neuroimaging studies have been ambivalent. Here, we employed multivoxel pattern analyses that can decode a brain region's informational content, allowing us to distinguish incidental activation overlap from actual shared information processing. We trained independent sets of "searchlight" classifiers on functional magnetic resonance imaging data to decode control processes associated with stimulus-conflict (Stroop task) and ideomotor-conflict (Simon task). Quantifying the proportion of domain-specific searchlights (capable of decoding only one type of conflict) and domain-general searchlights (capable of decoding both conflict types) in each subject, we found both domain-specific and domain-general searchlights, though the former were more common. When mapping anatomical loci of these searchlights across subjects, neural substrates of stimulus- and ideomotor-specific conflict-control were found to be anatomically consistent across subjects, whereas the substrates of domain-general conflict-control were not. Overall, these findings suggest a hybrid neural architecture of conflict-control that entails both modular (domain specific) and global (domain general) components. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

THz pulsed time-domain imaging of an oil canvas painting: a case study of a painting by Pablo Picasso

NASA Astrophysics Data System (ADS)

Fukunaga, Kaori; Ikari, Tomofumi; Iwai, Kikuko

2016-02-01

The terahertz pulsed time-domain imaging technique and near-infrared observation were applied to investigate an oil painting on canvas by Pablo Picasso. The multilayer structure is clearly observed in cross-sectional image by terahertz pulsed time-domain imaging, and particular Cubism style lines were revealed under newly painted area by near-infrared image.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Leng, Shuai; Yu, Lifeng; Wang, Jia

Purpose: Our purpose was to reduce image noise in spectral CT by exploiting data redundancies in the energy domain to allow flexible selection of the number, width, and location of the energy bins. Methods: Using a variety of spectral CT imaging methods, conventional filtered backprojection (FBP) reconstructions were performed and resulting images were compared to those processed using a Local HighlY constrained backPRojection Reconstruction (HYPR-LR) algorithm. The mean and standard deviation of CT numbers were measured within regions of interest (ROIs), and results were compared between FBP and HYPR-LR. For these comparisons, the following spectral CT imaging methods were used:(i)more » numerical simulations based on a photon-counting, detector-based CT system, (ii) a photon-counting, detector-based micro CT system using rubidium and potassium chloride solutions, (iii) a commercial CT system equipped with integrating detectors utilizing tube potentials of 80, 100, 120, and 140 kV, and (iv) a clinical dual-energy CT examination. The effects of tube energy and energy bin width were evaluated appropriate to each CT system. Results: The mean CT number in each ROI was unchanged between FBP and HYPR-LR images for each of the spectral CT imaging scenarios, irrespective of bin width or tube potential. However, image noise, as represented by the standard deviation of CT numbers in each ROI, was reduced by 36%-76%. In all scenarios, image noise after HYPR-LR algorithm was similar to that of composite images, which used all available photons. No difference in spatial resolution was observed between HYPR-LR processing and FBP. Dual energy patient data processed using HYPR-LR demonstrated reduced noise in the individual, low- and high-energy images, as well as in the material-specific basis images. Conclusions: Noise reduction can be accomplished for spectral CT by exploiting data redundancies in the energy domain. HYPR-LR is a robust method for reducing image noise in a variety of spectral CT imaging systems without losing spatial resolution or CT number accuracy. This method improves the flexibility to select energy bins in the manner that optimizes material identification and separation without paying the penalty of increased image noise or its corollary, increased patient dose.« less

Improving lateral resolution and image quality of optical coherence tomography by the multi-frame superresolution technique for 3D tissue imaging.

PubMed

Shen, Kai; Lu, Hui; Baig, Sarfaraz; Wang, Michael R

2017-11-01

The multi-frame superresolution technique is introduced to significantly improve the lateral resolution and image quality of spectral domain optical coherence tomography (SD-OCT). Using several sets of low resolution C-scan 3D images with lateral sub-spot-spacing shifts on different sets, the multi-frame superresolution processing of these sets at each depth layer reconstructs a higher resolution and quality lateral image. Layer by layer processing yields an overall high lateral resolution and quality 3D image. In theory, the superresolution processing including deconvolution can solve the diffraction limit, lateral scan density and background noise problems together. In experiment, the improved lateral resolution by ~3 times reaching 7.81 µm and 2.19 µm using sample arm optics of 0.015 and 0.05 numerical aperture respectively as well as doubling the image quality has been confirmed by imaging a known resolution test target. Improved lateral resolution on in vitro skin C-scan images has been demonstrated. For in vivo 3D SD-OCT imaging of human skin, fingerprint and retina layer, we used the multi-modal volume registration method to effectively estimate the lateral image shifts among different C-scans due to random minor unintended live body motion. Further processing of these images generated high lateral resolution 3D images as well as high quality B-scan images of these in vivo tissues.

Age-related functional changes in domain-specific medial temporal lobe pathways.

PubMed

Berron, David; Neumann, Katja; Maass, Anne; Schütze, Hartmut; Fliessbach, Klaus; Kiven, Verena; Jessen, Frank; Sauvage, Magdalena; Kumaran, Dharshan; Düzel, Emrah

2018-05-01

There is now converging evidence from studies in animals and humans that the medial temporal lobes (MTLs) harbor anatomically distinct processing pathways for object and scene information. Recent functional magnetic resonance imaging studies in humans suggest that this domain-specific organization may be associated with a functional preference of the anterior-lateral part of the entorhinal cortex (alErC) for objects and the posterior-medial entorhinal cortex (pmErC) for scenes. As MTL subregions are differentially affected by aging and neurodegenerative diseases, the question was raised whether aging may affect the 2 pathways differentially. To address this possibility, we developed a paradigm that allows the investigation of object memory and scene memory in a mnemonic discrimination task. A group of young (n = 43) and healthy older subjects (n = 44) underwent functional magnetic resonance imaging recordings during this novel task, while they were asked to discriminate exact repetitions of object and scene stimuli from novel stimuli that were similar but modified versions of the original stimuli ("lures"). We used structural magnetic resonance images to manually segment anatomical components of the MTL including alErC and pmErC and used these segmented regions to analyze domain specificity of functional activity. Across the entire sample, object processing was associated with activation of the perirhinal cortex (PrC) and alErC, whereas for scene processing, activation was more predominant in the parahippocampal cortex and pmErC. Functional activity related to mnemonic discrimination of object and scene lures from exact repetitions was found to overlap between processing pathways and suggests that while the PrC-alErC pathway was more involved in object discrimination, both pathways were involved in the discrimination of similar scenes. Older adults were behaviorally less accurate than young adults in discriminating similar lures from exact repetitions, but this reduction was equivalent in both domains. However, this was accompanied by significantly reduced domain-specific activity in PrC in older adults compared to what was observed in the young. Furthermore, this reduced domain-specific activity was associated to worse performance in object mnemonic discrimination in older adults. Taken together, we show the fine-grained functional organization of the MTL into domain-specific pathways for objects and scenes and their mnemonic discrimination and further provide evidence that aging might affect these pathways in a differential fashion. Future experiments will elucidate whether the 2 pathways are differentially affected in early stages of Alzheimer's disease in relation to amyloid or tau pathology. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

SPIDER: Next Generation Chip Scale Imaging Sensor Update

NASA Astrophysics Data System (ADS)

Duncan, A.; Kendrick, R.; Ogden, C.; Wuchenich, D.; Thurman, S.; Su, T.; Lai, W.; Chun, J.; Li, S.; Liu, G.; Yoo, S. J. B.

2016-09-01

The Lockheed Martin Advanced Technology Center (LM ATC) and the University of California at Davis (UC Davis) are developing an electro-optical (EO) imaging sensor called SPIDER (Segmented Planar Imaging Detector for Electro-optical Reconnaissance) that seeks to provide a 10x to 100x size, weight, and power (SWaP) reduction alternative to the traditional bulky optical telescope and focal-plane detector array. The substantial reductions in SWaP would reduce cost and/or provide higher resolution by enabling a larger-aperture imager in a constrained volume. Our SPIDER imager replaces the traditional optical telescope and digital focal plane detector array with a densely packed interferometer array based on emerging photonic integrated circuit (PIC) technologies that samples the object being imaged in the Fourier domain (i.e., spatial frequency domain), and then reconstructs an image. Our approach replaces the large optics and structures required by a conventional telescope with PICs that are accommodated by standard lithographic fabrication techniques (e.g., complementary metal-oxide-semiconductor (CMOS) fabrication). The standard EO payload integration and test process that involves precision alignment and test of optical components to form a diffraction limited telescope is, therefore, replaced by in-process integration and test as part of the PIC fabrication, which substantially reduces associated schedule and cost. This paper provides an overview of performance data on the second-generation PIC for SPIDER developed under the Defense Advanced Research Projects Agency (DARPA)'s SPIDER Zoom research funding. We also update the design description of the SPIDER Zoom imaging sensor and the second-generation PIC (high- and low resolution versions).

Novel dental dynamic depth profilometric imaging using simultaneous frequency-domain infrared photothermal radiometry and laser luminescence

NASA Astrophysics Data System (ADS)

Nicolaides, Lena; Mandelis, Andreas

2000-01-01

A high-spatial-resolution dynamic experimental imaging setup, which can provide simultaneous measurements of laser- induced frequency-domain infrared photothermal radiometric and luminescence signals from defects in teeth, has been developed for the first time. The major findings of this work are: (1) radiometric images are complementary to (anticorrelated with) luminescence images, as a result of the nature of the two physical signal generation processes; (2) the radiometric amplitude exhibits much superior dynamic (signal resolution) range to luminescence in distinguishing between intact and cracked sub-surface structures in the enamel; (3) the radiometric signal (amplitude and phase) produces dental images with much better defect localization, delineation, and resolution; (4) radiometric images (amplitude and phase) at a fixed modulation frequency are depth profilometric, whereas luminescence images are not; and (5) luminescence frequency responses from enamel and hydroxyapatite exhibit two relaxation lifetimes, the longer of which (approximately ms) is common to all and is not sensitive to the defect state and overall quality of the enamel. Simultaneous radiometric and luminescence frequency scans for the purpose of depth profiling were performed and a quantitative theoretical two-lifetime rate model of dental luminescence was advanced.

Radon-domain interferometric interpolation for reconstruction of the near-offset gap in marine seismic data

NASA Astrophysics Data System (ADS)

Xu, Zhuo; Sopher, Daniel; Juhlin, Christopher; Han, Liguo; Gong, Xiangbo

2018-04-01

In towed marine seismic data acquisition, a gap between the source and the nearest recording channel is typical. Therefore, extrapolation of the missing near-offset traces is often required to avoid unwanted effects in subsequent data processing steps. However, most existing interpolation methods perform poorly when extrapolating traces. Interferometric interpolation methods are one particular method that have been developed for filling in trace gaps in shot gathers. Interferometry-type interpolation methods differ from conventional interpolation methods as they utilize information from several adjacent shot records to fill in the missing traces. In this study, we aim to improve upon the results generated by conventional time-space domain interferometric interpolation by performing interferometric interpolation in the Radon domain, in order to overcome the effects of irregular data sampling and limited source-receiver aperture. We apply both time-space and Radon-domain interferometric interpolation methods to the Sigsbee2B synthetic dataset and a real towed marine dataset from the Baltic Sea with the primary aim to improve the image of the seabed through extrapolation into the near-offset gap. Radon-domain interferometric interpolation performs better at interpolating the missing near-offset traces than conventional interferometric interpolation when applied to data with irregular geometry and limited source-receiver aperture. We also compare the interferometric interpolated results with those obtained using solely Radon transform (RT) based interpolation and show that interferometry-type interpolation performs better than solely RT-based interpolation when extrapolating the missing near-offset traces. After data processing, we show that the image of the seabed is improved by performing interferometry-type interpolation, especially when Radon-domain interferometric interpolation is applied.

Wake acoustic analysis and image decomposition via beamforming of microphone signal projections on wavelet subspaces

DOT National Transportation Integrated Search

2006-05-08

This paper describes the integration of wavelet analysis and time-domain beamforming : of microphone array output signals for analyzing the acoustic emissions from airplane : generated wake vortices. This integrated process provides visual and quanti...

Imaging the equilibrium state and magnetization dynamics of partially built hard disk write heads

DOE Office of Scientific and Technical Information (OSTI.GOV)

Valkass, R. A. J., E-mail: rajv202@ex.ac.uk; Yu, W.; Shelford, L. R.

Four different designs of partially built hard disk write heads with a yoke comprising four repeats of NiFe (1 nm)/CoFe (50 nm) were studied by both x-ray photoemission electron microscopy (XPEEM) and time-resolved scanning Kerr microscopy (TRSKM). These techniques were used to investigate the static equilibrium domain configuration and the magnetodynamic response across the entire structure, respectively. Simulations and previous TRSKM studies have made proposals for the equilibrium domain configuration of similar structures, but no direct observation of the equilibrium state of the writers has yet been made. In this study, static XPEEM images of the equilibrium state of writer structures weremore » acquired using x-ray magnetic circular dichroism as the contrast mechanism. These images suggest that the crystalline anisotropy dominates the equilibrium state domain configuration, but competition with shape anisotropy ultimately determines the stability of the equilibrium state. Dynamic TRSKM images were acquired from nominally identical devices. These images suggest that a longer confluence region may hinder flux conduction from the yoke into the pole tip: the shorter confluence region exhibits clear flux beaming along the symmetry axis, whereas the longer confluence region causes flux to conduct along one edge of the writer. The observed variations in dynamic response agree well with the differences in the equilibrium magnetization configuration visible in the XPEEM images, confirming that minor variations in the geometric design of the writer structure can have significant effects on the process of flux beaming.« less

Fourier Domain Iterative Approach to Optical Sectioning of 3d Translucent Objects for Ophthalmology Purposes

NASA Astrophysics Data System (ADS)

Razguli, A. V.; Iroshnikov, N. G.; Larichev, A. V.; Romanenko, T. E.; Goncharov, A. S.

2017-05-01

In this paper we deal with the problem of optical sectioning. This is a post processing step while investigating of 3D translucent medical objects based on rapid refocusing of the imaging system by the adaptive optics technique. Each image, captured in focal plane, can be represented as the sum of in-focus true section and out-of-focus images of the neighboring sections of the depth that are undesirable in the subsequent reconstruction of 3D object. The problem of optical sectioning under consideration is to elaborate a robust approach capable of obtaining a stack of cross section images purified from such distortions. For a typical sectioning statement arising in ophthalmology we propose a local iterative method in Fourier spectral plane. Compared to the non-local constant parameter selection for the whole spectral domain, the method demonstrates both improved sectioning results and a good level of scalability when implemented on multi-core CPUs.

A Bayesian generative model for learning semantic hierarchies

PubMed Central

Mittelman, Roni; Sun, Min; Kuipers, Benjamin; Savarese, Silvio

2014-01-01

Building fine-grained visual recognition systems that are capable of recognizing tens of thousands of categories, has received much attention in recent years. The well known semantic hierarchical structure of categories and concepts, has been shown to provide a key prior which allows for optimal predictions. The hierarchical organization of various domains and concepts has been subject to extensive research, and led to the development of the WordNet domains hierarchy (Fellbaum, 1998), which was also used to organize the images in the ImageNet (Deng et al., 2009) dataset, in which the category count approaches the human capacity. Still, for the human visual system, the form of the hierarchy must be discovered with minimal use of supervision or innate knowledge. In this work, we propose a new Bayesian generative model for learning such domain hierarchies, based on semantic input. Our model is motivated by the super-subordinate organization of domain labels and concepts that characterizes WordNet, and accounts for several important challenges: maintaining context information when progressing deeper into the hierarchy, learning a coherent semantic concept for each node, and modeling uncertainty in the perception process. PMID:24904452

Time-Correlated Single-Photon Counting Fluorescence Imaging of Lipid Domains In Raft-Mimicking Giant Unilamellar Vesicles

NASA Astrophysics Data System (ADS)

Clarke, James; Cheng, Kwan; Shindell, Orrin; Wang, Exing

We have designed and constructed a high-throughput electrofusion chamber and an incubator to fabricate Giant Unilamellar Vesicles (GUVs) consisting of high-melting lipids, low-melting lipids, cholesterol and both ordered and disordered phase sensitive fluorescent probes (DiIC12, dehydroergosterol and BODIPY-Cholesterol). GUVs were formed in a 3 stage pulse sequence electrofusion process with voltages ranging from 50mVpp to 2.2Vpp and frequencies from 5Hz to 10Hz. Steady state and time-correlated single-photon counting (TCSPC) fluorescence lifetime (FLIM) based confocal and/or multi-photon microscopic techniques were used to characterize phase separated lipid domains in GUVs. Confocal imaging measures the probe concentration and the chemical environment of the system. TCSPC techniques determine the chemical environment through the perturbation of fluorescent lifetimes of the probes in the system. The above techniques will be applied to investigate the protein-lipid interactions involving domain formation. Specifically, the mechanisms governing lipid domain formations in the above systems that mimic the lipid rafts in cells will be explored. Murchison Fellowship at Trinity University.

Integrating NASA's Land Analysis System (LAS) image processing software with an appropriate Geographic Information System (GIS): A review of candidates in the public domain

NASA Technical Reports Server (NTRS)

Rochon, Gilbert L.

1989-01-01

A user requirements analysis (URA) was undertaken to determine and appropriate public domain Geographic Information System (GIS) software package for potential integration with NASA's LAS (Land Analysis System) 5.0 image processing system. The necessity for a public domain system was underscored due to the perceived need for source code access and flexibility in tailoring the GIS system to the needs of a heterogenous group of end-users, and to specific constraints imposed by LAS and its user interface, Transportable Applications Executive (TAE). Subsequently, a review was conducted of a variety of public domain GIS candidates, including GRASS 3.0, MOSS, IEMIS, and two university-based packages, IDRISI and KBGIS. The review method was a modified version of the GIS evaluation process, development by the Federal Interagency Coordinating Committee on Digital Cartography. One IEMIS-derivative product, the ALBE (AirLand Battlefield Environment) GIS, emerged as the most promising candidate for integration with LAS. IEMIS (Integrated Emergency Management Information System) was developed by the Federal Emergency Management Agency (FEMA). ALBE GIS is currently under development at the Pacific Northwest Laboratory under contract with the U.S. Army Corps of Engineers' Engineering Topographic Laboratory (ETL). Accordingly, recommendations are offered with respect to a potential LAS/ALBE GIS linkage and with respect to further system enhancements, including coordination with the development of the Spatial Analysis and Modeling System (SAMS) GIS in Goddard's IDM (Intelligent Data Management) developments in Goddard's National Space Science Data Center.

Digital image processing for information extraction.

NASA Technical Reports Server (NTRS)

Billingsley, F. C.

1973-01-01

The modern digital computer has made practical image processing techniques for handling nonlinear operations in both the geometrical and the intensity domains, various types of nonuniform noise cleanup, and the numerical analysis of pictures. An initial requirement is that a number of anomalies caused by the camera (e.g., geometric distortion, MTF roll-off, vignetting, and nonuniform intensity response) must be taken into account or removed to avoid their interference with the information extraction process. Examples illustrating these operations are discussed along with computer techniques used to emphasize details, perform analyses, classify materials by multivariate analysis, detect temporal differences, and aid in human interpretation of photos.

Rotation covariant image processing for biomedical applications.

PubMed

Skibbe, Henrik; Reisert, Marco

2013-01-01

With the advent of novel biomedical 3D image acquisition techniques, the efficient and reliable analysis of volumetric images has become more and more important. The amount of data is enormous and demands an automated processing. The applications are manifold, ranging from image enhancement, image reconstruction, and image description to object/feature detection and high-level contextual feature extraction. In most scenarios, it is expected that geometric transformations alter the output in a mathematically well-defined manner. In this paper we emphasis on 3D translations and rotations. Many algorithms rely on intensity or low-order tensorial-like descriptions to fulfill this demand. This paper proposes a general mathematical framework based on mathematical concepts and theories transferred from mathematical physics and harmonic analysis into the domain of image analysis and pattern recognition. Based on two basic operations, spherical tensor differentiation and spherical tensor multiplication, we show how to design a variety of 3D image processing methods in an efficient way. The framework has already been applied to several biomedical applications ranging from feature and object detection tasks to image enhancement and image restoration techniques. In this paper, the proposed methods are applied on a variety of different 3D data modalities stemming from medical and biological sciences.

An end to end secure CBIR over encrypted medical database.

PubMed

Bellafqira, Reda; Coatrieux, Gouenou; Bouslimi, Dalel; Quellec, Gwenole

2016-08-01

In this paper, we propose a new secure content based image retrieval (SCBIR) system adapted to the cloud framework. This solution allows a physician to retrieve images of similar content within an outsourced and encrypted image database, without decrypting them. Contrarily to actual CBIR approaches in the encrypted domain, the originality of the proposed scheme stands on the fact that the features extracted from the encrypted images are themselves encrypted. This is achieved by means of homomorphic encryption and two non-colluding servers, we however both consider as honest but curious. In that way an end to end secure CBIR process is ensured. Experimental results carried out on a diabetic retinopathy database encrypted with the Paillier cryptosystem indicate that our SCBIR achieves retrieval performance as good as if images were processed in their non-encrypted form.

Single-scale center-surround Retinex based restoration of low-illumination images with edge enhancement

NASA Astrophysics Data System (ADS)

Kwok, Ngaiming; Shi, Haiyan; Peng, Yeping; Wu, Hongkun; Li, Ruowei; Liu, Shilong; Rahman, Md Arifur

2018-04-01

Restoring images captured under low-illuminations is an essential front-end process for most image based applications. The Center-Surround Retinex algorithm has been a popular approach employed to improve image brightness. However, this algorithm in its basic form, is known to produce color degradations. In order to mitigate this problem, here the Single-Scale Retinex algorithm is modifid as an edge extractor while illumination is recovered through a non-linear intensity mapping stage. The derived edges are then integrated with the mapped image to produce the enhanced output. Furthermore, in reducing color distortion, the process is conducted in the magnitude sorted domain instead of the conventional Red-Green-Blue (RGB) color channels. Experimental results had shown that improvements with regard to mean brightness, colorfulness, saturation, and information content can be obtained.

Sparsity-based multi-height phase recovery in holographic microscopy

NASA Astrophysics Data System (ADS)

Rivenson, Yair; Wu, Yichen; Wang, Hongda; Zhang, Yibo; Feizi, Alborz; Ozcan, Aydogan

2016-11-01

High-resolution imaging of densely connected samples such as pathology slides using digital in-line holographic microscopy requires the acquisition of several holograms, e.g., at >6-8 different sample-to-sensor distances, to achieve robust phase recovery and coherent imaging of specimen. Reducing the number of these holographic measurements would normally result in reconstruction artifacts and loss of image quality, which would be detrimental especially for biomedical and diagnostics-related applications. Inspired by the fact that most natural images are sparse in some domain, here we introduce a sparsity-based phase reconstruction technique implemented in wavelet domain to achieve at least 2-fold reduction in the number of holographic measurements for coherent imaging of densely connected samples with minimal impact on the reconstructed image quality, quantified using a structural similarity index. We demonstrated the success of this approach by imaging Papanicolaou smears and breast cancer tissue slides over a large field-of-view of ~20 mm2 using 2 in-line holograms that are acquired at different sample-to-sensor distances and processed using sparsity-based multi-height phase recovery. This new phase recovery approach that makes use of sparsity can also be extended to other coherent imaging schemes, involving e.g., multiple illumination angles or wavelengths to increase the throughput and speed of coherent imaging.

Time domain SAR raw data simulation using CST and image focusing of 3D objects

NASA Astrophysics Data System (ADS)

Saeed, Adnan; Hellwich, Olaf

2017-10-01

This paper presents the use of a general purpose electromagnetic simulator, CST, to simulate realistic synthetic aperture radar (SAR) raw data of three-dimensional objects. Raw data is later focused in MATLAB using range-doppler algorithm. Within CST Microwave Studio a replica of TerraSAR-X chirp signal is incident upon a modeled Corner Reflector (CR) whose design and material properties are identical to that of the real one. Defining mesh and other appropriate settings reflected wave is measured at several distant points within a line parallel to the viewing direction. This is analogous to an array antenna and is synthesized to create a long aperture for SAR processing. The time domain solver in CST is based on the solution of differential form of Maxwells equations. Exported data from CST is arranged into a 2-d matrix of axis range and azimuth. Hilbert transform is applied to convert the real signal to complex data with phase information. Range compression, range cell migration correction (RCMC), and azimuth compression are applied in time domain to obtain the final SAR image. This simulation can provide valuable information to clarify which real world objects cause images suitable for high accuracy identification in the SAR images.

An iterative sinogram gap-filling method with object- and scanner-dedicated discrete cosine transform (DCT)-domain filters for high resolution PET scanners.

PubMed

Kim, Kwangdon; Lee, Kisung; Lee, Hakjae; Joo, Sungkwan; Kang, Jungwon

2018-01-01

We aimed to develop a gap-filling algorithm, in particular the filter mask design method of the algorithm, which optimizes the filter to the imaging object by an adaptive and iterative process, rather than by manual means. Two numerical phantoms (Shepp-Logan and Jaszczak) were used for sinogram generation. The algorithm works iteratively, not only on the gap-filling iteration but also on the mask generation, to identify the object-dedicated low frequency area in the DCT-domain that is to be preserved. We redefine the low frequency preserving region of the filter mask at every gap-filling iteration, and the region verges on the property of the original image in the DCT domain. The previous DCT2 mask for each phantom case had been manually well optimized, and the results show little difference from the reference image and sinogram. We observed little or no difference between the results of the manually optimized DCT2 algorithm and those of the proposed algorithm. The proposed algorithm works well for various types of scanning object and shows results that compare to those of the manually optimized DCT2 algorithm without perfect or full information of the imaging object.

[Method of correcting sensitivity nonuniformity using gaussian distribution on 3.0 Tesla abdominal MRI].

PubMed

Hayashi, Norio; Miyati, Tosiaki; Takanaga, Masako; Ohno, Naoki; Hamaguchi, Takashi; Kozaka, Kazuto; Sanada, Shigeru; Yamamoto, Tomoyuki; Matsui, Osamu

2011-01-01

In the direction where the phased array coil used in parallel magnetic resonance imaging (MRI) is perpendicular to the arrangement, sensitivity falls significantly. Moreover, in a 3.0 tesla (3T) abdominal MRI, the quality of the image is reduced by changes in the relaxation time, reinforcement of the magnetic susceptibility effect, etc. In a 3T MRI, which has a high resonant frequency, the signal of the depths (central part) is reduced in the trunk part. SCIC, which is sensitivity correction processing, has inadequate correction processing, such as that edges are emphasized and the central part is corrected. Therefore, we used 3T with a Gaussian distribution. The uneven compensation processing for sensitivity of an abdomen MR image was considered. The correction processing consisted of the following methods. 1) The center of gravity of the domain of the human body in an abdomen MR image was calculated. 2) The correction coefficient map was created from the center of gravity using the Gaussian distribution. 3) The sensitivity correction image was created from the correction coefficient map and the original picture image. Using the Gaussian correction to process the image, the uniformity calculated using the NEMA method was improved significantly compared to the original image of a phantom. In a visual evaluation by radiologists, the uniformity was improved significantly using the Gaussian correction processing. Because of the homogeneous improvement of the abdomen image taken using 3T MRI, the Gaussian correction processing is considered to be a very useful technique.

Real-time algorithm for acoustic imaging with a microphone array.

PubMed

Huang, Xun

2009-05-01

Acoustic phased array has become an important testing tool in aeroacoustic research, where the conventional beamforming algorithm has been adopted as a classical processing technique. The computation however has to be performed off-line due to the expensive cost. An innovative algorithm with real-time capability is proposed in this work. The algorithm is similar to a classical observer in the time domain while extended for the array processing to the frequency domain. The observer-based algorithm is beneficial mainly for its capability of operating over sampling blocks recursively. The expensive experimental time can therefore be reduced extensively since any defect in a testing can be corrected instantaneously.

MToS: A Tree of Shapes for Multivariate Images.

PubMed

Carlinet, Edwin; Géraud, Thierry

2015-12-01

The topographic map of a gray-level image, also called tree of shapes, provides a high-level hierarchical representation of the image contents. This representation, invariant to contrast changes and to contrast inversion, has been proved very useful to achieve many image processing and pattern recognition tasks. Its definition relies on the total ordering of pixel values, so this representation does not exist for color images, or more generally, multivariate images. Common workarounds, such as marginal processing, or imposing a total order on data, are not satisfactory and yield many problems. This paper presents a method to build a tree-based representation of multivariate images, which features marginally the same properties of the gray-level tree of shapes. Briefly put, we do not impose an arbitrary ordering on values, but we only rely on the inclusion relationship between shapes in the image definition domain. The interest of having a contrast invariant and self-dual representation of multivariate image is illustrated through several applications (filtering, segmentation, and object recognition) on different types of data: color natural images, document images, satellite hyperspectral imaging, multimodal medical imaging, and videos.

Self-Organization of Spatio-Temporal Hierarchy via Learning of Dynamic Visual Image Patterns on Action Sequences

PubMed Central

Jung, Minju; Hwang, Jungsik; Tani, Jun

2015-01-01

It is well known that the visual cortex efficiently processes high-dimensional spatial information by using a hierarchical structure. Recently, computational models that were inspired by the spatial hierarchy of the visual cortex have shown remarkable performance in image recognition. Up to now, however, most biological and computational modeling studies have mainly focused on the spatial domain and do not discuss temporal domain processing of the visual cortex. Several studies on the visual cortex and other brain areas associated with motor control support that the brain also uses its hierarchical structure as a processing mechanism for temporal information. Based on the success of previous computational models using spatial hierarchy and temporal hierarchy observed in the brain, the current report introduces a novel neural network model for the recognition of dynamic visual image patterns based solely on the learning of exemplars. This model is characterized by the application of both spatial and temporal constraints on local neural activities, resulting in the self-organization of a spatio-temporal hierarchy necessary for the recognition of complex dynamic visual image patterns. The evaluation with the Weizmann dataset in recognition of a set of prototypical human movement patterns showed that the proposed model is significantly robust in recognizing dynamically occluded visual patterns compared to other baseline models. Furthermore, an evaluation test for the recognition of concatenated sequences of those prototypical movement patterns indicated that the model is endowed with a remarkable capability for the contextual recognition of long-range dynamic visual image patterns. PMID:26147887

Self-Organization of Spatio-Temporal Hierarchy via Learning of Dynamic Visual Image Patterns on Action Sequences.

PubMed

Jung, Minju; Hwang, Jungsik; Tani, Jun

2015-01-01

It is well known that the visual cortex efficiently processes high-dimensional spatial information by using a hierarchical structure. Recently, computational models that were inspired by the spatial hierarchy of the visual cortex have shown remarkable performance in image recognition. Up to now, however, most biological and computational modeling studies have mainly focused on the spatial domain and do not discuss temporal domain processing of the visual cortex. Several studies on the visual cortex and other brain areas associated with motor control support that the brain also uses its hierarchical structure as a processing mechanism for temporal information. Based on the success of previous computational models using spatial hierarchy and temporal hierarchy observed in the brain, the current report introduces a novel neural network model for the recognition of dynamic visual image patterns based solely on the learning of exemplars. This model is characterized by the application of both spatial and temporal constraints on local neural activities, resulting in the self-organization of a spatio-temporal hierarchy necessary for the recognition of complex dynamic visual image patterns. The evaluation with the Weizmann dataset in recognition of a set of prototypical human movement patterns showed that the proposed model is significantly robust in recognizing dynamically occluded visual patterns compared to other baseline models. Furthermore, an evaluation test for the recognition of concatenated sequences of those prototypical movement patterns indicated that the model is endowed with a remarkable capability for the contextual recognition of long-range dynamic visual image patterns.

Information theoretical assessment of visual communication with subband coding

NASA Astrophysics Data System (ADS)

Rahman, Zia-ur; Fales, Carl L.; Huck, Friedrich O.

1994-09-01

A well-designed visual communication channel is one which transmits the most information about a radiance field with the fewest artifacts. The role of image processing, encoding and restoration is to improve the quality of visual communication channels by minimizing the error in the transmitted data. Conventionally this role has been analyzed strictly in the digital domain neglecting the effects of image-gathering and image-display devices on the quality of the image. This results in the design of a visual communication channel which is `suboptimal.' We propose an end-to-end assessment of the imaging process which incorporates the influences of these devices in the design of the encoder and the restoration process. This assessment combines Shannon's communication theory with Wiener's restoration filter and with the critical design factors of the image gathering and display devices, thus providing the metrics needed to quantify and optimize the end-to-end performance of the visual communication channel. Results show that the design of the image-gathering device plays a significant role in determining the quality of the visual communication channel and in designing the analysis filters for subband encoding.

A Web application for the management of clinical workflow in image-guided and adaptive proton therapy for prostate cancer treatments.

PubMed

Yeung, Daniel; Boes, Peter; Ho, Meng Wei; Li, Zuofeng

2015-05-08

Image-guided radiotherapy (IGRT), based on radiopaque markers placed in the prostate gland, was used for proton therapy of prostate patients. Orthogonal X-rays and the IBA Digital Image Positioning System (DIPS) were used for setup correction prior to treatment and were repeated after treatment delivery. Following a rationale for margin estimates similar to that of van Herk,(1) the daily post-treatment DIPS data were analyzed to determine if an adaptive radiotherapy plan was necessary. A Web application using ASP.NET MVC5, Entity Framework, and an SQL database was designed to automate this process. The designed features included state-of-the-art Web technologies, a domain model closely matching the workflow, a database-supporting concurrency and data mining, access to the DIPS database, secured user access and roles management, and graphing and analysis tools. The Model-View-Controller (MVC) paradigm allowed clean domain logic, unit testing, and extensibility. Client-side technologies, such as jQuery, jQuery Plug-ins, and Ajax, were adopted to achieve a rich user environment and fast response. Data models included patients, staff, treatment fields and records, correction vectors, DIPS images, and association logics. Data entry, analysis, workflow logics, and notifications were implemented. The system effectively modeled the clinical workflow and IGRT process.

BreakingNews: Article Annotation by Image and Text Processing.

PubMed

Ramisa, Arnau; Yan, Fei; Moreno-Noguer, Francesc; Mikolajczyk, Krystian

2018-05-01

Building upon recent Deep Neural Network architectures, current approaches lying in the intersection of Computer Vision and Natural Language Processing have achieved unprecedented breakthroughs in tasks like automatic captioning or image retrieval. Most of these learning methods, though, rely on large training sets of images associated with human annotations that specifically describe the visual content. In this paper we propose to go a step further and explore the more complex cases where textual descriptions are loosely related to the images. We focus on the particular domain of news articles in which the textual content often expresses connotative and ambiguous relations that are only suggested but not directly inferred from images. We introduce an adaptive CNN architecture that shares most of the structure for multiple tasks including source detection, article illustration and geolocation of articles. Deep Canonical Correlation Analysis is deployed for article illustration, and a new loss function based on Great Circle Distance is proposed for geolocation. Furthermore, we present BreakingNews, a novel dataset with approximately 100K news articles including images, text and captions, and enriched with heterogeneous meta-data (such as GPS coordinates and user comments). We show this dataset to be appropriate to explore all aforementioned problems, for which we provide a baseline performance using various Deep Learning architectures, and different representations of the textual and visual features. We report very promising results and bring to light several limitations of current state-of-the-art in this kind of domain, which we hope will help spur progress in the field.

SNR enhancement for catheter based intravascular photoacoustic/ultrasound imaging

NASA Astrophysics Data System (ADS)

Cho, Seonghee; Choi, Changhoon; Ahn, Joongho; Kim, Taehoon; Park, Sungjo; Park, Hyoeun; Kim, Jinmoo; Lee, Seunghoon; Kang, Yeonsu; Chang, Kiyuk; Kim, Yongmin; Kim, Chulhong

2017-03-01

Atherosclerosis, the most common cause of death, kills suddenly by arterial occlusion by thrombosis, which is caused by plaque rupture. Because a growing necrotic core is highly related to plaque rupture in atherosclerosis, distinguishing between fibrous plaque and lipid-rich plaque in real time is important, but has been challenging. Real-time photoacoustic imaging requires a pulse laser with high repetition rate, which tends to sacrifice pulse energy. Furthermore, a high repetition rate is hard to achieve at lipid-sensitive wavelengths, such as 1210 nm and 1720 nm. To address the unmet need, we have developed the algorithm for PA imaging. We successfully acquired ex vivo PA images from the lipid cores of arterial plaques in rabbit arteries, using a low-power 1064-nm laser. PA images were acquired with a custom-made catheter employing a single-element 40-MHz ultrasound transducer and a compact 1064-nm laser with the pulse energy of 5 μJ and the repetition rate of 24 kHz. Acquired raw data were processed in the time and frequency domains. In the time domain, a delay-and-sum algorithm was used for image enhancement. In the frequency domain, signals exceeding the MTF were removed. As a result, SNR was increased by about 10 dB without degrading spatial resolution. We were able to achieve high-speed and high-SNR lipid target imaging in animals in spite of the low lipid sensitivity of a 1064nm laser. These results show good promise for detecting lipid-rich plaques with a compact high-speed laser, which can be easily adapted for target clinical applications.

Vortex Ring Dynamics in Radially Confined Domains

NASA Astrophysics Data System (ADS)

Stewart, Kelley; Niebel, Casandra; Jung, Sunghwan; Vlachos, Pavlos

2010-11-01

Vortex ring dynamics have been studied extensively in semi-infinite quiescent volumes. However, very little is known about vortex-ring formation in wall-bounded domains where vortex wall interaction will affect both the vortex ring pinch-off and propagation velocity. This study addresses this limitation and studies vortex formation in radially confined domains to analyze the affect of vortex-ring wall interaction on the formation and propagation of the vortex ring. Vortex rings were produced using a pneumatically driven piston cylinder arrangement and were ejected into a long cylindrical tube which defined the confined downstream domain. A range of confinement domains were studied with varying confinement diameters Velocity field measurements were performed using planar Time Resolved Digital Particle Image Velocimetry (TRDPIV) and were processed using an in-house developed cross-correlation PIV algorithm. The experimental analysis was used to facilitate the development of a theoretical model to predict the variations in vortex ring circulation over time within confined domains.

Deep learning methods to guide CT image reconstruction and reduce metal artifacts

NASA Astrophysics Data System (ADS)

Gjesteby, Lars; Yang, Qingsong; Xi, Yan; Zhou, Ye; Zhang, Junping; Wang, Ge

2017-03-01

The rapidly-rising field of machine learning, including deep learning, has inspired applications across many disciplines. In medical imaging, deep learning has been primarily used for image processing and analysis. In this paper, we integrate a convolutional neural network (CNN) into the computed tomography (CT) image reconstruction process. Our first task is to monitor the quality of CT images during iterative reconstruction and decide when to stop the process according to an intelligent numerical observer instead of using a traditional stopping rule, such as a fixed error threshold or a maximum number of iterations. After training on ground truth images, the CNN was successful in guiding an iterative reconstruction process to yield high-quality images. Our second task is to improve a sinogram to correct for artifacts caused by metal objects. A large number of interpolation and normalization-based schemes were introduced for metal artifact reduction (MAR) over the past four decades. The NMAR algorithm is considered a state-of-the-art method, although residual errors often remain in the reconstructed images, especially in cases of multiple metal objects. Here we merge NMAR with deep learning in the projection domain to achieve additional correction in critical image regions. Our results indicate that deep learning can be a viable tool to address CT reconstruction challenges.

Acousto-optic time- and space-integrating spotlight-mode SAR processor

NASA Astrophysics Data System (ADS)

Haney, Michael W.; Levy, James J.; Michael, Robert R., Jr.

1993-09-01

The technical approach and recent experimental results for the acousto-optic time- and space- integrating real-time SAR image formation processor program are reported. The concept overcomes the size and power consumption limitations of electronic approaches by using compact, rugged, and low-power analog optical signal processing techniques for the most computationally taxing portions of the SAR imaging problem. Flexibility and performance are maintained by the use of digital electronics for the critical low-complexity filter generation and output image processing functions. The results include a demonstration of the processor's ability to perform high-resolution spotlight-mode SAR imaging by simultaneously compensating for range migration and range/azimuth coupling in the analog optical domain, thereby avoiding a highly power-consuming digital interpolation or reformatting operation usually required in all-electronic approaches.

Research Issues in Image Registration for Remote Sensing

NASA Technical Reports Server (NTRS)

Eastman, Roger D.; LeMoigne, Jacqueline; Netanyahu, Nathan S.

2007-01-01

Image registration is an important element in data processing for remote sensing with many applications and a wide range of solutions. Despite considerable investigation the field has not settled on a definitive solution for most applications and a number of questions remain open. This article looks at selected research issues by surveying the experience of operational satellite teams, application-specific requirements for Earth science, and our experiments in the evaluation of image registration algorithms with emphasis on the comparison of algorithms for subpixel accuracy. We conclude that remote sensing applications put particular demands on image registration algorithms to take into account domain-specific knowledge of geometric transformations and image content.

RADIANCE AND PHOTON NOISE: Imaging in geometrical optics, physical optics, quantum optics and radiology.

PubMed

Barrett, Harrison H; Myers, Kyle J; Caucci, Luca

2014-08-17

A fundamental way of describing a photon-limited imaging system is in terms of a Poisson random process in spatial, angular and wavelength variables. The mean of this random process is the spectral radiance. The principle of conservation of radiance then allows a full characterization of the noise in the image (conditional on viewing a specified object). To elucidate these connections, we first review the definitions and basic properties of radiance as defined in terms of geometrical optics, radiology, physical optics and quantum optics. The propagation and conservation laws for radiance in each of these domains are reviewed. Then we distinguish four categories of imaging detectors that all respond in some way to the incident radiance, including the new category of photon-processing detectors. The relation between the radiance and the statistical properties of the detector output is discussed and related to task-based measures of image quality and the information content of a single detected photon.

RADIANCE AND PHOTON NOISE: Imaging in geometrical optics, physical optics, quantum optics and radiology

PubMed Central

Barrett, Harrison H.; Myers, Kyle J.; Caucci, Luca

2016-01-01

A fundamental way of describing a photon-limited imaging system is in terms of a Poisson random process in spatial, angular and wavelength variables. The mean of this random process is the spectral radiance. The principle of conservation of radiance then allows a full characterization of the noise in the image (conditional on viewing a specified object). To elucidate these connections, we first review the definitions and basic properties of radiance as defined in terms of geometrical optics, radiology, physical optics and quantum optics. The propagation and conservation laws for radiance in each of these domains are reviewed. Then we distinguish four categories of imaging detectors that all respond in some way to the incident radiance, including the new category of photon-processing detectors. The relation between the radiance and the statistical properties of the detector output is discussed and related to task-based measures of image quality and the information content of a single detected photon. PMID:27478293

Formal Foundations for the Specification of Software Architecture.

DTIC Science & Technology

1995-03-01

Architectures For- mally: A Case-Study Using KWIC." Kestrel Institute, Palo Alto, CA 94304, April 1994. 58. Kang, Kyo C. Feature-Oriented Domain Analysis ( FODA ...6.3.5 Constraint-Based Architectures ................. 6-60 6.4 Summary ......... ............................. 6-63 VII. Analysis of Process-Based...between these architec- ture theories were investigated. A feasibility analysis on an image processing application demonstrated that architecture theories

Analog signal processing for optical coherence imaging systems

NASA Astrophysics Data System (ADS)

Xu, Wei

Optical coherence tomography (OCT) and optical coherence microscopy (OCM) are non-invasive optical coherence imaging techniques, which enable micron-scale resolution, depth resolved imaging capability. Both OCT and OCM are based on Michelson interferometer theory. They are widely used in ophthalmology, gastroenterology and dermatology, because of their high resolution, safety and low cost. OCT creates cross sectional images whereas OCM obtains en face images. In this dissertation, the design and development of three increasingly complicated analog signal processing (ASP) solutions for optical coherence imaging are presented. The first ASP solution was implemented for a time domain OCT system with a Rapid Scanning Optical Delay line (RSOD)-based optical signal modulation and logarithmic amplifier (Log amp) based demodulation. This OCT system can acquire up to 1600 A-scans per second. The measured dynamic range is 106dB at 200A-scan per second. This OCT signal processing electronics includes an off-the-shelf filter box with a Log amp circuit implemented on a PCB board. The second ASP solution was developed for an OCM system with synchronized modulation and demodulation and compensation for interferometer phase drift. This OCM acquired micron-scale resolution, high dynamic range images at acquisition speeds up to 45,000 pixels/second. This OCM ASP solution is fully custom designed on a perforated circuit board. The third ASP solution was implemented on a single 2.2 mm x 2.2 mm complementary metal oxide semiconductor (CMOS) chip. This design is expandable to a multiple channel OCT system. A single on-chip CMOS photodetector and ASP channel was used for coherent demodulation in a time domain OCT system. Cross-sectional images were acquired with a dynamic range of 76dB (limited by photodetector responsivity). When incorporated with a bump-bonded InGaAs photodiode with higher responsivity, the expected dynamic range is close to 100dB.

High-order statistics of weber local descriptors for image representation.

PubMed

Han, Xian-Hua; Chen, Yen-Wei; Xu, Gang

2015-06-01

Highly discriminant visual features play a key role in different image classification applications. This study aims to realize a method for extracting highly-discriminant features from images by exploring a robust local descriptor inspired by Weber's law. The investigated local descriptor is based on the fact that human perception for distinguishing a pattern depends not only on the absolute intensity of the stimulus but also on the relative variance of the stimulus. Therefore, we firstly transform the original stimulus (the images in our study) into a differential excitation-domain according to Weber's law, and then explore a local patch, called micro-Texton, in the transformed domain as Weber local descriptor (WLD). Furthermore, we propose to employ a parametric probability process to model the Weber local descriptors, and extract the higher-order statistics to the model parameters for image representation. The proposed strategy can adaptively characterize the WLD space using generative probability model, and then learn the parameters for better fitting the training space, which would lead to more discriminant representation for images. In order to validate the efficiency of the proposed strategy, we apply three different image classification applications including texture, food images and HEp-2 cell pattern recognition, which validates that our proposed strategy has advantages over the state-of-the-art approaches.

Evaluation of dispersivity coefficients by means of a laboratory image analysis.

PubMed

Citarella, Donato; Cupola, Fausto; Tanda, Maria Giovanna; Zanini, Andrea

2015-01-01

This paper describes the application of an innovative procedure that allows the estimation of longitudinal and transverse dispersivities in an experimental plume devised in a laboratory sandbox. The phenomenon of transport in porous media is studied using sodium fluorescein as tracer. The fluorescent excitation was achieved by using blue light and the concentration data were obtained through the processing of side wall images collected with a high resolution color digital camera. After a calibration process, the relationship between the luminosity of the emitted fluorescence and the fluorescein concentration was determined at each point of the sandbox. The relationships were used to describe the evolution of the transport process quantitatively throughout the entire domain. Some check tests were performed in order to verify the reliability of the experimental device. Numerical flow and transport models of the sandbox were developed and calibrated comparing computed and observed flow rates and breakthrough curves. The estimation of the dispersivity coefficients was carried out by analyzing the concentration field deduced from the images collected during the experiments; the dispersivity coefficients were evaluated in the domain zones where the tracer affected the porous medium under the hypothesis that the transport phenomenon is described by advection-dispersion equation (ADE) and by computing the differential components of the concentration by means of a numerical leap-frog scheme. The values determined agree with the ones referred in literature for similar media and with the coefficients obtained by calibrating the numerical model. Very interesting considerations have been made from the analysis of the performance of the methodology at different locations in the flow domain and phases of the plume evolution. Copyright © 2014 Elsevier B.V. All rights reserved.

A new scheme for velocity analysis and imaging of diffractions

NASA Astrophysics Data System (ADS)

Lin, Peng; Peng, Suping; Zhao, Jingtao; Cui, Xiaoqin; Du, Wenfeng

2018-06-01

Seismic diffractions are the responses of small-scale inhomogeneities or discontinuous geological features, which play a vital role in the exploitation and development of oil and gas reservoirs. However, diffractions are generally ignored and considered as interference noise in conventional data processing. In this paper, a new scheme for velocity analysis and imaging of seismic diffractions is proposed. Two steps compose of this scheme in our application. First, the plane-wave destruction method is used to separate diffractions from specular reflections in the prestack domain. Second, in order to accurately estimate migration velocity of the diffractions, the time-domain dip-angle gathers are derived from a Kirchhoff-based angle prestack time migration using separated diffractions. Diffraction events appear flat in the dip-angle gathers when imaged above the diffraction point with selected accurate migration velocity for diffractions. The selected migration velocity helps to produce the desired prestack imaging of diffractions. Synthetic and field examples are applied to test the validity of the new scheme. The diffraction imaging results indicate that the proposed scheme for velocity analysis and imaging of diffractions can provide more detailed information about small-scale geologic features for seismic interpretation.

Poisson-Gaussian Noise Reduction Using the Hidden Markov Model in Contourlet Domain for Fluorescence Microscopy Images

PubMed Central

Yang, Sejung; Lee, Byung-Uk

2015-01-01

In certain image acquisitions processes, like in fluorescence microscopy or astronomy, only a limited number of photons can be collected due to various physical constraints. The resulting images suffer from signal dependent noise, which can be modeled as a Poisson distribution, and a low signal-to-noise ratio. However, the majority of research on noise reduction algorithms focuses on signal independent Gaussian noise. In this paper, we model noise as a combination of Poisson and Gaussian probability distributions to construct a more accurate model and adopt the contourlet transform which provides a sparse representation of the directional components in images. We also apply hidden Markov models with a framework that neatly describes the spatial and interscale dependencies which are the properties of transformation coefficients of natural images. In this paper, an effective denoising algorithm for Poisson-Gaussian noise is proposed using the contourlet transform, hidden Markov models and noise estimation in the transform domain. We supplement the algorithm by cycle spinning and Wiener filtering for further improvements. We finally show experimental results with simulations and fluorescence microscopy images which demonstrate the improved performance of the proposed approach. PMID:26352138

DOE Office of Scientific and Technical Information (OSTI.GOV)

Niu, T; Dong, X; Petrongolo, M

Purpose: Dual energy CT (DECT) imaging plays an important role in advanced imaging applications due to its material decomposition capability. Direct decomposition via matrix inversion suffers from significant degradation of image signal-to-noise ratios, which reduces clinical value. Existing de-noising algorithms achieve suboptimal performance since they suppress image noise either before or after the decomposition and do not fully explore the noise statistical properties of the decomposition process. We propose an iterative image-domain decomposition method for noise suppression in DECT, using the full variance-covariance matrix of the decomposed images. Methods: The proposed algorithm is formulated in the form of least-square estimationmore » with smoothness regularization. It includes the inverse of the estimated variance-covariance matrix of the decomposed images as the penalty weight in the least-square term. Performance is evaluated using an evaluation phantom (Catphan 600) and an anthropomorphic head phantom. Results are compared to those generated using direct matrix inversion with no noise suppression, a de-noising method applied on the decomposed images, and an existing algorithm with similar formulation but with an edge-preserving regularization term. Results: On the Catphan phantom, our method retains the same spatial resolution as the CT images before decomposition while reducing the noise standard deviation of decomposed images by over 98%. The other methods either degrade spatial resolution or achieve less low-contrast detectability. Also, our method yields lower electron density measurement error than direct matrix inversion and reduces error variation by over 97%. On the head phantom, it reduces the noise standard deviation of decomposed images by over 97% without blurring the sinus structures. Conclusion: We propose an iterative image-domain decomposition method for DECT. The method combines noise suppression and material decomposition into an iterative process and achieves both goals simultaneously. The proposed algorithm shows superior performance on noise suppression with high image spatial resolution and low-contrast detectability. This work is supported by a Varian MRA grant.« less

Knowledge-driven information mining in remote-sensing image archives

NASA Astrophysics Data System (ADS)

Datcu, M.; Seidel, K.; D'Elia, S.; Marchetti, P. G.

2002-05-01

Users in all domains require information or information-related services that are focused, concise, reliable, low cost and timely and which are provided in forms and formats compatible with the user's own activities. In the current Earth Observation (EO) scenario, the archiving centres generally only offer data, images and other "low level" products. The user's needs are being only partially satisfied by a number of, usually small, value-adding companies applying time-consuming (mostly manual) and expensive processes relying on the knowledge of experts to extract information from those data or images.

Improving lateral resolution and image quality of optical coherence tomography by the multi-frame superresolution technique for 3D tissue imaging

PubMed Central

Shen, Kai; Lu, Hui; Baig, Sarfaraz; Wang, Michael R.

2017-01-01

The multi-frame superresolution technique is introduced to significantly improve the lateral resolution and image quality of spectral domain optical coherence tomography (SD-OCT). Using several sets of low resolution C-scan 3D images with lateral sub-spot-spacing shifts on different sets, the multi-frame superresolution processing of these sets at each depth layer reconstructs a higher resolution and quality lateral image. Layer by layer processing yields an overall high lateral resolution and quality 3D image. In theory, the superresolution processing including deconvolution can solve the diffraction limit, lateral scan density and background noise problems together. In experiment, the improved lateral resolution by ~3 times reaching 7.81 µm and 2.19 µm using sample arm optics of 0.015 and 0.05 numerical aperture respectively as well as doubling the image quality has been confirmed by imaging a known resolution test target. Improved lateral resolution on in vitro skin C-scan images has been demonstrated. For in vivo 3D SD-OCT imaging of human skin, fingerprint and retina layer, we used the multi-modal volume registration method to effectively estimate the lateral image shifts among different C-scans due to random minor unintended live body motion. Further processing of these images generated high lateral resolution 3D images as well as high quality B-scan images of these in vivo tissues. PMID:29188089

A platform for European CMOS image sensors for space applications

NASA Astrophysics Data System (ADS)

Minoglou, K.; San Segundo Bello, D.; Sabuncuoglu Tezcan, D.; Haspeslagh, L.; Van Olmen, J.; Merry, B.; Cavaco, C.; Mazzamuto, F.; Toqué-Trésonne, I.; Moirin, R.; Brouwer, M.; Toccafondi, M.; Preti, G.; Rosmeulen, M.; De Moor, P.

2017-11-01

Both ESA and the EC have identified the need for a supply chain of CMOS imagers for space applications which uses solely European sources. An essential requirement on this supply chain is the platformization of the process modules, in particular when it comes to very specific processing steps, such as those required for the manufacturing of backside illuminated image sensors. This is the goal of the European (EC/FP7/SPACE) funded project EUROCIS. All EUROCIS partners have excellent know-how and track record in the expertise fields required. Imec has been leading the imager chip design and the front side and backside processing. LASSE, as a major player in the laser annealing supplier sector, has been focusing on the optimization of the process related to the backside passivation of the image sensors. TNO, known worldwide as a top developer of instruments for scientific research, including space research and sensors for satellites, has contributed in the domain of optical layers for space instruments and optimized antireflective coatings. Finally, Selex ES, as a world-wide leader for manufacturing instruments with expertise in various space missions and programs, has defined the image sensor specifications and is taking care of the final device characterization. In this paper, an overview of the process flow, the results on test structures and imagers processed using this platform will be presented.

Advances in functional brain imaging technology and developmental neuro-psychology: their applications in the Jungian analytic domain.

PubMed

Petchkovsky, Leon

2017-06-01

Analytical psychology shares with many other psychotherapies the important task of repairing the consequences of developmental trauma. The majority of analytic patients come from compromised early developmental backgrounds: they may have experienced neglect, abuse, or failures of empathic resonance from their carers. Functional brain imagery techniques including Quantitative Electroencephalogram (QEEG), and functional Magnetic Resonance Imagery (fMRI), allow us to track mental processes in ways beyond verbal reportage and introspection. This independent perspective is useful for developing new psychodynamic hypotheses, testing current ones, providing diagnostic markers, and monitoring treatment progress. Jung, with the Word Association Test, grasped these principles 100 years ago. Brain imaging techniques have contributed to powerful recent advances in our understanding of neurodevelopmental processes in the first three years of life. If adequate nurturance is compromised, a range of difficulties may emerge. This has important implications for how we understand and treat our psychotherapy clients. The paper provides an overview of functional brain imaging and advances in developmental neuropsychology, and looks at applications of some of these findings (including neurofeedback) in the Jungian psychotherapy domain. © 2017, The Society of Analytical Psychology.

Processing Images of Craters for Spacecraft Navigation

NASA Technical Reports Server (NTRS)

Cheng, Yang; Johnson, Andrew E.; Matthies, Larry H.

2009-01-01

A crater-detection algorithm has been conceived to enable automation of what, heretofore, have been manual processes for utilizing images of craters on a celestial body as landmarks for navigating a spacecraft flying near or landing on that body. The images are acquired by an electronic camera aboard the spacecraft, then digitized, then processed by the algorithm, which consists mainly of the following steps: 1. Edges in an image detected and placed in a database. 2. Crater rim edges are selected from the edge database. 3. Edges that belong to the same crater are grouped together. 4. An ellipse is fitted to each group of crater edges. 5. Ellipses are refined directly in the image domain to reduce errors introduced in the detection of edges and fitting of ellipses. 6. The quality of each detected crater is evaluated. It is planned to utilize this algorithm as the basis of a computer program for automated, real-time, onboard processing of crater-image data. Experimental studies have led to the conclusion that this algorithm is capable of a detection rate >93 percent, a false-alarm rate <5 percent, a geometric error <0.5 pixel, and a position error <0.3 pixel.

Non-rigid ultrasound image registration using generalized relaxation labeling process

NASA Astrophysics Data System (ADS)

Lee, Jong-Ha; Seong, Yeong Kyeong; Park, MoonHo; Woo, Kyoung-Gu; Ku, Jeonghun; Park, Hee-Jun

2013-03-01

This research proposes a novel non-rigid registration method for ultrasound images. The most predominant anatomical features in medical images are tissue boundaries, which appear as edges. In ultrasound images, however, other features can be identified as well due to the specular reflections that appear as bright lines superimposed on the ideal edge location. In this work, an image's local phase information (via the frequency domain) is used to find the ideal edge location. The generalized relaxation labeling process is then formulated to align the feature points extracted from the ideal edge location. In this work, the original relaxation labeling method was generalized by taking n compatibility coefficient values to improve non-rigid registration performance. This contextual information combined with a relaxation labeling process is used to search for a correspondence. Then the transformation is calculated by the thin plate spline (TPS) model. These two processes are iterated until the optimal correspondence and transformation are found. We have tested our proposed method and the state-of-the-art algorithms with synthetic data and bladder ultrasound images of in vivo human subjects. Experiments show that the proposed method improves registration performance significantly, as compared to other state-of-the-art non-rigid registration algorithms.

3D-resolved fluorescence and phosphorescence lifetime imaging using temporal focusing wide-field two-photon excitation

PubMed Central

Choi, Heejin; Tzeranis, Dimitrios S.; Cha, Jae Won; Clémenceau, Philippe; de Jong, Sander J. G.; van Geest, Lambertus K.; Moon, Joong Ho; Yannas, Ioannis V.; So, Peter T. C.

2012-01-01

Fluorescence and phosphorescence lifetime imaging are powerful techniques for studying intracellular protein interactions and for diagnosing tissue pathophysiology. While lifetime-resolved microscopy has long been in the repertoire of the biophotonics community, current implementations fall short in terms of simultaneously providing 3D resolution, high throughput, and good tissue penetration. This report describes a new highly efficient lifetime-resolved imaging method that combines temporal focusing wide-field multiphoton excitation and simultaneous acquisition of lifetime information in frequency domain using a nanosecond gated imager from a 3D-resolved plane. This approach is scalable allowing fast volumetric imaging limited only by the available laser peak power. The accuracy and performance of the proposed method is demonstrated in several imaging studies important for understanding peripheral nerve regeneration processes. Most importantly, the parallelism of this approach may enhance the imaging speed of long lifetime processes such as phosphorescence by several orders of magnitude. PMID:23187477

Near-Space TOPSAR Large-Scene Full-Aperture Imaging Scheme Based on Two-Step Processing

PubMed Central

Zhang, Qianghui; Wu, Junjie; Li, Wenchao; Huang, Yulin; Yang, Jianyu; Yang, Haiguang

2016-01-01

Free of the constraints of orbit mechanisms, weather conditions and minimum antenna area, synthetic aperture radar (SAR) equipped on near-space platform is more suitable for sustained large-scene imaging compared with the spaceborne and airborne counterparts. Terrain observation by progressive scans (TOPS), which is a novel wide-swath imaging mode and allows the beam of SAR to scan along the azimuth, can reduce the time of echo acquisition for large scene. Thus, near-space TOPS-mode SAR (NS-TOPSAR) provides a new opportunity for sustained large-scene imaging. An efficient full-aperture imaging scheme for NS-TOPSAR is proposed in this paper. In this scheme, firstly, two-step processing (TSP) is adopted to eliminate the Doppler aliasing of the echo. Then, the data is focused in two-dimensional frequency domain (FD) based on Stolt interpolation. Finally, a modified TSP (MTSP) is performed to remove the azimuth aliasing. Simulations are presented to demonstrate the validity of the proposed imaging scheme for near-space large-scene imaging application. PMID:27472341

3D image restoration for confocal microscopy: toward a wavelet deconvolution for the study of complex biological structures

NASA Astrophysics Data System (ADS)

Boutet de Monvel, Jacques; Le Calvez, Sophie; Ulfendahl, Mats

2000-05-01

Image restoration algorithms provide efficient tools for recovering part of the information lost in the imaging process of a microscope. We describe recent progress in the application of deconvolution to confocal microscopy. The point spread function of a Biorad-MRC1024 confocal microscope was measured under various imaging conditions, and used to process 3D-confocal images acquired in an intact preparation of the inner ear developed at Karolinska Institutet. Using these experiments we investigate the application of denoising methods based on wavelet analysis as a natural regularization of the deconvolution process. Within the Bayesian approach to image restoration, we compare wavelet denoising with the use of a maximum entropy constraint as another natural regularization method. Numerical experiments performed with test images show a clear advantage of the wavelet denoising approach, allowing to `cool down' the image with respect to the signal, while suppressing much of the fine-scale artifacts appearing during deconvolution due to the presence of noise, incomplete knowledge of the point spread function, or undersampling problems. We further describe a natural development of this approach, which consists of performing the Bayesian inference directly in the wavelet domain.

Compressive Sensing Image Sensors-Hardware Implementation

PubMed Central

Dadkhah, Mohammadreza; Deen, M. Jamal; Shirani, Shahram

2013-01-01

The compressive sensing (CS) paradigm uses simultaneous sensing and compression to provide an efficient image acquisition technique. The main advantages of the CS method include high resolution imaging using low resolution sensor arrays and faster image acquisition. Since the imaging philosophy in CS imagers is different from conventional imaging systems, new physical structures have been developed for cameras that use the CS technique. In this paper, a review of different hardware implementations of CS encoding in optical and electrical domains is presented. Considering the recent advances in CMOS (complementary metal–oxide–semiconductor) technologies and the feasibility of performing on-chip signal processing, important practical issues in the implementation of CS in CMOS sensors are emphasized. In addition, the CS coding for video capture is discussed. PMID:23584123

Direct Correlation of DNA Binding and Single Protein Domain Motion via Dual Illumination Fluorescence Microscopy

PubMed Central

2015-01-01

We report a dual illumination, single-molecule imaging strategy to dissect directly and in real-time the correlation between nanometer-scale domain motion of a DNA repair protein and its interaction with individual DNA substrates. The strategy was applied to XPD, an FeS cluster-containing DNA repair helicase. Conformational dynamics was assessed via FeS-mediated quenching of a fluorophore site-specifically incorporated into XPD. Simultaneously, binding of DNA molecules labeled with a spectrally distinct fluorophore was detected by colocalization of the DNA- and protein-derived signals. We show that XPD undergoes thermally driven conformational transitions that manifest in spatial separation of its two auxiliary domains. DNA binding does not strictly enforce a specific conformation. Interaction with a cognate DNA damage, however, stabilizes the compact conformation of XPD by increasing the weighted average lifetime of this state by 140% relative to an undamaged DNA. Our imaging strategy will be a valuable tool to study other FeS-containing nucleic acid processing enzymes. PMID:25204359

NeuroSeek dual-color image processing infrared focal plane array

NASA Astrophysics Data System (ADS)

McCarley, Paul L.; Massie, Mark A.; Baxter, Christopher R.; Huynh, Buu L.

1998-09-01

Several technologies have been developed in recent years to advance the state of the art of IR sensor systems including dual color affordable focal planes, on-focal plane array biologically inspired image and signal processing techniques and spectral sensing techniques. Pacific Advanced Technology (PAT) and the Air Force Research Lab Munitions Directorate have developed a system which incorporates the best of these capabilities into a single device. The 'NeuroSeek' device integrates these technologies into an IR focal plane array (FPA) which combines multicolor Midwave IR/Longwave IR radiometric response with on-focal plane 'smart' neuromorphic analog image processing. The readout and processing integrated circuit very large scale integration chip which was developed under this effort will be hybridized to a dual color detector array to produce the NeuroSeek FPA, which will have the capability to fuse multiple pixel-based sensor inputs directly on the focal plane. Great advantages are afforded by application of massively parallel processing algorithms to image data in the analog domain; the high speed and low power consumption of this device mimic operations performed in the human retina.

Three-dimensional image signals: processing methods

NASA Astrophysics Data System (ADS)

Schiopu, Paul; Manea, Adrian; Craciun, Anca-Ileana; Craciun, Alexandru

2010-11-01

Over the years extensive studies have been carried out to apply coherent optics methods in real-time processing, communications and transmission image. This is especially true when a large amount of information needs to be processed, e.g., in high-resolution imaging. The recent progress in data-processing networks and communication systems has considerably increased the capacity of information exchange. We describe the results of literature investigation research of processing methods for the signals of the three-dimensional images. All commercially available 3D technologies today are based on stereoscopic viewing. 3D technology was once the exclusive domain of skilled computer-graphics developers with high-end machines and software. The images capture from the advanced 3D digital camera can be displayed onto screen of the 3D digital viewer with/ without special glasses. For this is needed considerable processing power and memory to create and render the complex mix of colors, textures, and virtual lighting and perspective necessary to make figures appear three-dimensional. Also, using a standard digital camera and a technique called phase-shift interferometry we can capture "digital holograms." These are holograms that can be stored on computer and transmitted over conventional networks. We present some research methods to process "digital holograms" for the Internet transmission and results.

Magneto-optical imaging technique for hostile environments: The ghost imaging approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Meda, A.; Caprile, A.; Avella, A.

2015-06-29

In this paper, we develop an approach to magneto optical imaging (MOI), applying a ghost imaging (GI) protocol to perform Faraday microscopy. MOI is of the utmost importance for the investigation of magnetic properties of material samples, through Weiss domains shape, dimension and dynamics analysis. Nevertheless, in some extreme conditions such as cryogenic temperatures or high magnetic field applications, there exists a lack of domain images due to the difficulty in creating an efficient imaging system in such environments. Here, we present an innovative MOI technique that separates the imaging optical path from the one illuminating the object. The techniquemore » is based on thermal light GI and exploits correlations between light beams to retrieve the image of magnetic domains. As a proof of principle, the proposed technique is applied to the Faraday magneto-optical observation of the remanence domain structure of an yttrium iron garnet sample.« less

lop-DWI: A Novel Scheme for Pre-Processing of Diffusion-Weighted Images in the Gradient Direction Domain.

PubMed

Sepehrband, Farshid; Choupan, Jeiran; Caruyer, Emmanuel; Kurniawan, Nyoman D; Gal, Yaniv; Tieng, Quang M; McMahon, Katie L; Vegh, Viktor; Reutens, David C; Yang, Zhengyi

2014-01-01

We describe and evaluate a pre-processing method based on a periodic spiral sampling of diffusion-gradient directions for high angular resolution diffusion magnetic resonance imaging. Our pre-processing method incorporates prior knowledge about the acquired diffusion-weighted signal, facilitating noise reduction. Periodic spiral sampling of gradient direction encodings results in an acquired signal in each voxel that is pseudo-periodic with characteristics that allow separation of low-frequency signal from high frequency noise. Consequently, it enhances local reconstruction of the orientation distribution function used to define fiber tracks in the brain. Denoising with periodic spiral sampling was tested using synthetic data and in vivo human brain images. The level of improvement in signal-to-noise ratio and in the accuracy of local reconstruction of fiber tracks was significantly improved using our method.

An optimized digital watermarking algorithm in wavelet domain based on differential evolution for color image.

PubMed

Cui, Xinchun; Niu, Yuying; Zheng, Xiangwei; Han, Yingshuai

2018-01-01

In this paper, a new color watermarking algorithm based on differential evolution is proposed. A color host image is first converted from RGB space to YIQ space, which is more suitable for the human visual system. Then, apply three-level discrete wavelet transformation to luminance component Y and generate four different frequency sub-bands. After that, perform singular value decomposition on these sub-bands. In the watermark embedding process, apply discrete wavelet transformation to a watermark image after the scrambling encryption processing. Our new algorithm uses differential evolution algorithm with adaptive optimization to choose the right scaling factors. Experimental results show that the proposed algorithm has a better performance in terms of invisibility and robustness.

Noise reduction in spectral CT: reducing dose and breaking the trade-off between image noise and energy bin selection.

PubMed

Leng, Shuai; Yu, Lifeng; Wang, Jia; Fletcher, Joel G; Mistretta, Charles A; McCollough, Cynthia H

2011-09-01

Our purpose was to reduce image noise in spectral CT by exploiting data redundancies in the energy domain to allow flexible selection of the number, width, and location of the energy bins. Using a variety of spectral CT imaging methods, conventional filtered backprojection (FBP) reconstructions were performed and resulting images were compared to those processed using a Local HighlY constrained backPRojection Reconstruction (HYPR-LR) algorithm. The mean and standard deviation of CT numbers were measured within regions of interest (ROIs), and results were compared between FBP and HYPR-LR. For these comparisons, the following spectral CT imaging methods were used:(i) numerical simulations based on a photon-counting, detector-based CT system, (ii) a photon-counting, detector-based micro CT system using rubidium and potassium chloride solutions, (iii) a commercial CT system equipped with integrating detectors utilizing tube potentials of 80, 100, 120, and 140 kV, and (iv) a clinical dual-energy CT examination. The effects of tube energy and energy bin width were evaluated appropriate to each CT system. The mean CT number in each ROI was unchanged between FBP and HYPR-LR images for each of the spectral CT imaging scenarios, irrespective of bin width or tube potential. However, image noise, as represented by the standard deviation of CT numbers in each ROI, was reduced by 36%-76%. In all scenarios, image noise after HYPR-LR algorithm was similar to that of composite images, which used all available photons. No difference in spatial resolution was observed between HYPR-LR processing and FBP. Dual energy patient data processed using HYPR-LR demonstrated reduced noise in the individual, low- and high-energy images, as well as in the material-specific basis images. Noise reduction can be accomplished for spectral CT by exploiting data redundancies in the energy domain. HYPR-LR is a robust method for reducing image noise in a variety of spectral CT imaging systems without losing spatial resolution or CT number accuracy. This method improves the flexibility to select energy bins in the manner that optimizes material identification and separation without paying the penalty of increased image noise or its corollary, increased patient dose.

In-vivo Fourier domain optical coherence tomography as a new tool for investigation of vasodynamics in the mouse model.

PubMed

Meissner, Sven; Müller, Gregor; Walther, Julia; Morawietz, Henning; Koch, Edmund

2009-01-01

In-vivo imaging of the vascular system can provide novel insight into the dynamics of vasoconstriction and vasodilation. Fourier domain optical coherence tomography (FD-OCT) is an optical, noncontact imaging technique based on interferometry of short-coherent near-infrared light with axial resolution of less than 10 microm. In this study, we apply FD-OCT as an in-vivo imaging technique to investigate blood vessels in their anatomical context using temporally resolved image stacks. Our chosen model system is the murine saphenous artery and vein, due to their small inner vessel diameters, sensitive response to vasoactive stimuli, and advantageous anatomical position. The vascular function of male wild-type mice (C57BL/6) is determined at the ages of 6 and 20 weeks. Vasoconstriction is analyzed in response to dermal application of potassium (K(+)), and vasodilation in response to sodium nitroprusside (SNP). Vasodynamics are quantified from time series (75 sec, 4 frames per sec, 330 x 512 pixels per frame) of cross sectional images that are analyzed by semiautomated image processing software. The morphology of the saphenous artery and vein is determined by 3-D image stacks of 512 x 512 x 512 pixels. Using the FD-OCT technique, we are able to demonstrate age-dependent differences in vascular function and vasodynamics.

Processing, mosaicking and management of the Monterey Bay digital sidescan-sonar images

USGS Publications Warehouse

Chavez, P.S.; Isbrecht, J.; Galanis, P.; Gabel, G.L.; Sides, S.C.; Soltesz, D.L.; Ross, Stephanie L.; Velasco, M.G.

2002-01-01

Sidescan-sonar imaging systems with digital capabilities have now been available for approximately 20 years. In this paper we present several of the various digital image processing techniques developed by the U.S. Geological Survey (USGS) and used to apply intensity/radiometric and geometric corrections, as well as enhance and digitally mosaic, sidescan-sonar images of the Monterey Bay region. New software run by a WWW server was designed and implemented to allow very large image data sets, such as the digital mosaic, to be easily viewed interactively, including the ability to roam throughout the digital mosaic at the web site in either compressed or full 1-m resolution. The processing is separated into the two different stages: preprocessing and information extraction. In the preprocessing stage, sensor-specific algorithms are applied to correct for both geometric and intensity/radiometric distortions introduced by the sensor. This is followed by digital mosaicking of the track-line strips into quadrangle format which can be used as input to either visual or digital image analysis and interpretation. An automatic seam removal procedure was used in combination with an interactive digital feathering/stenciling procedure to help minimize tone or seam matching problems between image strips from adjacent track-lines. The sidescan-sonar image processing package is part of the USGS Mini Image Processing System (MIPS) and has been designed to process data collected by any 'generic' digital sidescan-sonar imaging system. The USGS MIPS software, developed over the last 20 years as a public domain package, is available on the WWW at: http://terraweb.wr.usgs.gov/trs/software.html.

Preclinical evaluation and intraoperative human retinal imaging with a high-resolution microscope-integrated spectral domain optical coherence tomography device.

PubMed

Hahn, Paul; Migacz, Justin; O'Donnell, Rachelle; Day, Shelley; Lee, Annie; Lin, Phoebe; Vann, Robin; Kuo, Anthony; Fekrat, Sharon; Mruthyunjaya, Prithvi; Postel, Eric A; Izatt, Joseph A; Toth, Cynthia A

2013-01-01

The authors have recently developed a high-resolution microscope-integrated spectral domain optical coherence tomography (MIOCT) device designed to enable OCT acquisition simultaneous with surgical maneuvers. The purpose of this report is to describe translation of this device from preclinical testing into human intraoperative imaging. Before human imaging, surgical conditions were fully simulated for extensive preclinical MIOCT evaluation in a custom model eye system. Microscope-integrated spectral domain OCT images were then acquired in normal human volunteers and during vitreoretinal surgery in patients who consented to participate in a prospective institutional review board-approved study. Microscope-integrated spectral domain OCT images were obtained before and at pauses in surgical maneuvers and were compared based on predetermined diagnostic criteria to images obtained with a high-resolution spectral domain research handheld OCT system (HHOCT; Bioptigen, Inc) at the same time point. Cohorts of five consecutive patients were imaged. Successful end points were predefined, including ≥80% correlation in identification of pathology between MIOCT and HHOCT in ≥80% of the patients. Microscope-integrated spectral domain OCT was favorably evaluated by study surgeons and scrub nurses, all of whom responded that they would consider participating in human intraoperative imaging trials. The preclinical evaluation identified significant improvements that were made before MIOCT use during human surgery. The MIOCT transition into clinical human research was smooth. Microscope-integrated spectral domain OCT imaging in normal human volunteers demonstrated high resolution comparable to tabletop scanners. In the operating room, after an initial learning curve, surgeons successfully acquired human macular MIOCT images before and after surgical maneuvers. Microscope-integrated spectral domain OCT imaging confirmed preoperative diagnoses, such as full-thickness macular hole and vitreomacular traction, and demonstrated postsurgical changes in retinal morphology. Two cohorts of five patients were imaged. In the second cohort, the predefined end points were exceeded with ≥80% correlation between microscope-mounted OCT and HHOCT imaging in 100% of the patients. This report describes high-resolution MIOCT imaging using the prototype device in human eyes during vitreoretinal surgery, with successful achievement of predefined end points for imaging. Further refinements and investigations will be directed toward fully integrating MIOCT with vitreoretinal and other ocular surgery to image surgical maneuvers in real time.

Signal processing in ultrasound. [for diagnostic medicine

NASA Technical Reports Server (NTRS)

Le Croissette, D. H.; Gammell, P. M.

1978-01-01

Signal is the term used to denote the characteristic in the time or frequency domain of the probing energy of the system. Processing of this signal in diagnostic ultrasound occurs as the signal travels through the ultrasonic and electrical sections of the apparatus. The paper discusses current signal processing methods, postreception processing, display devices, real-time imaging, and quantitative measurements in noninvasive cardiology. The possibility of using deconvolution in a single transducer system is examined, and some future developments using digital techniques are outlined.

Low temperature and high field regimes of connected kagome artificial spin ice: the role of domain wall topology.

PubMed

Zeissler, Katharina; Chadha, Megha; Lovell, Edmund; Cohen, Lesley F; Branford, Will R

2016-07-22

Artificial spin ices are frustrated magnetic nanostructures where single domain nanobars act as macrosized spins. In connected kagome artificial spin ice arrays, reversal occurs along one-dimensional chains by propagation of ferromagnetic domain walls through Y-shaped vertices. Both the vertices and the walls are complex chiral objects with well-defined topological edge-charges. At room temperature, it is established that the topological edge-charges determine the exact switching reversal path taken. However, magnetic reversal at low temperatures has received much less attention and how these chiral objects interact at reduced temperature is unknown. In this study we use magnetic force microscopy to image the magnetic reversal process at low temperatures revealing the formation of quite remarkable high energy remanence states and a change in the dynamics of the reversal process. The implication is the breakdown of the artificial spin ice regime in these connected structures at low temperatures.

Advanced Image Processing for NASA Applications

NASA Technical Reports Server (NTRS)

LeMoign, Jacqueline

2007-01-01

The future of space exploration will involve cooperating fleets of spacecraft or sensor webs geared towards coordinated and optimal observation of Earth Science phenomena. The main advantage of such systems is to utilize multiple viewing angles as well as multiple spatial and spectral resolutions of sensors carried on multiple spacecraft but acting collaboratively as a single system. Within this framework, our research focuses on all areas related to sensing in collaborative environments, which means systems utilizing intracommunicating spatially distributed sensor pods or crafts being deployed to monitor or explore different environments. This talk will describe the general concept of sensing in collaborative environments, will give a brief overview of several technologies developed at NASA Goddard Space Flight Center in this area, and then will concentrate on specific image processing research related to that domain, specifically image registration and image fusion.

Rotation Covariant Image Processing for Biomedical Applications

PubMed Central

Reisert, Marco

2013-01-01

With the advent of novel biomedical 3D image acquisition techniques, the efficient and reliable analysis of volumetric images has become more and more important. The amount of data is enormous and demands an automated processing. The applications are manifold, ranging from image enhancement, image reconstruction, and image description to object/feature detection and high-level contextual feature extraction. In most scenarios, it is expected that geometric transformations alter the output in a mathematically well-defined manner. In this paper we emphasis on 3D translations and rotations. Many algorithms rely on intensity or low-order tensorial-like descriptions to fulfill this demand. This paper proposes a general mathematical framework based on mathematical concepts and theories transferred from mathematical physics and harmonic analysis into the domain of image analysis and pattern recognition. Based on two basic operations, spherical tensor differentiation and spherical tensor multiplication, we show how to design a variety of 3D image processing methods in an efficient way. The framework has already been applied to several biomedical applications ranging from feature and object detection tasks to image enhancement and image restoration techniques. In this paper, the proposed methods are applied on a variety of different 3D data modalities stemming from medical and biological sciences. PMID:23710255

Low dose CT image restoration using a database of image patches

NASA Astrophysics Data System (ADS)

Ha, Sungsoo; Mueller, Klaus

2015-01-01

Reducing the radiation dose in CT imaging has become an active research topic and many solutions have been proposed to remove the significant noise and streak artifacts in the reconstructed images. Most of these methods operate within the domain of the image that is subject to restoration. This, however, poses limitations on the extent of filtering possible. We advocate to take into consideration the vast body of external knowledge that exists in the domain of already acquired medical CT images, since after all, this is what radiologists do when they examine these low quality images. We can incorporate this knowledge by creating a database of prior scans, either of the same patient or a diverse corpus of different patients, to assist in the restoration process. Our paper follows up on our previous work that used a database of images. Using images, however, is challenging since it requires tedious and error prone registration and alignment. Our new method eliminates these problems by storing a diverse set of small image patches in conjunction with a localized similarity matching scheme. We also empirically show that it is sufficient to store these patches without anatomical tags since their statistics are sufficiently strong to yield good similarity matches from the database and as a direct effect, produce image restorations of high quality. A final experiment demonstrates that our global database approach can recover image features that are difficult to preserve with conventional denoising approaches.

Noise reduction with complex bilateral filter.

PubMed

Matsumoto, Mitsuharu

2017-12-01

This study introduces a noise reduction technique that uses a complex bilateral filter. A bilateral filter is a nonlinear filter originally developed for images that can reduce noise while preserving edge information. It is an attractive filter and has been used in many applications in image processing. When it is applied to an acoustical signal, small-amplitude noise is reduced while the speech signal is preserved. However, a bilateral filter cannot handle noise with relatively large amplitudes owing to its innate characteristics. In this study, the noisy signal is transformed into the time-frequency domain and the filter is improved to handle complex spectra. The high-amplitude noise is reduced in the time-frequency domain via the proposed filter. The features and the potential of the proposed filter are also confirmed through experiments.

Magnetization reversal of the domain structure in the anti-perovskite nitride Co{sub 3}FeN investigated by high-resolution X-ray microscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hajiri, T., E-mail: t.hajiri@numse.nagoya-u.ac.jp; Kuroki, Y.; Ando, H.

2016-05-14

We performed X-ray magnetic circular dichroism (XMCD) photoemission electron microscopy imaging to reveal the magnetic domain structure of anti-perovskite nitride Co{sub 3}FeN exhibiting a negative spin polarization. In square and disc patterns, we systematically and quantitatively determined the statistics of the stable states as a function of geometry. By direct imaging during the application of a magnetic field, we revealed the magnetic reversal process in a spatially resolved manner. We compared the hysteresis on the continuous area and the square patterns from the magnetic field-dependent XMCD ratio, which can be explained as resulting from the effect of the shape anisotropy,more » present in nanostructured thin films.« less

Gamma activity modulated by naming of ambiguous and unambiguous images: intracranial recording

PubMed Central

Cho-Hisamoto, Yoshimi; Kojima, Katsuaki; Brown, Erik C; Matsuzaki, Naoyuki; Asano, Eishi

2014-01-01

OBJECTIVE Humans sometimes need to recognize objects based on vague and ambiguous silhouettes. Recognition of such images may require an intuitive guess. We determined the spatial-temporal characteristics of intracranially-recorded gamma activity (at 50–120 Hz) augmented differentially by naming of ambiguous and unambiguous images. METHODS We studied ten patients who underwent epilepsy surgery. Ambiguous and unambiguous images were presented during extraoperative electrocorticography recording, and patients were instructed to overtly name the object as it is first perceived. RESULTS Both naming tasks were commonly associated with gamma-augmentation sequentially involving the occipital and occipital-temporal regions, bilaterally, within 200 ms after the onset of image presentation. Naming of ambiguous images elicited gamma-augmentation specifically involving portions of the inferior-frontal, orbitofrontal, and inferior-parietal regions at 400 ms and after. Unambiguous images were associated with more intense gamma-augmentation in portions of the occipital and occipital-temporal regions. CONCLUSIONS Frontal-parietal gamma-augmentation specific to ambiguous images may reflect the additional cortical processing involved in exerting intuitive guess. Occipital gamma-augmentation enhanced during naming of unambiguous images can be explained by visual processing of stimuli with richer detail. SIGNIFICANCE Our results support the theoretical model that guessing processes in visual domain occur following the accumulation of sensory evidence resulting from the bottom-up processing in the occipital-temporal visual pathways. PMID:24815577

Elongated phase separation domains in spin-cast polymer blend thin films characterized using a panoramic image.

PubMed

Zhang, Hong; Okamura, Yosuke

2018-02-14

Polymer thin films with micro/nano-structures can be prepared by a solvent evaporation induced phase separation process via spin-casting a polymer blend, where the elongated phase separation domains are always inevitable. The striation defect, as a thickness nonunifomity in spin-cast films, is generally coexistent with the elongated domains. Herein, the morphologies of polymer blend thin films are recorded from the spin-cast center to the edge in a panoramic view. The elongated domains are inclined to appear at the ridge regions of striations with increasing radial distance and align radially, exhibiting a coupling between the phase separation morphology and the striation defect that may exist. We demonstrate that the formation of elongated domains is not attributed to shape deformation, but is accomplished in situ. A possible model to describe the initiation and evolution of the polymer blend phase separation morphology during spin-casting is proposed.

The Open Microscopy Environment: open image informatics for the biological sciences

NASA Astrophysics Data System (ADS)

Blackburn, Colin; Allan, Chris; Besson, Sébastien; Burel, Jean-Marie; Carroll, Mark; Ferguson, Richard K.; Flynn, Helen; Gault, David; Gillen, Kenneth; Leigh, Roger; Leo, Simone; Li, Simon; Lindner, Dominik; Linkert, Melissa; Moore, Josh; Moore, William J.; Ramalingam, Balaji; Rozbicki, Emil; Rustici, Gabriella; Tarkowska, Aleksandra; Walczysko, Petr; Williams, Eleanor; Swedlow, Jason R.

2016-07-01

Despite significant advances in biological imaging and analysis, major informatics challenges remain unsolved: file formats are proprietary, storage and analysis facilities are lacking, as are standards for sharing image data and results. While the open FITS file format is ubiquitous in astronomy, astronomical imaging shares many challenges with biological imaging, including the need to share large image sets using secure, cross-platform APIs, and the need for scalable applications for processing and visualization. The Open Microscopy Environment (OME) is an open-source software framework developed to address these challenges. OME tools include: an open data model for multidimensional imaging (OME Data Model); an open file format (OME-TIFF) and library (Bio-Formats) enabling free access to images (5D+) written in more than 145 formats from many imaging domains, including FITS; and a data management server (OMERO). The Java-based OMERO client-server platform comprises an image metadata store, an image repository, visualization and analysis by remote access, allowing sharing and publishing of image data. OMERO provides a means to manage the data through a multi-platform API. OMERO's model-based architecture has enabled its extension into a range of imaging domains, including light and electron microscopy, high content screening, digital pathology and recently into applications using non-image data from clinical and genomic studies. This is made possible using the Bio-Formats library. The current release includes a single mechanism for accessing image data of all types, regardless of original file format, via Java, C/C++ and Python and a variety of applications and environments (e.g. ImageJ, Matlab and R).

Realization of a single image haze removal system based on DaVinci DM6467T processor

NASA Astrophysics Data System (ADS)

Liu, Zhuang

2014-10-01

Video monitoring system (VMS) has been extensively applied in domains of target recognition, traffic management, remote sensing, auto navigation and national defence. However the VMS has a strong dependence on the weather, for instance, in foggy weather, the quality of images received by the VMS are distinct degraded and the effective range of VMS is also decreased. All in all, the VMS performs terribly in bad weather. Thus the research of fog degraded images enhancement has very high theoretical and practical application value. A design scheme of a fog degraded images enhancement system based on the TI DaVinci processor is presented in this paper. The main function of the referred system is to extract and digital cameras capture images and execute image enhancement processing to obtain a clear image. The processor used in this system is the dual core TI DaVinci DM6467T - ARM@500MHz+DSP@1GH. A MontaVista Linux operating system is running on the ARM subsystem which handles I/O and application processing. The DSP handles signal processing and the results are available to the ARM subsystem in shared memory.The system benefits from the DaVinci processor so that, with lower power cost and smaller volume, it provides the equivalent image processing capability of a X86 computer. The outcome shows that the system in this paper can process images at 25 frames per second on D1 resolution.

Fast downscaled inverses for images compressed with M-channel lapped transforms.

PubMed

de Queiroz, R L; Eschbach, R

1997-01-01

Compressed images may be decompressed and displayed or printed using different devices at different resolutions. Full decompression and rescaling in space domain is a very expensive method. We studied downscaled inverses where the image is decompressed partially, and a reduced inverse transform is used to recover the image. In this fashion, fewer transform coefficients are used and the synthesis process is simplified. We studied the design of fast inverses, for a given forward transform. General solutions are presented for M-channel finite impulse response (FIR) filterbanks, of which block and lapped transforms are a subset. Designs of faster inverses are presented for popular block and lapped transforms.

New image compression scheme for digital angiocardiography application

NASA Astrophysics Data System (ADS)

Anastassopoulos, George C.; Lymberopoulos, Dimitris C.; Kotsopoulos, Stavros A.; Kokkinakis, George C.

1993-06-01

The present paper deals with the development and evaluation of a new compression scheme, for angiocardiography images. This scheme provides considerable compression of the medical data file, through two different stages. The first stage obliterates the redundancy inside a single frame domain since the second stage obliterates the redundancy among the sequential frames. Within these stages the employed data compression ratio can be easily adjusted according to the needs of the angiocardiography applications, where still or moving (in slow or full motion) images are hauled. The developed scheme has been tailored on the real needs of the diagnosis oriented conferencing-teleworking processes, where Unified Image Viewing facilities are required.

New Software Developments for Quality Mesh Generation and Optimization from Biomedical Imaging Data

PubMed Central

Yu, Zeyun; Wang, Jun; Gao, Zhanheng; Xu, Ming; Hoshijima, Masahiko

2013-01-01

In this paper we present a new software toolkit for generating and optimizing surface and volumetric meshes from three-dimensional (3D) biomedical imaging data, targeted at image-based finite element analysis of some biomedical activities in a single material domain. Our toolkit includes a series of geometric processing algorithms including surface re-meshing and quality-guaranteed tetrahedral mesh generation and optimization. All methods described have been encapsulated into a user-friendly graphical interface for easy manipulation and informative visualization of biomedical images and mesh models. Numerous examples are presented to demonstrate the effectiveness and efficiency of the described methods and toolkit. PMID:24252469

Comparative study of 2D ultrasound imaging methods in the f-k domain and evaluation of their performances in a realistic NDT configuration

NASA Astrophysics Data System (ADS)

Merabet, Lucas; Robert, Sébastien; Prada, Claire

2018-04-01

In this paper, we present two frequency-domain algorithms for 2D imaging with plane wave emissions, namely Stolt's migration and Lu's method. The theoretical background is first presented, followed by an analysis of the algorithm complexities. The frequency-domain methods are then compared to the time-domain plane wave imaging in a realistic inspection configuration where the array elements are not in contact with the specimen. Imaging defects located far away from the array aperture is assessed and computation times for the three methods are presented as a function of the number of pixels of the reconstructed image. We show that Lu's method provides a time gain of up to 33 compared to the time-domain algorithm, and demonstrate the limitations of Stolt's migration for defects far away from the aperture.

Garnet film rotator applied in polarizing microscope for domain image modulation (abstract)

NASA Astrophysics Data System (ADS)

Wakabayashi, K.; Numata, T.; Inokuchi, S.

1991-04-01

A garnet film polarization rotator placed before the analyzer in a polarizing microscope was investigated to obtain the difference image of a positive and a negative one of magnetic domain in real time along with an image processor. In the difference image, a nonmagnetic image can be reduced and hence the weak magnetic contrast enhanced. Theoretical calculation of S/N and contrast C of the domain image as a function of the rotation shows they take maxima at the rotation angle of 2.6° and 0.1°, respectively, with the extinction ratio of e=4×10-6 of a polarizing microscope. Thus, since the thickness of the garnet film required is 1 μm or so, the absorption by the garnet rotator does not bring a serious problem even in a visible region for the domain observation. The optimum rotation of the rotator for a high quality observation was obtained by a quantitative study of images obtained experimentally as well as by a visual evaluation. A magnetically unsaturated garnet film with perpendicular magnetization (i.e., multidomain) was employed as a rotator, in which the polarization rotation angle θm of the undeflected beam with respect to the light diffraction could be continuously varied by an applied magnetic field. The dependences of S/N and C on θm were measured, resulting in a well agreement between the measured and the calculated. The visually best image was obtained at θm=0.5° which made the product of S/N and C maximum. The domain image of the Kerr rotation angle of θk=0.22° was observed in S/N=47 dB and C=0.4 when Ar+ laser (λ=515 nm) of tenths of a watt was employed as a light source. Since the domain image with 47 dB S/N does not need an image summation for a noise reduction, a garnet film rotator makes it possible to invert the contrast of a domain image in a real time for an improved domain observation.

A Lossless hybrid wavelet-fractal compression for welding radiographic images.

PubMed

Mekhalfa, Faiza; Avanaki, Mohammad R N; Berkani, Daoud

2016-01-01

In this work a lossless wavelet-fractal image coder is proposed. The process starts by compressing and decompressing the original image using wavelet transformation and fractal coding algorithm. The decompressed image is removed from the original one to obtain a residual image which is coded by using Huffman algorithm. Simulation results show that with the proposed scheme, we achieve an infinite peak signal to noise ratio (PSNR) with higher compression ratio compared to typical lossless method. Moreover, the use of wavelet transform speeds up the fractal compression algorithm by reducing the size of the domain pool. The compression results of several welding radiographic images using the proposed scheme are evaluated quantitatively and compared with the results of Huffman coding algorithm.

Quantitative Analysis of En Face Spectral-Domain Optical Coherence Tomography Imaging in Polypoidal Choroidal Vasculopathy.

PubMed

Simonett, Joseph M; Chan, Errol W; Chou, Jonathan; Skondra, Dimitra; Colon, Daniel; Chee, Caroline K; Lingam, Gopal; Fawzi, Amani A

2017-02-01

Spectral-domain optical coherence tomography (SD-OCT) imaging can be used to visualize polypoidal choroidal vasculopathy (PCV) lesions in the en face plane. Here, the authors describe a novel lesion quantification technique and compare PCV lesion area measurements and morphology before and after anti-vascular endothelial growth factor (VEGF) treatment. Volumetric SD-OCT scans in eyes with PCV before and after induction anti-VEGF therapy were retrospectively analyzed. En face SD-OCT images were generated and a pixel intensity thresholding process was used to quantify total lesion area. Thirteen eyes with PCV were analyzed. En face SD-OCT PCV lesion area quantification showed good intergrader reliability (intraclass correlation coefficient = 0.944). Total PCV lesion area was significantly reduced after anti-VEGF therapy (2.22 mm 2 vs. 2.73 mm 2 ; P = .02). The overall geographic pattern of the branching vascular network was typically preserved. PCV lesion area analysis using en face SD-OCT is a reproducible tool that can quantify treatment related changes. [Ophthalmic Surg Lasers Imaging Retina. 2017;48:126-133.]. Copyright 2017, SLACK Incorporated.

Wide-field ultraviolet imager for astronomical transient studies

NASA Astrophysics Data System (ADS)

Mathew, Joice; Ambily, S.; Prakash, Ajin; Sarpotdar, Mayuresh; Nirmal, K.; G. Sreejith, A.; Safonova, Margarita; Murthy, Jayant; Brosch, Noah

2018-04-01

Though the ultraviolet (UV) domain plays a vital role in the studies of astronomical transient events, the UV time-domain sky remains largely unexplored. We have designed a wide-field UV imager that can be flown on a range of available platforms, such as high-altitude balloons, CubeSats, and larger space missions. The major scientific goals are the variability of astronomical sources, detection of transients such as supernovae, novae, tidal disruption events, and characterizing active galactic nuclei variability. The instrument has a 80 mm aperture with a circular field of view of 10.8 degrees, an angular resolution of ˜22 arcsec, and a 240 - 390 nm spectral observation window. The detector for the instrument is a Microchannel Plate (MCP)-based image intensifier with both photon counting and integration capabilities. An FPGA-based detector readout mechanism and real time data processing have been implemented. The imager is designed in such a way that its lightweight and compact nature are well fitted for the CubeSat dimensions. Here we present various design and developmental aspects of this UV wide-field transient explorer.

Polarization-resolved second-harmonic generation microscopy as a method to visualize protein-crystal domains

PubMed Central

DeWalt, Emma L.; Begue, Victoria J.; Ronau, Judith A.; Sullivan, Shane Z.; Das, Chittaranjan; Simpson, Garth J.

2013-01-01

Polarization-resolved second-harmonic generation (PR-SHG) microscopy is described and applied to identify the presence of multiple crystallographic domains within protein-crystal conglomerates, which was confirmed by synchrotron X-ray diffraction. Principal component analysis (PCA) of PR-SHG images resulted in principal component 2 (PC2) images with areas of contrasting negative and positive values for conglomerated crystals and PC2 images exhibiting uniformly positive or uniformly negative values for single crystals. Qualitative assessment of PC2 images allowed the identification of domains of different internal ordering within protein-crystal samples as well as differentiation between multi-domain conglomerated crystals and single crystals. PR-SHG assessments of crystalline domains were in good agreement with spatially resolved synchrotron X-ray diffraction measurements. These results have implications for improving the productive throughput of protein structure determination through early identification of multi-domain crystals. PMID:23275165

On the possibility of producing true real-time retinal cross-sectional images using a graphics processing unit enhanced master-slave optical coherence tomography system.

PubMed

Bradu, Adrian; Kapinchev, Konstantin; Barnes, Frederick; Podoleanu, Adrian

2015-07-01

In a previous report, we demonstrated master-slave optical coherence tomography (MS-OCT), an OCT method that does not need resampling of data and can be used to deliver en face images from several depths simultaneously. In a separate report, we have also demonstrated MS-OCT's capability of producing cross-sectional images of a quality similar to those provided by the traditional Fourier domain (FD) OCT technique, but at a much slower rate. Here, we demonstrate that by taking advantage of the parallel processing capabilities offered by the MS-OCT method, cross-sectional OCT images of the human retina can be produced in real time. We analyze the conditions that ensure a true real-time B-scan imaging operation and demonstrate in vivo real-time images from human fovea and the optic nerve, with resolution and sensitivity comparable to those produced using the traditional FD-based method, however, without the need of data resampling.

In-vivo gingival sulcus imaging using full-range, complex-conjugate-free, endoscopic spectral domain optical coherence tomography

NASA Astrophysics Data System (ADS)

Huang, Yong; Zhang, Kang; Yi, WonJin; Kang, Jin U.

2012-01-01

Frequent monitoring of gingival sulcus will provide valuable information for judging the presence and severity of periodontal disease. Optical coherence tomography, as a 3D high resolution high speed imaging modality is able to provide information for pocket depth, gum contour, gum texture, gum recession simultaneously. A handheld forward-viewing miniature resonant fiber-scanning probe was developed for in-vivo gingival sulcus imaging. The fiber cantilever driven by magnetic force vibrates at resonant frequency. A synchronized linear phase-modulation was applied in the reference arm by the galvanometer-driven reference mirror. Full-range, complex-conjugate-free, real-time endoscopic SD-OCT was achieved by accelerating the data process using graphics processing unit. Preliminary results showed a real-time in-vivo imaging at 33 fps with an imaging range of lateral 2 mm by depth 3 mm. Gap between the tooth and gum area was clearly visualized. Further quantification analysis of the gingival sulcus will be performed on the image acquired.

A single dual-stream framework for syntactic computations in music and language.

PubMed

Musso, Mariacristina; Weiller, Cornelius; Horn, Andreas; Glauche, Volkmer; Umarova, Roza; Hennig, Jürgen; Schneider, Albrecht; Rijntjes, Michel

2015-08-15

This study is the first to compare in the same subjects the specific spatial distribution and the functional and anatomical connectivity of the neuronal resources that activate and integrate syntactic representations during music and language processing. Combining functional magnetic resonance imaging with functional connectivity and diffusion tensor imaging-based probabilistic tractography, we examined the brain network involved in the recognition and integration of words and chords that were not hierarchically related to the preceding syntax; that is, those deviating from the universal principles of grammar and tonal relatedness. This kind of syntactic processing in both domains was found to rely on a shared network in the left hemisphere centered on the inferior part of the inferior frontal gyrus (IFG), including pars opercularis and pars triangularis, and on dorsal and ventral long association tracts connecting this brain area with temporo-parietal regions. Language processing utilized some adjacent left hemispheric IFG and middle temporal regions more than music processing, and music processing also involved right hemisphere regions not activated in language processing. Our data indicate that a dual-stream system with dorsal and ventral long association tracts centered on a functionally and structurally highly differentiated left IFG is pivotal for domain-general syntactic competence over a broad range of elements including words and chords. Copyright © 2015 Elsevier Inc. All rights reserved.

A cost-efficient frequency-domain photoacoustic imaging system

PubMed Central

LeBoulluec, Peter; Liu, Hanli; Yuan, Baohong

2013-01-01

Photoacoustic (PA) imaging techniques have recently attracted much attention and can be used for noninvasive imaging of biological tissues. Most PA imaging systems in research laboratories use the time domain method with expensive nanosecond pulsed lasers that are not affordable for most educational laboratories. Using an intensity modulated light source to excite PA signals is an alternative technique, known as the frequency domain method, with a much lower cost. In this paper, we describe a simple frequency domain PA system and demonstrate its imaging capability. The system provides opportunities not only to observe PA signals in tissue phantoms, but also to acquire hands-on skills in PA signal detection. It also provides opportunities to explore the underlying mechanisms of the PA effect. PMID:24659823

A cost-efficient frequency-domain photoacoustic imaging system.

PubMed

Leboulluec, Peter; Liu, Hanli; Yuan, Baohong

2013-09-01

Photoacoustic (PA) imaging techniques have recently attracted much attention and can be used for noninvasive imaging of biological tissues. Most PA imaging systems in research laboratories use the time domain method with expensive nanosecond pulsed lasers that are not affordable for most educational laboratories. Using an intensity modulated light source to excite PA signals is an alternative technique, known as the frequency domain method, with a much lower cost. In this paper, we describe a simple frequency domain PA system and demonstrate its imaging capability. The system provides opportunities not only to observe PA signals in tissue phantoms, but also to acquire hands-on skills in PA signal detection. It also provides opportunities to explore the underlying mechanisms of the PA effect.

Robust Global Image Registration Based on a Hybrid Algorithm Combining Fourier and Spatial Domain Techniques

DTIC Science & Technology

2012-09-01

Robust global image registration based on a hybrid algorithm combining Fourier and spatial domain techniques Peter N. Crabtree, Collin Seanor...00-00-2012 to 00-00-2012 4. TITLE AND SUBTITLE Robust global image registration based on a hybrid algorithm combining Fourier and spatial domain...demonstrate performance of a hybrid algorithm . These results are from analysis of a set of images of an ISO 12233 [12] resolution chart captured in the

Emotional textile image classification based on cross-domain convolutional sparse autoencoders with feature selection

NASA Astrophysics Data System (ADS)

Li, Zuhe; Fan, Yangyu; Liu, Weihua; Yu, Zeqi; Wang, Fengqin

2017-01-01

We aim to apply sparse autoencoder-based unsupervised feature learning to emotional semantic analysis for textile images. To tackle the problem of limited training data, we present a cross-domain feature learning scheme for emotional textile image classification using convolutional autoencoders. We further propose a correlation-analysis-based feature selection method for the weights learned by sparse autoencoders to reduce the number of features extracted from large size images. First, we randomly collect image patches on an unlabeled image dataset in the source domain and learn local features with a sparse autoencoder. We then conduct feature selection according to the correlation between different weight vectors corresponding to the autoencoder's hidden units. We finally adopt a convolutional neural network including a pooling layer to obtain global feature activations of textile images in the target domain and send these global feature vectors into logistic regression models for emotional image classification. The cross-domain unsupervised feature learning method achieves 65% to 78% average accuracy in the cross-validation experiments corresponding to eight emotional categories and performs better than conventional methods. Feature selection can reduce the computational cost of global feature extraction by about 50% while improving classification performance.

Segmentation of dermatoscopic images by frequency domain filtering and k-means clustering algorithms.

PubMed

Rajab, Maher I

2011-11-01

Since the introduction of epiluminescence microscopy (ELM), image analysis tools have been extended to the field of dermatology, in an attempt to algorithmically reproduce clinical evaluation. Accurate image segmentation of skin lesions is one of the key steps for useful, early and non-invasive diagnosis of coetaneous melanomas. This paper proposes two image segmentation algorithms based on frequency domain processing and k-means clustering/fuzzy k-means clustering. The two methods are capable of segmenting and extracting the true border that reveals the global structure irregularity (indentations and protrusions), which may suggest excessive cell growth or regression of a melanoma. As a pre-processing step, Fourier low-pass filtering is applied to reduce the surrounding noise in a skin lesion image. A quantitative comparison of the techniques is enabled by the use of synthetic skin lesion images that model lesions covered with hair to which Gaussian noise is added. The proposed techniques are also compared with an established optimal-based thresholding skin-segmentation method. It is demonstrated that for lesions with a range of different border irregularity properties, the k-means clustering and fuzzy k-means clustering segmentation methods provide the best performance over a range of signal to noise ratios. The proposed segmentation techniques are also demonstrated to have similar performance when tested on real skin lesions representing high-resolution ELM images. This study suggests that the segmentation results obtained using a combination of low-pass frequency filtering and k-means or fuzzy k-means clustering are superior to the result that would be obtained by using k-means or fuzzy k-means clustering segmentation methods alone. © 2011 John Wiley & Sons A/S.

Real time 3D structural and Doppler OCT imaging on graphics processing units

NASA Astrophysics Data System (ADS)

Sylwestrzak, Marcin; Szlag, Daniel; Szkulmowski, Maciej; Gorczyńska, Iwona; Bukowska, Danuta; Wojtkowski, Maciej; Targowski, Piotr

2013-03-01

In this report the application of graphics processing unit (GPU) programming for real-time 3D Fourier domain Optical Coherence Tomography (FdOCT) imaging with implementation of Doppler algorithms for visualization of the flows in capillary vessels is presented. Generally, the time of the data processing of the FdOCT data on the main processor of the computer (CPU) constitute a main limitation for real-time imaging. Employing additional algorithms, such as Doppler OCT analysis, makes this processing even more time consuming. Lately developed GPUs, which offers a very high computational power, give a solution to this problem. Taking advantages of them for massively parallel data processing, allow for real-time imaging in FdOCT. The presented software for structural and Doppler OCT allow for the whole processing with visualization of 2D data consisting of 2000 A-scans generated from 2048 pixels spectra with frame rate about 120 fps. The 3D imaging in the same mode of the volume data build of 220 × 100 A-scans is performed at a rate of about 8 frames per second. In this paper a software architecture, organization of the threads and optimization applied is shown. For illustration the screen shots recorded during real time imaging of the phantom (homogeneous water solution of Intralipid in glass capillary) and the human eye in-vivo is presented.

NEFI: Network Extraction From Images

PubMed Central

Dirnberger, M.; Kehl, T.; Neumann, A.

2015-01-01

Networks are amongst the central building blocks of many systems. Given a graph of a network, methods from graph theory enable a precise investigation of its properties. Software for the analysis of graphs is widely available and has been applied to study various types of networks. In some applications, graph acquisition is relatively simple. However, for many networks data collection relies on images where graph extraction requires domain-specific solutions. Here we introduce NEFI, a tool that extracts graphs from images of networks originating in various domains. Regarding previous work on graph extraction, theoretical results are fully accessible only to an expert audience and ready-to-use implementations for non-experts are rarely available or insufficiently documented. NEFI provides a novel platform allowing practitioners to easily extract graphs from images by combining basic tools from image processing, computer vision and graph theory. Thus, NEFI constitutes an alternative to tedious manual graph extraction and special purpose tools. We anticipate NEFI to enable time-efficient collection of large datasets. The analysis of these novel datasets may open up the possibility to gain new insights into the structure and function of various networks. NEFI is open source and available at http://nefi.mpi-inf.mpg.de. PMID:26521675

Analysis of x-ray hand images for bone age assessment

NASA Astrophysics Data System (ADS)

Serrat, Joan; Vitria, Jordi M.; Villanueva, Juan J.

1990-09-01

In this paper we describe a model-based system for the assessment of skeletal maturity on hand radiographs by the TW2 method. The problem consists in classiflying a set of bones appearing in an image in one of several stages described in an atlas. A first approach consisting in pre-processing segmentation and classification independent phases is also presented. However it is only well suited for well contrasted low noise images without superimposed bones were the edge detection by zero crossing of second directional derivatives is able to extract all bone contours maybe with little gaps and few false edges on the background. Hence the use of all available knowledge about the problem domain is needed to build a rather general system. We have designed a rule-based system for narrow down the rank of possible stages for each bone and guide the analysis process. It calls procedures written in conventional languages for matching stage models against the image and getting features needed in the classification process.

Low-count PET image restoration using sparse representation

NASA Astrophysics Data System (ADS)

Li, Tao; Jiang, Changhui; Gao, Juan; Yang, Yongfeng; Liang, Dong; Liu, Xin; Zheng, Hairong; Hu, Zhanli

2018-04-01

In the field of positron emission tomography (PET), reconstructed images are often blurry and contain noise. These problems are primarily caused by the low resolution of projection data. Solving this problem by improving hardware is an expensive solution, and therefore, we attempted to develop a solution based on optimizing several related algorithms in both the reconstruction and image post-processing domains. As sparse technology is widely used, sparse prediction is increasingly applied to solve this problem. In this paper, we propose a new sparse method to process low-resolution PET images. Two dictionaries (D1 for low-resolution PET images and D2 for high-resolution PET images) are learned from a group real PET image data sets. Among these two dictionaries, D1 is used to obtain a sparse representation for each patch of the input PET image. Then, a high-resolution PET image is generated from this sparse representation using D2. Experimental results indicate that the proposed method exhibits a stable and superior ability to enhance image resolution and recover image details. Quantitatively, this method achieves better performance than traditional methods. This proposed strategy is a new and efficient approach for improving the quality of PET images.

Progressive multi-atlas label fusion by dictionary evolution.

PubMed

Song, Yantao; Wu, Guorong; Bahrami, Khosro; Sun, Quansen; Shen, Dinggang

2017-02-01

Accurate segmentation of anatomical structures in medical images is important in recent imaging based studies. In the past years, multi-atlas patch-based label fusion methods have achieved a great success in medical image segmentation. In these methods, the appearance of each input image patch is first represented by an atlas patch dictionary (in the image domain), and then the latent label of the input image patch is predicted by applying the estimated representation coefficients to the corresponding anatomical labels of the atlas patches in the atlas label dictionary (in the label domain). However, due to the generally large gap between the patch appearance in the image domain and the patch structure in the label domain, the estimated (patch) representation coefficients from the image domain may not be optimal for the final label fusion, thus reducing the labeling accuracy. To address this issue, we propose a novel label fusion framework to seek for the suitable label fusion weights by progressively constructing a dynamic dictionary in a layer-by-layer manner, where the intermediate dictionaries act as a sequence of guidance to steer the transition of (patch) representation coefficients from the image domain to the label domain. Our proposed multi-layer label fusion framework is flexible enough to be applied to the existing labeling methods for improving their label fusion performance, i.e., by extending their single-layer static dictionary to the multi-layer dynamic dictionary. The experimental results show that our proposed progressive label fusion method achieves more accurate hippocampal segmentation results for the ADNI dataset, compared to the counterpart methods using only the single-layer static dictionary. Copyright © 2016 Elsevier B.V. All rights reserved.

Automated image analysis for quantification of reactive oxygen species in plant leaves.

PubMed

Sekulska-Nalewajko, Joanna; Gocławski, Jarosław; Chojak-Koźniewska, Joanna; Kuźniak, Elżbieta

2016-10-15

The paper presents an image processing method for the quantitative assessment of ROS accumulation areas in leaves stained with DAB or NBT for H 2 O 2 and O 2 - detection, respectively. Three types of images determined by the combination of staining method and background color are considered. The method is based on the principle of supervised machine learning with manually labeled image patterns used for training. The method's algorithm is developed as a JavaScript macro in the public domain Fiji (ImageJ) environment. It allows to select the stained regions of ROS-mediated histochemical reactions, subsequently fractionated according to the weak, medium and intense staining intensity and thus ROS accumulation. It also evaluates total leaf blade area. The precision of ROS accumulation area detection is validated by the Dice Similarity Coefficient in the case of manual patterns. The proposed framework reduces the computation complexity, once prepared, requires less image processing expertise than the competitive methods and represents a routine quantitative imaging assay for a general histochemical image classification. Copyright © 2016 Elsevier Inc. All rights reserved.

Resting-state fMRI and social cognition: An opportunity to connect.

PubMed

Doruyter, Alex; Groenewold, Nynke A; Dupont, Patrick; Stein, Dan J; Warwick, James M

2017-09-01

Many psychiatric disorders are characterized by altered social cognition. The importance of social cognition has previously been recognized by the National Institute of Mental Health Research Domain Criteria project, in which it features as a core domain. Social task-based functional magnetic resonance imaging (fMRI) currently offers the most direct insight into how the brain processes social information; however, resting-state fMRI may be just as important in understanding the biology and network nature of social processing. Resting-state fMRI allows researchers to investigate the functional relationships between brain regions in a neutral state: so-called resting functional connectivity (RFC). There is evidence that RFC is predictive of how the brain processes information during social tasks. This is important because it shifts the focus from possibly context-dependent aberrations to context-independent aberrations in functional network architecture. Rather than being analysed in isolation, the study of resting-state brain networks shows promise in linking results of task-based fMRI results, structural connectivity, molecular imaging findings, and performance measures of social cognition-which may prove crucial in furthering our understanding of the social brain. Copyright © 2017 John Wiley & Sons, Ltd.

A multiscale Markov random field model in wavelet domain for image segmentation

NASA Astrophysics Data System (ADS)

Dai, Peng; Cheng, Yu; Wang, Shengchun; Du, Xinyu; Wu, Dan

2017-07-01

The human vision system has abilities for feature detection, learning and selective attention with some properties of hierarchy and bidirectional connection in the form of neural population. In this paper, a multiscale Markov random field model in the wavelet domain is proposed by mimicking some image processing functions of vision system. For an input scene, our model provides its sparse representations using wavelet transforms and extracts its topological organization using MRF. In addition, the hierarchy property of vision system is simulated using a pyramid framework in our model. There are two information flows in our model, i.e., a bottom-up procedure to extract input features and a top-down procedure to provide feedback controls. The two procedures are controlled simply by two pyramidal parameters, and some Gestalt laws are also integrated implicitly. Equipped with such biological inspired properties, our model can be used to accomplish different image segmentation tasks, such as edge detection and region segmentation.

A review of image quality assessment methods with application to computational photography

NASA Astrophysics Data System (ADS)

Maître, Henri

2015-12-01

Image quality assessment has been of major importance for several domains of the industry of image as for instance restoration or communication and coding. New application fields are opening today with the increase of embedded power in the camera and the emergence of computational photography: automatic tuning, image selection, image fusion, image data-base building, etc. We review the literature of image quality evaluation. We pay attention to the very different underlying hypotheses and results of the existing methods to approach the problem. We explain why they differ and for which applications they may be beneficial. We also underline their limits, especially for a possible use in the novel domain of computational photography. Being developed to address different objectives, they propose answers on different aspects, which make them sometimes complementary. However, they all remain limited in their capability to challenge the human expert, the said or unsaid ultimate goal. We consider the methods which are based on retrieving the parameters of a signal, mostly in spectral analysis; then we explore the more global methods to qualify the image quality in terms of noticeable defects or degradation as popular in the compression domain; in a third field the image acquisition process is considered as a channel between the source and the receiver, allowing to use the tools of the information theory and to qualify the system in terms of entropy and information capacity. However, these different approaches hardly attack the most difficult part of the task which is to measure the quality of the photography in terms of aesthetic properties. To help in addressing this problem, in between Philosophy, Biology and Psychology, we propose a brief review of the literature which addresses the problematic of qualifying Beauty, present the attempts to adapt these concepts to visual patterns and initiate a reflection on what could be done in the field of photography.

Processing of Visual Imagery by an Adaptive Model of the Visual System: Its Performance and its Significance. Final Report, June 1969-March 1970.

ERIC Educational Resources Information Center

Tallman, Oliver H.

A digital simulation of a model for the processing of visual images is derived from known aspects of the human visual system. The fundamental principle of computation suggested by a biological model is a transformation that distributes information contained in an input stimulus everywhere in a transform domain. Each sensory input contributes under…

Principal curve detection in complicated graph images

NASA Astrophysics Data System (ADS)

Liu, Yuncai; Huang, Thomas S.

2001-09-01

Finding principal curves in an image is an important low level processing in computer vision and pattern recognition. Principal curves are those curves in an image that represent boundaries or contours of objects of interest. In general, a principal curve should be smooth with certain length constraint and allow either smooth or sharp turning. In this paper, we present a method that can efficiently detect principal curves in complicated map images. For a given feature image, obtained from edge detection of an intensity image or thinning operation of a pictorial map image, the feature image is first converted to a graph representation. In graph image domain, the operation of principal curve detection is performed to identify useful image features. The shortest path and directional deviation schemes are used in our algorithm os principal verve detection, which is proven to be very efficient working with real graph images.

Comparison of Frequency-Domain Array Methods for Studying Earthquake Rupture Process

NASA Astrophysics Data System (ADS)

Sheng, Y.; Yin, J.; Yao, H.

2014-12-01

Seismic array methods, in both time- and frequency- domains, have been widely used to study the rupture process and energy radiation of earthquakes. With better spatial resolution, the high-resolution frequency-domain methods, such as Multiple Signal Classification (MUSIC) (Schimdt, 1986; Meng et al., 2011) and the recently developed Compressive Sensing (CS) technique (Yao et al., 2011, 2013), are revealing new features of earthquake rupture processes. We have performed various tests on the methods of MUSIC, CS, minimum-variance distortionless response (MVDR) Beamforming and conventional Beamforming in order to better understand the advantages and features of these methods for studying earthquake rupture processes. We use the ricker wavelet to synthesize seismograms and use these frequency-domain techniques to relocate the synthetic sources we set, for instance, two sources separated in space but, their waveforms completely overlapping in the time domain. We also test the effects of the sliding window scheme on the recovery of a series of input sources, in particular, some artifacts that are caused by the sliding window scheme. Based on our tests, we find that CS, which is developed from the theory of sparsity inversion, has relatively high spatial resolution than the other frequency-domain methods and has better performance at lower frequencies. In high-frequency bands, MUSIC, as well as MVDR Beamforming, is more stable, especially in the multi-source situation. Meanwhile, CS tends to produce more artifacts when data have poor signal-to-noise ratio. Although these techniques can distinctly improve the spatial resolution, they still produce some artifacts along with the sliding of the time window. Furthermore, we propose a new method, which combines both the time-domain and frequency-domain techniques, to suppress these artifacts and obtain more reliable earthquake rupture images. Finally, we apply this new technique to study the 2013 Okhotsk deep mega earthquake in order to better capture the rupture characteristics (e.g., rupture area and velocity) of this earthquake.

Iterative image-domain decomposition for dual-energy CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Niu, Tianye; Dong, Xue; Petrongolo, Michael

2014-04-15

Purpose: Dual energy CT (DECT) imaging plays an important role in advanced imaging applications due to its capability of material decomposition. Direct decomposition via matrix inversion suffers from significant degradation of image signal-to-noise ratios, which reduces clinical values of DECT. Existing denoising algorithms achieve suboptimal performance since they suppress image noise either before or after the decomposition and do not fully explore the noise statistical properties of the decomposition process. In this work, the authors propose an iterative image-domain decomposition method for noise suppression in DECT, using the full variance-covariance matrix of the decomposed images. Methods: The proposed algorithm ismore » formulated in the form of least-square estimation with smoothness regularization. Based on the design principles of a best linear unbiased estimator, the authors include the inverse of the estimated variance-covariance matrix of the decomposed images as the penalty weight in the least-square term. The regularization term enforces the image smoothness by calculating the square sum of neighboring pixel value differences. To retain the boundary sharpness of the decomposed images, the authors detect the edges in the CT images before decomposition. These edge pixels have small weights in the calculation of the regularization term. Distinct from the existing denoising algorithms applied on the images before or after decomposition, the method has an iterative process for noise suppression, with decomposition performed in each iteration. The authors implement the proposed algorithm using a standard conjugate gradient algorithm. The method performance is evaluated using an evaluation phantom (Catphan©600) and an anthropomorphic head phantom. The results are compared with those generated using direct matrix inversion with no noise suppression, a denoising method applied on the decomposed images, and an existing algorithm with similar formulation as the proposed method but with an edge-preserving regularization term. Results: On the Catphan phantom, the method maintains the same spatial resolution on the decomposed images as that of the CT images before decomposition (8 pairs/cm) while significantly reducing their noise standard deviation. Compared to that obtained by the direct matrix inversion, the noise standard deviation in the images decomposed by the proposed algorithm is reduced by over 98%. Without considering the noise correlation properties in the formulation, the denoising scheme degrades the spatial resolution to 6 pairs/cm for the same level of noise suppression. Compared to the edge-preserving algorithm, the method achieves better low-contrast detectability. A quantitative study is performed on the contrast-rod slice of Catphan phantom. The proposed method achieves lower electron density measurement error as compared to that by the direct matrix inversion, and significantly reduces the error variation by over 97%. On the head phantom, the method reduces the noise standard deviation of decomposed images by over 97% without blurring the sinus structures. Conclusions: The authors propose an iterative image-domain decomposition method for DECT. The method combines noise suppression and material decomposition into an iterative process and achieves both goals simultaneously. By exploring the full variance-covariance properties of the decomposed images and utilizing the edge predetection, the proposed algorithm shows superior performance on noise suppression with high image spatial resolution and low-contrast detectability.« less

Maximizing Iodine Contrast-to-Noise Ratios in Abdominal CT Imaging through Use of Energy Domain Noise Reduction and Virtual Monoenergetic Dual-Energy CT.

PubMed

Leng, Shuai; Yu, Lifeng; Fletcher, Joel G; McCollough, Cynthia H

2015-08-01

To determine the iodine contrast-to-noise ratio (CNR) for abdominal computed tomography (CT) when using energy domain noise reduction and virtual monoenergetic dual-energy (DE) CT images and to compare the CNR to that attained with single-energy CT at 80, 100, 120, and 140 kV. This HIPAA-compliant study was approved by the institutional review board with waiver of informed consent. A syringe filled with diluted iodine contrast material was placed into 30-, 35-, and 45-cm-wide water phantoms and scanned with a dual-source CT scanner in both DE and single-energy modes with matched scanner output. Virtual monoenergetic images were generated, with energies ranging from 40 to 110 keV in 10-keV steps. A previously developed energy domain noise reduction algorithm was applied to reduce image noise by exploiting information redundancies in the energy domain. Image noise and iodine CNR were calculated. To show the potential clinical benefit of this technique, it was retrospectively applied to a clinical DE CT study of the liver in a 59-year-old male patient by using conventional and iterative reconstruction techniques. Image noise and CNR were compared for virtual monoenergetic images with and without energy domain noise reduction at each virtual monoenergetic energy (in kiloelectron volts) and phantom size by using a paired t test. CNR of virtual monoenergetic images was also compared with that of single-energy images acquired with 80, 100, 120, and 140 kV. Noise reduction of up to 59% (28.7 of 65.7) was achieved for DE virtual monoenergetic images by using an energy domain noise reduction technique. For the commercial virtual monoenergetic images, the maximum iodine CNR was achieved at 70 keV and was 18.6, 16.6, and 10.8 for the 30-, 35-, and 45-cm phantoms. After energy domain noise reduction, maximum iodine CNR was achieved at 40 keV and increased to 30.6, 25.4, and 16.5. These CNRs represented improvement of up to 64% (12.0 of 18.6) with the energy domain noise reduction technique. For single-energy CT at the optimal tube potential, iodine CNR was 29.1 (80 kV), 21.2 (80 kV), and 11.5 (100 kV). For patient images, 39% (24 of 61) noise reduction and 67% (0.74 of 1.10) CNR improvement were observed with the energy domain noise reduction technique when compared with standard filtered back-projection images. Iodine CNR for adult abdominal CT may be maximized with energy domain noise reduction and virtual monoenergetic DE CT. (©) RSNA, 2015.

Unprocessed real-time imaging of vitreoretinal surgical maneuvers using a microscope-integrated spectral-domain optical coherence tomography system.

PubMed

Hahn, Paul; Migacz, Justin; O'Connell, Rachelle; Izatt, Joseph A; Toth, Cynthia A

2013-01-01

We have recently developed a microscope-integrated spectral-domain optical coherence tomography (MIOCT) device towards intrasurgical cross-sectional imaging of surgical maneuvers. In this report, we explore the capability of MIOCT to acquire real-time video imaging of vitreoretinal surgical maneuvers without post-processing modifications. Standard 3-port vitrectomy was performed in human during scheduled surgery as well as in cadaveric porcine eyes. MIOCT imaging of human subjects was performed in healthy normal volunteers and intraoperatively at a normal pause immediately following surgical manipulations, under an Institutional Review Board-approved protocol, with informed consent from all subjects. Video MIOCT imaging of live surgical manipulations was performed in cadaveric porcine eyes by carefully aligning B-scans with instrument orientation and movement. Inverted imaging was performed by lengthening of the reference arm to a position beyond the choroid. Unprocessed MIOCT imaging was successfully obtained in healthy human volunteers and in human patients undergoing surgery, with visualization of post-surgical changes in unprocessed single B-scans. Real-time, unprocessed MIOCT video imaging was successfully obtained in cadaveric porcine eyes during brushing of the retina with the Tano scraper, peeling of superficial retinal tissue with intraocular forceps, and separation of the posterior hyaloid face. Real-time inverted imaging enabled imaging without complex conjugate artifacts. MIOCT is capable of unprocessed imaging of the macula in human patients undergoing surgery and of unprocessed, real-time, video imaging of surgical maneuvers in model eyes. These capabilities represent an important step towards development of MIOCT for efficient, real-time imaging of manipulations during human surgery.

Multiple-image hiding using super resolution reconstruction in high-frequency domains

NASA Astrophysics Data System (ADS)

Li, Xiao-Wei; Zhao, Wu-Xiang; Wang, Jun; Wang, Qiong-Hua

2017-12-01

In this paper, a robust multiple-image hiding method using the computer-generated integral imaging and the modified super-resolution reconstruction algorithm is proposed. In our work, the host image is first transformed into frequency domains by cellular automata (CA), to assure the quality of the stego-image, the secret images are embedded into the CA high-frequency domains. The proposed method has the following advantages: (1) robustness to geometric attacks because of the memory-distributed property of elemental images, (2) increasing quality of the reconstructed secret images as the scheme utilizes the modified super-resolution reconstruction algorithm. The simulation results show that the proposed multiple-image hiding method outperforms other similar hiding methods and is robust to some geometric attacks, e.g., Gaussian noise and JPEG compression attacks.

Review of image processing fundamentals

NASA Technical Reports Server (NTRS)

Billingsley, F. C.

1985-01-01

Image processing through convolution, transform coding, spatial frequency alterations, sampling, and interpolation are considered. It is postulated that convolution in one domain (real or frequency) is equivalent to multiplication in the other (frequency or real), and that the relative amplitudes of the Fourier components must be retained to reproduce any waveshape. It is suggested that all digital systems may be considered equivalent, with a frequency content approximately at the Nyquist limit, and with a Gaussian frequency response. An optimized cubic version of the interpolation continuum image is derived as a set of cubic spines. Pixel replication has been employed to enlarge the visable area of digital samples, however, suitable elimination of the extraneous high frequencies involved in the visable edges, by defocusing, is necessary to allow the underlying object represented by the data values to be seen.

MREG V1.1 : a multi-scale image registration algorithm for SAR applications.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eichel, Paul H.

2013-08-01

MREG V1.1 is the sixth generation SAR image registration algorithm developed by the Signal Processing&Technology Department for Synthetic Aperture Radar applications. Like its predecessor algorithm REGI, it employs a powerful iterative multi-scale paradigm to achieve the competing goals of sub-pixel registration accuracy and the ability to handle large initial offsets. Since it is not model based, it allows for high fidelity tracking of spatially varying terrain-induced misregistration. Since it does not rely on image domain phase, it is equally adept at coherent and noncoherent image registration. This document provides a brief history of the registration processors developed by Dept. 5962more » leading up to MREG V1.1, a full description of the signal processing steps involved in the algorithm, and a user's manual with application specific recommendations for CCD, TwoColor MultiView, and SAR stereoscopy.« less

a Comparative Case Study of Reflection Seismic Imaging Method

NASA Astrophysics Data System (ADS)

Alamooti, M.; Aydin, A.

2017-12-01

Seismic imaging is the most common means of gathering information about subsurface structural features. The accuracy of seismic images may be highly variable depending on the complexity of the subsurface and on how seismic data is processed. One of the crucial steps in this process, especially in layered sequences with complicated structure, is the time and/or depth migration of seismic data.The primary purpose of the migration is to increase the spatial resolution of seismic images by repositioning the recorded seismic signal back to its original point of reflection in time/space, which enhances information about complex structure. In this study, our objective is to process a seismic data set (courtesy of the University of South Carolina) to generate an image on which the Magruder fault near Allendale SC can be clearly distinguished and its attitude can be accurately depicted. The data was gathered by common mid-point method with 60 geophones equally spaced along an about 550 m long traverse over a nearly flat ground. The results obtained from the application of different migration algorithms (including finite-difference and Kirchhoff) are compared in time and depth domains to investigate the efficiency of each algorithm in reducing the processing time and improving the accuracy of seismic images in reflecting the correct position of the Magruder fault.

Infrared and visible image fusion with the target marked based on multi-resolution visual attention mechanisms

NASA Astrophysics Data System (ADS)

Huang, Yadong; Gao, Kun; Gong, Chen; Han, Lu; Guo, Yue

2016-03-01

During traditional multi-resolution infrared and visible image fusion processing, the low contrast ratio target may be weakened and become inconspicuous because of the opposite DN values in the source images. So a novel target pseudo-color enhanced image fusion algorithm based on the modified attention model and fast discrete curvelet transformation is proposed. The interesting target regions are extracted from source images by introducing the motion features gained from the modified attention model, and source images are performed the gray fusion via the rules based on physical characteristics of sensors in curvelet domain. The final fusion image is obtained by mapping extracted targets into the gray result with the proper pseudo-color instead. The experiments show that the algorithm can highlight dim targets effectively and improve SNR of fusion image.

Gabor domain optical coherence microscopy

NASA Astrophysics Data System (ADS)

Murali, Supraja

Time domain Optical Coherence Tomography (TD-OCT), first reported in 1991, makes use of the low temporal coherence properties of a NIR broadband laser to create depth sectioning of up to 2mm under the surface using optical interferometry and point to point scanning. Prior and ongoing work in OCT in the research community has concentrated on improving axial resolution through the development of broadband sources and speed of image acquisition through new techniques such as Spectral domain OCT (SD-OCT). In SD-OCT, an entire depth scan is acquired at once with a low numerical aperture (NA) objective lens focused at a fixed point within the sample. In this imaging geometry, a longer depth of focus is achieved at the expense of lateral resolution, which is typically limited to 10 to 20 mum. Optical Coherence Microscopy (OCM), introduced in 1994, combined the advantages of high axial resolution obtained in OCT with high lateral resolution obtained by increasing the NA of the microscope placed in the sample arm. However, OCM presented trade-offs caused by the inverse quadratic relationship between the NA and the DOF of the optics used. For applications requiring high lateral resolution, such as cancer diagnostics, several solutions have been proposed including the periodic manual re-focusing of the objective lens in the time domain as well as the spectral domain C-mode configuration in order to overcome the loss in lateral resolution outside the DOF. In this research, we report for the first time, high speed, sub-cellular imaging (lateral resolution of 2 mum) in OCM using a Gabor domain image processing algorithm with a custom designed and fabricated dynamic focus microscope interfaced to a Ti:Sa femtosecond laser centered at 800 nm within an SD-OCM configuration. It is envisioned that this technology will provide a non-invasive replacement for the current practice of multiple biopsies for skin cancer diagnosis. The research reported here presents three important advances to this technology all of which have been demonstrated in full functional hardware conceived and built during the course of this research. First, it has been demonstrated that the coherence gate created by the femtosecond laser can be coupled into a scanning optical microscope using optical design methods to include liquid lens technology that enables scanning below the surface of skin with no moving parts and at high resolution throughout a 2x2x2 mm imaging cube. Second, the integration the variable-focus liquid lens technology within a fixed-optics microscope custom optical design helped increase the working NA by an order of magnitude over the limitation imposed by the liquid lens alone. Thus, this design has enabled homogenous axial and lateral resolution at the micron-level (i.e., 2 mum) while imaging in the spectral domain, and still maintaining in vivo speeds. The latest images in biological specimens clearly demonstrate sub-cellular resolution in all dimensions throughout the imaging volume. Third, this new modality for data collection has been integrated with an automated Gabor domain image registration and fusion algorithm to provide full resolution images across the data cube in real-time. We refer to this overall OCM method as Gabor domain OCM (GD-OCM). These advantages place GD-OCM in a unique position with respect to the diagnosis of cancer, because when fully developed, it promises to enable fast and accurate screening for early symptoms that could lead to prevention. The next step for this technology is to apply it directly, in a clinical environment. This step is underway and is expected to be reported by the next generation of researchers within this group.

Time domain simulation of nonlinear acoustic beams generated by rectangular pistons with application to harmonic imaging

NASA Astrophysics Data System (ADS)

Yang, Xinmai; Cleveland, Robin O.

2005-01-01

A time-domain numerical code (the so-called Texas code) that solves the Khokhlov-Zabolotskaya-Kuznetsov (KZK) equation has been extended from an axis-symmetric coordinate system to a three-dimensional (3D) Cartesian coordinate system. The code accounts for diffraction (in the parabolic approximation), nonlinearity and absorption and dispersion associated with thermoviscous and relaxation processes. The 3D time domain code was shown to be in agreement with benchmark solutions for circular and rectangular sources, focused and unfocused beams, and linear and nonlinear propagation. The 3D code was used to model the nonlinear propagation of diagnostic ultrasound pulses through tissue. The prediction of the second-harmonic field was sensitive to the choice of frequency-dependent absorption: a frequency squared f2 dependence produced a second-harmonic field which peaked closer to the transducer and had a lower amplitude than that computed for an f1.1 dependence. In comparing spatial maps of the harmonics we found that the second harmonic had dramatically reduced amplitude in the near field and also lower amplitude side lobes in the focal region than the fundamental. These findings were consistent for both uniform and apodized sources and could be contributing factors in the improved imaging reported with clinical scanners using tissue harmonic imaging. .

Time domain simulation of nonlinear acoustic beams generated by rectangular pistons with application to harmonic imaging.

PubMed

Yang, Xinmai; Cleveland, Robin O

2005-01-01

A time-domain numerical code (the so-called Texas code) that solves the Khokhlov-Zabolotskaya-Kuznetsov (KZK) equation has been extended from an axis-symmetric coordinate system to a three-dimensional (3D) Cartesian coordinate system. The code accounts for diffraction (in the parabolic approximation), nonlinearity and absorption and dispersion associated with thermoviscous and relaxation processes. The 3D time domain code was shown to be in agreement with benchmark solutions for circular and rectangular sources, focused and unfocused beams, and linear and nonlinear propagation. The 3D code was used to model the nonlinear propagation of diagnostic ultrasound pulses through tissue. The prediction of the second-harmonic field was sensitive to the choice of frequency-dependent absorption: a frequency squared f2 dependence produced a second-harmonic field which peaked closer to the transducer and had a lower amplitude than that computed for an f1.1 dependence. In comparing spatial maps of the harmonics we found that the second harmonic had dramatically reduced amplitude in the near field and also lower amplitude side lobes in the focal region than the fundamental. These findings were consistent for both uniform and apodized sources and could be contributing factors in the improved imaging reported with clinical scanners using tissue harmonic imaging.

Lossless Compression of JPEG Coded Photo Collections.

PubMed

Wu, Hao; Sun, Xiaoyan; Yang, Jingyu; Zeng, Wenjun; Wu, Feng

2016-04-06

The explosion of digital photos has posed a significant challenge to photo storage and transmission for both personal devices and cloud platforms. In this paper, we propose a novel lossless compression method to further reduce the size of a set of JPEG coded correlated images without any loss of information. The proposed method jointly removes inter/intra image redundancy in the feature, spatial, and frequency domains. For each collection, we first organize the images into a pseudo video by minimizing the global prediction cost in the feature domain. We then present a hybrid disparity compensation method to better exploit both the global and local correlations among the images in the spatial domain. Furthermore, the redundancy between each compensated signal and the corresponding target image is adaptively reduced in the frequency domain. Experimental results demonstrate the effectiveness of the proposed lossless compression method. Compared to the JPEG coded image collections, our method achieves average bit savings of more than 31%.

Image characterization by fractal descriptors in variational mode decomposition domain: Application to brain magnetic resonance

NASA Astrophysics Data System (ADS)

Lahmiri, Salim

2016-08-01

The main purpose of this work is to explore the usefulness of fractal descriptors estimated in multi-resolution domains to characterize biomedical digital image texture. In this regard, three multi-resolution techniques are considered: the well-known discrete wavelet transform (DWT) and the empirical mode decomposition (EMD), and; the newly introduced; variational mode decomposition mode (VMD). The original image is decomposed by the DWT, EMD, and VMD into different scales. Then, Fourier spectrum based fractal descriptors is estimated at specific scales and directions to characterize the image. The support vector machine (SVM) was used to perform supervised classification. The empirical study was applied to the problem of distinguishing between normal and abnormal brain magnetic resonance images (MRI) affected with Alzheimer disease (AD). Our results demonstrate that fractal descriptors estimated in VMD domain outperform those estimated in DWT and EMD domains; and also those directly estimated from the original image.

Validation of CT dose-reduction simulation

PubMed Central

Massoumzadeh, Parinaz; Don, Steven; Hildebolt, Charles F.; Bae, Kyongtae T.; Whiting, Bruce R.

2009-01-01

The objective of this research was to develop and validate a custom computed tomography dose-reduction simulation technique for producing images that have an appearance consistent with the same scan performed at a lower mAs (with fixed kVp, rotation time, and collimation). Synthetic noise is added to projection (sinogram) data, incorporating a stochastic noise model that includes energy-integrating detectors, tube-current modulation, bowtie beam filtering, and electronic system noise. Experimental methods were developed to determine the parameters required for each component of the noise model. As a validation, the outputs of the simulations were compared to measurements with cadavers in the image domain and with phantoms in both the sinogram and image domain, using an unbiased root-mean-square relative error metric to quantify agreement in noise processes. Four-alternative forced-choice (4AFC) observer studies were conducted to confirm the realistic appearance of simulated noise, and the effects of various system model components on visual noise were studied. The “just noticeable difference (JND)” in noise levels was analyzed to determine the sensitivity of observers to changes in noise level. Individual detector measurements were shown to be normally distributed (p>0.54), justifying the use of a Gaussian random noise generator for simulations. Phantom tests showed the ability to match original and simulated noise variance in the sinogram domain to within 5.6%±1.6% (standard deviation), which was then propagated into the image domain with errors less than 4.1%±1.6%. Cadaver measurements indicated that image noise was matched to within 2.6%±2.0%. More importantly, the 4AFC observer studies indicated that the simulated images were realistic, i.e., no detectable difference between simulated and original images (p=0.86) was observed. JND studies indicated that observers’ sensitivity to change in noise levels corresponded to a 25% difference in dose, which is far larger than the noise accuracy achieved by simulation. In summary, the dose-reduction simulation tool demonstrated excellent accuracy in providing realistic images. The methodology promises to be a useful tool for researchers and radiologists to explore dose reduction protocols in an effort to produce diagnostic images with radiation dose “as low as reasonably achievable.” PMID:19235386

The Impact of Cognitive Training on Cerebral White Matter in Community-Dwelling Elderly: One-Year Prospective Longitudinal Diffusion Tensor Imaging Study.

PubMed

Cao, Xinyi; Yao, Ye; Li, Ting; Cheng, Yan; Feng, Wei; Shen, Yuan; Li, Qingwei; Jiang, Lijuan; Wu, Wenyuan; Wang, Jijun; Sheng, Jianhua; Feng, Jianfeng; Li, Chunbo

2016-09-15

It has been shown that cognitive training (CogTr) is effective and recuperative for older adults, and can be used to fight against cognitive decline. In this study, we investigated whether behavioural gains from CogTr would extend to white matter (WM) microstructure, and whether training-induced changes in WM integrity would be associated with improvements in cognitive function, using diffusion tensor imaging (DTI). 48 healthy community elderly were either assigned to multi-domain or single-domain CogTr groups to receive 24 sessions over 12 weeks, or to a control group. DTI was performed at both baseline and 12-month follow-up. Positive effects of multi-domain CogTr on long-term changes in DTI indices were found in posterior parietal WM. Participants in the multi-domain group showed a trend of long-term decrease in axial diffusivity (AD) without significant change in fractional anisotropy (FA), mean diffusivity (MD) or radial diffusivity (RD), while those in the control group displayed a significant FA decrease, and an increase in MD and RD. In addition, significant relationships between an improvement in processing speed and changes in RD, MD and AD were found in the multi-domain group. These findings support the hypothesis that plasticity of WM can be modified by CogTr, even in late adulthood.

A secure online image trading system for untrusted cloud environments.

PubMed

Munadi, Khairul; Arnia, Fitri; Syaryadhi, Mohd; Fujiyoshi, Masaaki; Kiya, Hitoshi

2015-01-01

In conventional image trading systems, images are usually stored unprotected on a server, rendering them vulnerable to untrusted server providers and malicious intruders. This paper proposes a conceptual image trading framework that enables secure storage and retrieval over Internet services. The process involves three parties: an image publisher, a server provider, and an image buyer. The aim is to facilitate secure storage and retrieval of original images for commercial transactions, while preventing untrusted server providers and unauthorized users from gaining access to true contents. The framework exploits the Discrete Cosine Transform (DCT) coefficients and the moment invariants of images. Original images are visually protected in the DCT domain, and stored on a repository server. Small representation of the original images, called thumbnails, are generated and made publicly accessible for browsing. When a buyer is interested in a thumbnail, he/she sends a query to retrieve the visually protected image. The thumbnails and protected images are matched using the DC component of the DCT coefficients and the moment invariant feature. After the matching process, the server returns the corresponding protected image to the buyer. However, the image remains visually protected unless a key is granted. Our target application is the online market, where publishers sell their stock images over the Internet using public cloud servers.

Frequency Domain Ultrasound Waveform Tomography: Breast Imaging Using a Ring Transducer

PubMed Central

Sandhu, G Y; Li, C; Roy, O; Schmidt, S; Duric, N

2016-01-01

Application of the frequency domain acoustic wave equation on data acquired from ultrasound tomography scans is shown to yield high resolution sound speed images on the order of the wavelength of the highest reconstructed frequency. Using a signal bandwidth of 0.4–1 MHz and an average sound speed of 1500 m/s, the resolution is approximately 1.5 mm. The quantitative sound speed values and morphology provided by these images have the potential to inform diagnosis and classification of breast disease. In this study, we present the formalism, practical application, and in vivo results of waveform tomography applied to breast data gathered by two different ultrasound tomography scanners that utilize ring transducers. The formalism includes a review of frequency domain modeling of the wave equation using finite difference operators as well as a review of the gradient descent method for the iterative reconstruction scheme. It is shown that the practical application of waveform tomography requires an accurate starting model, careful data processing, and a method to gradually incorporate higher frequency information into the sound speed reconstruction. Following these steps resulted in high resolution quantitative sound speed images of the breast. These images show marked improvement relative to commonly used ray tomography reconstruction methods. The robustness of the method is demonstrated by obtaining similar results from two different ultrasound tomography devices. We also compare our method to MRI to demonstrate concordant findings. The clinical data used in this work was obtained from a HIPAA compliant clinical study (IRB 040912M1F). PMID:26110909

Chirp Scaling Algorithms for SAR Processing

NASA Technical Reports Server (NTRS)

Jin, M.; Cheng, T.; Chen, M.

1993-01-01

The chirp scaling SAR processing algorithm is both accurate and efficient. Successful implementation requires proper selection of the interval of output samples, which is a function of the chirp interval, signal sampling rate, and signal bandwidth. Analysis indicates that for both airborne and spaceborne SAR applications in the slant range domain a linear chirp scaling is sufficient. To perform nonlinear interpolation process such as to output ground range SAR images, one can use a nonlinear chirp scaling interpolator presented in this paper.

Extracting and compensating dispersion mismatch in ultrahigh-resolution Fourier domain OCT imaging of the retina

PubMed Central

Choi, WooJhon; Baumann, Bernhard; Swanson, Eric A.; Fujimoto, James G.

2012-01-01

We present a numerical approach to extract the dispersion mismatch in ultrahigh-resolution Fourier domain optical coherence tomography (OCT) imaging of the retina. The method draws upon an analogy with a Shack-Hartmann wavefront sensor. By exploiting mathematical similarities between the expressions for aberration in optical imaging and dispersion mismatch in spectral / Fourier domain OCT, Shack-Hartmann principles can be extended from the two-dimensional paraxial wavevector space (or the x-y plane in the spatial domain) to the one-dimensional wavenumber space (or the z-axis in the spatial domain). For OCT imaging of the retina, different retinal layers, such as the retinal nerve fiber layer (RNFL), the photoreceptor inner and outer segment junction (IS/OS), or all the retinal layers near the retinal pigment epithelium (RPE) can be used as point source beacons in the axial direction, analogous to point source beacons used in conventional two-dimensional Shack-Hartman wavefront sensors for aberration characterization. Subtleties regarding speckle phenomena in optical imaging, which affect the Shack-Hartmann wavefront sensor used in adaptive optics, also occur analogously in this application. Using this approach and carefully suppressing speckle, the dispersion mismatch in spectral / Fourier domain OCT retinal imaging can be successfully extracted numerically and used for numerical dispersion compensation to generate sharper, ultrahigh-resolution OCT images. PMID:23187353

Interferometrically enhanced sub-terahertz picosecond imaging utilizing a miniature collapsing-field-domain source

NASA Astrophysics Data System (ADS)

Vainshtein, Sergey N.; Duan, Guoyong; Mikhnev, Valeri A.; Zemlyakov, Valery E.; Egorkin, Vladimir I.; Kalyuzhnyy, Nikolay A.; Maleev, Nikolai A.; Näpänkangas, Juha; Sequeiros, Roberto Blanco; Kostamovaara, Juha T.

2018-05-01

Progress in terahertz spectroscopy and imaging is mostly associated with femtosecond laser-driven systems, while solid-state sources, mainly sub-millimetre integrated circuits, are still in an early development phase. As simple and cost-efficient an emitter as a Gunn oscillator could cause a breakthrough in the field, provided its frequency limitations could be overcome. Proposed here is an application of the recently discovered collapsing field domains effect that permits sub-THz oscillations in sub-micron semiconductor layers thanks to nanometer-scale powerfully ionizing domains arising due to negative differential mobility in extreme fields. This shifts the frequency limit by an order of magnitude relative to the conventional Gunn effect. Our first miniature picosecond pulsed sources cover the 100-200 GHz band and promise milliwatts up to ˜500 GHz. Thanks to the method of interferometrically enhanced time-domain imaging proposed here and the low single-shot jitter of ˜1 ps, our simple imaging system provides sufficient time-domain imaging contrast for fresh-tissue terahertz histology.

Wavefront sensorless adaptive optics optical coherence tomography for in vivo retinal imaging in mice

PubMed Central

Jian, Yifan; Xu, Jing; Gradowski, Martin A.; Bonora, Stefano; Zawadzki, Robert J.; Sarunic, Marinko V.

2014-01-01

We present wavefront sensorless adaptive optics (WSAO) Fourier domain optical coherence tomography (FD-OCT) for in vivo small animal retinal imaging. WSAO is attractive especially for mouse retinal imaging because it simplifies optical design and eliminates the need for wavefront sensing, which is difficult in the small animal eye. GPU accelerated processing of the OCT data permitted real-time extraction of image quality metrics (intensity) for arbitrarily selected retinal layers to be optimized. Modal control of a commercially available segmented deformable mirror (IrisAO Inc.) provided rapid convergence using a sequential search algorithm. Image quality improvements with WSAO OCT are presented for both pigmented and albino mouse retinal data, acquired in vivo. PMID:24575347

Combining textual and visual information for image retrieval in the medical domain.

PubMed

Gkoufas, Yiannis; Morou, Anna; Kalamboukis, Theodore

2011-01-01

In this article we have assembled the experience obtained from our participation in the imageCLEF evaluation task over the past two years. Exploitation on the use of linear combinations for image retrieval has been attempted by combining visual and textual sources of images. From our experiments we conclude that a mixed retrieval technique that applies both textual and visual retrieval in an interchangeably repeated manner improves the performance while overcoming the scalability limitations of visual retrieval. In particular, the mean average precision (MAP) has increased from 0.01 to 0.15 and 0.087 for 2009 and 2010 data, respectively, when content-based image retrieval (CBIR) is performed on the top 1000 results from textual retrieval based on natural language processing (NLP).

Reliable clarity automatic-evaluation method for optical remote sensing images

NASA Astrophysics Data System (ADS)

Qin, Bangyong; Shang, Ren; Li, Shengyang; Hei, Baoqin; Liu, Zhiwen

2015-10-01

Image clarity, which reflects the sharpness degree at the edge of objects in images, is an important quality evaluate index for optical remote sensing images. Scholars at home and abroad have done a lot of work on estimation of image clarity. At present, common clarity-estimation methods for digital images mainly include frequency-domain function methods, statistical parametric methods, gradient function methods and edge acutance methods. Frequency-domain function method is an accurate clarity-measure approach. However, its calculation process is complicate and cannot be carried out automatically. Statistical parametric methods and gradient function methods are both sensitive to clarity of images, while their results are easy to be affected by the complex degree of images. Edge acutance method is an effective approach for clarity estimate, while it needs picking out the edges manually. Due to the limits in accuracy, consistent or automation, these existing methods are not applicable to quality evaluation of optical remote sensing images. In this article, a new clarity-evaluation method, which is based on the principle of edge acutance algorithm, is proposed. In the new method, edge detection algorithm and gradient search algorithm are adopted to automatically search the object edges in images. Moreover, The calculation algorithm for edge sharpness has been improved. The new method has been tested with several groups of optical remote sensing images. Compared with the existing automatic evaluation methods, the new method perform better both in accuracy and consistency. Thus, the new method is an effective clarity evaluation method for optical remote sensing images.

Imaging resin infiltration into non-cavitated carious lesions by optical coherence tomography.

PubMed

Schneider, Hartmut; Park, Kyung-Jin; Rueger, Claudia; Ziebolz, Dirk; Krause, Felix; Haak, Rainer

2017-05-01

Visualisation of the etching process and resin penetration at white spot carious lesions by spectral domain optical coherence tomography (SD-OCT). The non-cavitated carious lesions (ICDAS code 2) of four visually preselected extracted human molars and premolars were verified as enamel lesions by micro computed tomography (μCT). One region of interest (ROI) per tooth was marked by two drill-holes in occlusal-cervical direction. The lesions were imaged by SD-OCT. Lesions were infiltrated (Icon, DMG) according to the manufacturer's instructions. During each treatment step and after light curing of the infiltrant, the ROIs were imaged again by SD-OCT. Teeth were sectioned through the ROIs and section layers were imaged by scanning electron microscopy in order to compare with the OCT images. The image sequences for etching and infiltration were viewed in time lapse. During the etching process, numerous bubbles formed on the lesion surface. Using OCT, the process of resin penetration into the carious lesion body became visible. The early enamel carious lesion was completely infiltrated by the resin whereas infiltration of the advanced enamel carious lesion was incomplete and inhomogeneous. Resin infiltration can be increased by optimizing the etching process. Optical coherence tomography provides information about the process and degree of resin infiltration. Active acid application before resin infiltration is recommendable. Copyright © 2017 Elsevier Ltd. All rights reserved.

Ultrasonic Phased Array Compressive Imaging in Time and Frequency Domain: Simulation, Experimental Verification and Real Application

PubMed Central

Bai, Zhiliang; Chen, Shili; Jia, Lecheng; Zeng, Zhoumo

2018-01-01

Embracing the fact that one can recover certain signals and images from far fewer measurements than traditional methods use, compressive sensing (CS) provides solutions to huge amounts of data collection in phased array-based material characterization. This article describes how a CS framework can be utilized to effectively compress ultrasonic phased array images in time and frequency domains. By projecting the image onto its Discrete Cosine transform domain, a novel scheme was implemented to verify the potentiality of CS for data reduction, as well as to explore its reconstruction accuracy. The results from CIVA simulations indicate that both time and frequency domain CS can accurately reconstruct array images using samples less than the minimum requirements of the Nyquist theorem. For experimental verification of three types of artificial flaws, although a considerable data reduction can be achieved with defects clearly preserved, it is currently impossible to break Nyquist limitation in the time domain. Fortunately, qualified recovery in the frequency domain makes it happen, meaning a real breakthrough for phased array image reconstruction. As a case study, the proposed CS procedure is applied to the inspection of an engine cylinder cavity containing different pit defects and the results show that orthogonal matching pursuit (OMP)-based CS guarantees the performance for real application. PMID:29738452

Inversion domain boundaries in ZnO with additions of Fe2O3 studied by high-resolution ADF imaging.

PubMed

Wolf, Frank; Freitag, Bert H; Mader, Werner

2007-01-01

Columns of metal atoms in the polytypoid compound Fe2O3(ZnO)15 could be resolved by high angle annular dark field imaging in a transmission electron microscopy (TEM)/STEM electron microscope--a result which could not be realized by high-resolution bright field imaging due to inherent strain from inversion domains and inversion domain boundaries (IDBs) in the crystals. The basal plane IDB was imaged in [11 00] yielding the spacing of the two adjacent ZnO domains, while imaging in [21 1 0] yields the position of single metal ions. The images allow the construction of the entire domain structure including the stacking sequence and positions of the oxygen ions. The IDB consists of a single layer of octahedrally co-ordinated Fe3+ ions, and the inverted ZnO domains are related by point symmetry at the iron position. The FeO6 octahedrons are compressed along the ZnO c-axis resulting in a FeO bond length of 0.208 nm which is in the range of FeO distances in iron containing oxides. The model of the basal plane boundary resembles that of the IDB in polytypoid ZnO-In2O3 compounds.

Depth resolved hyperspectral imaging spectrometer based on structured light illumination and Fourier transform interferometry

PubMed Central

Choi, Heejin; Wadduwage, Dushan; Matsudaira, Paul T.; So, Peter T.C.

2014-01-01

A depth resolved hyperspectral imaging spectrometer can provide depth resolved imaging both in the spatial and the spectral domain. Images acquired through a standard imaging Fourier transform spectrometer do not have the depth-resolution. By post processing the spectral cubes (x, y, λ) obtained through a Sagnac interferometer under uniform illumination and structured illumination, spectrally resolved images with depth resolution can be recovered using structured light illumination algorithms such as the HiLo method. The proposed scheme is validated with in vitro specimens including fluorescent solution and fluorescent beads with known spectra. The system is further demonstrated in quantifying spectra from 3D resolved features in biological specimens. The system has demonstrated depth resolution of 1.8 μm and spectral resolution of 7 nm respectively. PMID:25360367

A review of automated image understanding within 3D baggage computed tomography security screening.

PubMed

Mouton, Andre; Breckon, Toby P

2015-01-01

Baggage inspection is the principal safeguard against the transportation of prohibited and potentially dangerous materials at airport security checkpoints. Although traditionally performed by 2D X-ray based scanning, increasingly stringent security regulations have led to a growing demand for more advanced imaging technologies. The role of X-ray Computed Tomography is thus rapidly expanding beyond the traditional materials-based detection of explosives. The development of computer vision and image processing techniques for the automated understanding of 3D baggage-CT imagery is however, complicated by poor image resolutions, image clutter and high levels of noise and artefacts. We discuss the recent and most pertinent advancements and identify topics for future research within the challenging domain of automated image understanding for baggage security screening CT.

Improving the signal analysis for in vivo photoacoustic flow cytometry

NASA Astrophysics Data System (ADS)

Niu, Zhenyu; Yang, Ping; Wei, Dan; Tang, Shuo; Wei, Xunbin

2015-03-01

At early stage of cancer, a small number of circulating tumor cells (CTCs) appear in the blood circulation. Thus, early detection of malignant circulating tumor cells has great significance for timely treatment to reduce the cancer death rate. We have developed an in vivo photoacoustic flow cytometry (PAFC) to monitor the metastatic process of CTCs and record the signals from target cells. Information of target cells which is helpful to the early therapy would be obtained through analyzing and processing the signals. The raw signal detected from target cells often contains some noise caused by electronic devices, such as background noise and thermal noise. We choose the Wavelet denoising method to effectively distinguish the target signal from background noise. Processing in time domain and frequency domain would be combined to analyze the signal after denoising. This algorithm contains time domain filter and frequency transformation. The frequency spectrum image of the signal contains distinctive features that can be used to analyze the property of target cells or particles. The PAFC technique can detect signals from circulating tumor cells or other particles. The processing methods have a great potential for analyzing signals accurately and rapidly.

A Scientific Workflow Platform for Generic and Scalable Object Recognition on Medical Images

NASA Astrophysics Data System (ADS)

Möller, Manuel; Tuot, Christopher; Sintek, Michael

In the research project THESEUS MEDICO we aim at a system combining medical image information with semantic background knowledge from ontologies to give clinicians fully cross-modal access to biomedical image repositories. Therefore joint efforts have to be made in more than one dimension: Object detection processes have to be specified in which an abstraction is performed starting from low-level image features across landmark detection utilizing abstract domain knowledge up to high-level object recognition. We propose a system based on a client-server extension of the scientific workflow platform Kepler that assists the collaboration of medical experts and computer scientists during development and parameter learning.

Hypercomplex Fourier transforms of color images.

PubMed

Ell, Todd A; Sangwine, Stephen J

2007-01-01

Fourier transforms are a fundamental tool in signal and image processing, yet, until recently, there was no definition of a Fourier transform applicable to color images in a holistic manner. In this paper, hypercomplex numbers, specifically quaternions, are used to define a Fourier transform applicable to color images. The properties of the transform are developed, and it is shown that the transform may be computed using two standard complex fast Fourier transforms. The resulting spectrum is explained in terms of familiar phase and modulus concepts, and a new concept of hypercomplex axis. A method for visualizing the spectrum using color graphics is also presented. Finally, a convolution operational formula in the spectral domain is discussed.

The increasing influence of medical image processing in clinical neuroimaging.

PubMed

Barillot, Christian

2007-01-20

This paper review the evolution of clinical neuroinformatics domain in the passed and gives an outlook how this research field will evolve in clinical neurology (e.g. Epilepsy, Multiple Sclerosis, Dementia) and neurosurgery (e.g. image guided surgery, intra-operative imaging, the definition of the Operation Room of the future). These different issues, as addressed by the VisAGeS research team, are discussed in more details and the benefits of a close collaboration between clinical scientists (radiologist, neurologist and neurosurgeon) and computer scientists are shown to give adequate answers to the series of problems which needs to be solved for a more effective use of medical images in clinical neurosciences.

New software developments for quality mesh generation and optimization from biomedical imaging data.

PubMed

Yu, Zeyun; Wang, Jun; Gao, Zhanheng; Xu, Ming; Hoshijima, Masahiko

2014-01-01

In this paper we present a new software toolkit for generating and optimizing surface and volumetric meshes from three-dimensional (3D) biomedical imaging data, targeted at image-based finite element analysis of some biomedical activities in a single material domain. Our toolkit includes a series of geometric processing algorithms including surface re-meshing and quality-guaranteed tetrahedral mesh generation and optimization. All methods described have been encapsulated into a user-friendly graphical interface for easy manipulation and informative visualization of biomedical images and mesh models. Numerous examples are presented to demonstrate the effectiveness and efficiency of the described methods and toolkit. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Imaging Crustal Structure of East Central United States using receiver function and implications for the accretion of juvenile crust

NASA Astrophysics Data System (ADS)

Deng, S.; Levander, A.

2017-12-01

Almost half of the North American continental plate is formed by the juvenile terrane accretion between 1.8-1.0 Ga, therefore, the suturing process of juvenile crust in East Central United States, not receiving as much attention probably due to low station coverage before the deployment of US transportable array, is of great importance to better understand the evolution of North American Plate. The Yavapai province is formed by the accretion of juvenile crust during 1.8-1.7 Ga. The northeastern part of Yavapai province is accreted to the Superior province along the Spirit Lake Tectonic Zone (SLTZ). During the period of 1.7-1.6 Ga, the Mazatzal Province, bounded the south of Yavapai Province, was added to Laurentia. The previous research mainly focuses on the southwestern Yavapai-Mazatzal boundary (Karlstrom et.al 2002, Magnani et.al 2004) but less in the northeastern area that we are interested in. The Granite-Rhyolite province is the product of the suturing event of juvenile arc crust reoccurring along the southeast margin of Laurentia between 1.55-1.35 Ga, which has been proved by the Nd model age (Whitmeyer et.al 2007). Here we will select the Mw>=5.5 teleseismic events with epicenter distance between 35 and 90 recorded by 300 available seismic stations in our study region. The receiver functions will be calculated by the water-level deconvolution in frequency domain (Langston 1979) and iterative deconvolution in time domain (Ligorria et.al 1999). The common conversion point (CCP) stacking method will then be applied to the receiver functions to create the 3-D image volume by imaging the conversion points in space from the time domain signals (Levander and Miller 2012). The preliminary results show that the accretion process of the tectonic provinces may have different models. The profiles of CCP image volume will inform us the seismic evidence to model the suturing process of juvenile Yavapai, Mozatzal and Granite-Rhyolite crust, hence providing great indication to interpret the growth of the North American plate. The updated results will be presented in the meeting.

The Impact of Image Management, Self-Justification, and Escalation of Commitment on Knowledge Development in the Marketing Discipline

ERIC Educational Resources Information Center

Sharmaa, Dheeraj; Albers-Miller, Nancy D.; Pelton, Lou E.; Straughan, Robert D.

2006-01-01

The paramount role of scholarship in the modern academic environment is manifest across program accreditation, individual evaluation, and institutional reputation processes. At the microlevel, success in this domain positively influences scholars' performance evaluations and institutions' external reputations. At the macrolevel, research expands…

Characterization of PET preforms using spectral domain optical coherence tomography

NASA Astrophysics Data System (ADS)

Hosseiny, Hamid; Ferreira, Manuel João.; Martins, Teresa; Carmelo Rosa, Carla

2013-11-01

Polyethylene terephthalate (PET) preforms are massively produced nowadays with the purpose of producing food and beverages packaging and liquid containers. Some varieties of these preforms are produced as multilayer structures, where very thin inner film(s) act as a barrier for nutrients leakage. The knowledge of the thickness of this thin inner layer is important in the production line. The quality control of preforms production requires a fast approach and normally the thickness control is performed by destructive means out of the production line. A spectral domain optical coherence tomography (SD-OCT) method was proposed to examine the thin layers in real time. This paper describes a nondestructive approach and all required signal processing steps to characterize the thin inner layers and also to improve the imaging speed and the signal to noise ratio. The algorithm was developed by using graphics processing unit (GPU) with computer unified device architecture (CUDA). This GPU-accelerated white light interferometry technique nondestructively assesses the samples and has high imaging speed advantage, overcoming the bottlenecks in PET performs quality control.

Deep neural network-based domain adaptation for classification of remote sensing images

NASA Astrophysics Data System (ADS)

Ma, Li; Song, Jiazhen

2017-10-01

We investigate the effectiveness of deep neural network for cross-domain classification of remote sensing images in this paper. In the network, class centroid alignment is utilized as a domain adaptation strategy, making the network able to transfer knowledge from the source domain to target domain on a per-class basis. Since predicted labels of target data should be used to estimate the centroid of each class, we use overall centroid alignment as a coarse domain adaptation method to improve the estimation accuracy. In addition, rectified linear unit is used as the activation function to produce sparse features, which may improve the separation capability. The proposed network can provide both aligned features and an adaptive classifier, as well as obtain label-free classification of target domain data. The experimental results using Hyperion, NCALM, and WorldView-2 remote sensing images demonstrated the effectiveness of the proposed approach.

Thermography-based blood flow imaging in human skin of the hands and feet: a spectral filtering approach.

PubMed

Sagaidachnyi, A A; Fomin, A V; Usanov, D A; Skripal, A V

2017-02-01

The determination of the relationship between skin blood flow and skin temperature dynamics is the main problem in thermography-based blood flow imaging. Oscillations in skin blood flow are the source of thermal waves propagating from micro-vessels toward the skin's surface, as assumed in this study. This hypothesis allows us to use equations for the attenuation and dispersion of thermal waves for converting the temperature signal into the blood flow signal, and vice versa. We developed a spectral filtering approach (SFA), which is a new technique for thermography-based blood flow imaging. In contrast to other processing techniques, the SFA implies calculations in the spectral domain rather than in the time domain. Therefore, it eliminates the need to solve differential equations. The developed technique was verified within 0.005-0.1 Hz, including the endothelial, neurogenic and myogenic frequency bands of blood flow oscillations. The algorithm for an inverse conversion of the blood flow signal into the skin temperature signal is addressed. The examples of blood flow imaging of hands during cuff occlusion and feet during heating of the back are illustrated. The processing of infrared (IR) thermograms using the SFA allowed us to restore the blood flow signals and achieve correlations of about 0.8 with a waveform of a photoplethysmographic signal. The prospective applications of the thermography-based blood flow imaging technique include non-contact monitoring of the blood supply during engraftment of skin flaps and burns healing, as well the use of contact temperature sensors to monitor low-frequency oscillations of peripheral blood flow.

Noise analysis for near-field 3D FM-CW radar imaging systems

NASA Astrophysics Data System (ADS)

Sheen, David M.

2015-05-01

Near field radar imaging systems are used for demanding security applications including concealed weapon detection in airports and other high-security venues. Despite the near-field operation, phase noise and thermal noise can limit performance in several ways. Practical imaging systems can employ arrays with low gain antennas and relatively large signal distribution networks that have substantial losses which limit transmit power and increase the effective noise figure of the receiver chain, resulting in substantial thermal noise. Phase noise can also limit system performance. The signal coupled from transmitter to receiver is much larger than expected target signals. Phase noise from this coupled signal can set the system noise floor if the oscillator is too noisy. Frequency modulated continuous wave (FM-CW) radar transceivers used in short range systems are relatively immune to the effects of the coupled phase noise due to range correlation effects. This effect can reduce the phase-noise floor such that it is below the thermal noise floor for moderate performance oscillators. Phase noise is also manifested in the range response around bright targets, and can cause smaller targets to be obscured. Noise in synthetic aperture imaging systems is mitigated by the processing gain of the system. In this paper, the effects of thermal noise, phase noise, and processing gain are analyzed in the context of a near field 3-D FM-CW imaging radar as might be used for concealed weapon detection. In addition to traditional frequency domain analysis, a time-domain simulation is employed to graphically demonstrate the effect of these noise sources on a fast-chirping FM-CW system.

Medium-throughput processing of whole mount in situ hybridisation experiments into gene expression domains.

PubMed

Crombach, Anton; Cicin-Sain, Damjan; Wotton, Karl R; Jaeger, Johannes

2012-01-01

Understanding the function and evolution of developmental regulatory networks requires the characterisation and quantification of spatio-temporal gene expression patterns across a range of systems and species. However, most high-throughput methods to measure the dynamics of gene expression do not preserve the detailed spatial information needed in this context. For this reason, quantification methods based on image bioinformatics have become increasingly important over the past few years. Most available approaches in this field either focus on the detailed and accurate quantification of a small set of gene expression patterns, or attempt high-throughput analysis of spatial expression through binary pattern extraction and large-scale analysis of the resulting datasets. Here we present a robust, "medium-throughput" pipeline to process in situ hybridisation patterns from embryos of different species of flies. It bridges the gap between high-resolution, and high-throughput image processing methods, enabling us to quantify graded expression patterns along the antero-posterior axis of the embryo in an efficient and straightforward manner. Our method is based on a robust enzymatic (colorimetric) in situ hybridisation protocol and rapid data acquisition through wide-field microscopy. Data processing consists of image segmentation, profile extraction, and determination of expression domain boundary positions using a spline approximation. It results in sets of measured boundaries sorted by gene and developmental time point, which are analysed in terms of expression variability or spatio-temporal dynamics. Our method yields integrated time series of spatial gene expression, which can be used to reverse-engineer developmental gene regulatory networks across species. It is easily adaptable to other processes and species, enabling the in silico reconstitution of gene regulatory networks in a wide range of developmental contexts.

A proxy of DICOM services

NASA Astrophysics Data System (ADS)

Ribeiro, Luís S.; Costa, Carlos; Oliveira, José Luís

2010-03-01

Diagnostic tools supported by digital medical images have increasingly become an essential aid to medical decisions. However, despite its growing importance, Picture Archiving and Communication Systems (PACS) are typically oriented to support a single healthcare institution, and the sharing of medical data across institutions is still a difficult process. This paper describes a proposal to publish and control Digital Imaging Communications in Medicine (DICOM) services in a wide domain composed of several healthcare institutions. The system creates virtual bridges between intranets enabling the exchange, search and store of the medical data within the wide domain. The service provider publishes the DICOM services following a token-based strategy. The token advertisements are public and known by all system users. However, access to the DICOM service is controlled through a role association between an access key and the service. Furthermore, in medical diagnoses, time is a crucial factor. Therefore, our system is a turnkey solution, capable of exchanging medical data across firewalls and Network Address Translation (NAT), avoiding bureaucratic issues with local network security. Security is also an important concern - in any transmission across different domains, data is encrypted by Transport Layer Security (TLS).

Reduction of Poisson noise in measured time-resolved data for time-domain diffuse optical tomography.

PubMed

Okawa, S; Endo, Y; Hoshi, Y; Yamada, Y

2012-01-01

A method to reduce noise for time-domain diffuse optical tomography (DOT) is proposed. Poisson noise which contaminates time-resolved photon counting data is reduced by use of maximum a posteriori estimation. The noise-free data are modeled as a Markov random process, and the measured time-resolved data are assumed as Poisson distributed random variables. The posterior probability of the occurrence of the noise-free data is formulated. By maximizing the probability, the noise-free data are estimated, and the Poisson noise is reduced as a result. The performances of the Poisson noise reduction are demonstrated in some experiments of the image reconstruction of time-domain DOT. In simulations, the proposed method reduces the relative error between the noise-free and noisy data to about one thirtieth, and the reconstructed DOT image was smoothed by the proposed noise reduction. The variance of the reconstructed absorption coefficients decreased by 22% in a phantom experiment. The quality of DOT, which can be applied to breast cancer screening etc., is improved by the proposed noise reduction.

Master-slave interferometry for parallel spectral domain interferometry sensing and versatile 3D optical coherence tomography.

PubMed

Podoleanu, Adrian Gh; Bradu, Adrian

2013-08-12

Conventional spectral domain interferometry (SDI) methods suffer from the need of data linearization. When applied to optical coherence tomography (OCT), conventional SDI methods are limited in their 3D capability, as they cannot deliver direct en-face cuts. Here we introduce a novel SDI method, which eliminates these disadvantages. We denote this method as Master - Slave Interferometry (MSI), because a signal is acquired by a slave interferometer for an optical path difference (OPD) value determined by a master interferometer. The MSI method radically changes the main building block of an SDI sensor and of a spectral domain OCT set-up. The serially provided signal in conventional technology is replaced by multiple signals, a signal for each OPD point in the object investigated. This opens novel avenues in parallel sensing and in parallelization of signal processing in 3D-OCT, with applications in high- resolution medical imaging and microscopy investigation of biosamples. Eliminating the need of linearization leads to lower cost OCT systems and opens potential avenues in increasing the speed of production of en-face OCT images in comparison with conventional SDI.

Metal Artifact Suppression in Dental Cone Beam Computed Tomography Images Using Image Processing Techniques.

PubMed

Johari, Masoumeh; Abdollahzadeh, Milad; Esmaeili, Farzad; Sakhamanesh, Vahideh

2018-01-01

Dental cone beam computed tomography (CBCT) images suffer from severe metal artifacts. These artifacts degrade the quality of acquired image and in some cases make it unsuitable to use. Streaking artifacts and cavities around teeth are the main reason of degradation. In this article, we have proposed a new artifact reduction algorithm which has three parallel components. The first component extracts teeth based on the modeling of image histogram with a Gaussian mixture model. Striking artifact reduction component reduces artifacts using converting image into the polar domain and applying morphological filtering. The third component fills cavities through a simple but effective morphological filtering operation. Finally, results of these three components are combined into a fusion step to create a visually good image which is more compatible to human visual system. Results show that the proposed algorithm reduces artifacts of dental CBCT images and produces clean images.

Metal Artifact Suppression in Dental Cone Beam Computed Tomography Images Using Image Processing Techniques

PubMed Central

Johari, Masoumeh; Abdollahzadeh, Milad; Esmaeili, Farzad; Sakhamanesh, Vahideh

2018-01-01

Background: Dental cone beam computed tomography (CBCT) images suffer from severe metal artifacts. These artifacts degrade the quality of acquired image and in some cases make it unsuitable to use. Streaking artifacts and cavities around teeth are the main reason of degradation. Methods: In this article, we have proposed a new artifact reduction algorithm which has three parallel components. The first component extracts teeth based on the modeling of image histogram with a Gaussian mixture model. Striking artifact reduction component reduces artifacts using converting image into the polar domain and applying morphological filtering. The third component fills cavities through a simple but effective morphological filtering operation. Results: Finally, results of these three components are combined into a fusion step to create a visually good image which is more compatible to human visual system. Conclusions: Results show that the proposed algorithm reduces artifacts of dental CBCT images and produces clean images. PMID:29535920

Twofold processing for denoising ultrasound medical images.

PubMed

Kishore, P V V; Kumar, K V V; Kumar, D Anil; Prasad, M V D; Goutham, E N D; Rahul, R; Krishna, C B S Vamsi; Sandeep, Y

2015-01-01

Ultrasound medical (US) imaging non-invasively pictures inside of a human body for disease diagnostics. Speckle noise attacks ultrasound images degrading their visual quality. A twofold processing algorithm is proposed in this work to reduce this multiplicative speckle noise. First fold used block based thresholding, both hard (BHT) and soft (BST), on pixels in wavelet domain with 8, 16, 32 and 64 non-overlapping block sizes. This first fold process is a better denoising method for reducing speckle and also inducing object of interest blurring. The second fold process initiates to restore object boundaries and texture with adaptive wavelet fusion. The degraded object restoration in block thresholded US image is carried through wavelet coefficient fusion of object in original US mage and block thresholded US image. Fusion rules and wavelet decomposition levels are made adaptive for each block using gradient histograms with normalized differential mean (NDF) to introduce highest level of contrast between the denoised pixels and the object pixels in the resultant image. Thus the proposed twofold methods are named as adaptive NDF block fusion with hard and soft thresholding (ANBF-HT and ANBF-ST). The results indicate visual quality improvement to an interesting level with the proposed twofold processing, where the first fold removes noise and second fold restores object properties. Peak signal to noise ratio (PSNR), normalized cross correlation coefficient (NCC), edge strength (ES), image quality Index (IQI) and structural similarity index (SSIM), measure the quantitative quality of the twofold processing technique. Validation of the proposed method is done by comparing with anisotropic diffusion (AD), total variational filtering (TVF) and empirical mode decomposition (EMD) for enhancement of US images. The US images are provided by AMMA hospital radiology labs at Vijayawada, India.

Image counter-forensics based on feature injection

NASA Astrophysics Data System (ADS)

Iuliani, M.; Rossetto, S.; Bianchi, T.; De Rosa, Alessia; Piva, A.; Barni, M.

2014-02-01

Starting from the concept that many image forensic tools are based on the detection of some features revealing a particular aspect of the history of an image, in this work we model the counter-forensic attack as the injection of a specific fake feature pointing to the same history of an authentic reference image. We propose a general attack strategy that does not rely on a specific detector structure. Given a source image x and a target image y, the adversary processes x in the pixel domain producing an attacked image ~x, perceptually similar to x, whose feature f(~x) is as close as possible to f(y) computed on y. Our proposed counter-forensic attack consists in the constrained minimization of the feature distance Φ(z) =│ f(z) - f(y)│ through iterative methods based on gradient descent. To solve the intrinsic limit due to the numerical estimation of the gradient on large images, we propose the application of a feature decomposition process, that allows the problem to be reduced into many subproblems on the blocks the image is partitioned into. The proposed strategy has been tested by attacking three different features and its performance has been compared to state-of-the-art counter-forensic methods.

Imaging of surface spin textures on bulk crystals by scanning electron microscopy

NASA Astrophysics Data System (ADS)

Akamine, Hiroshi; Okumura, So; Farjami, Sahar; Murakami, Yasukazu; Nishida, Minoru

2016-11-01

Direct observation of magnetic microstructures is vital for advancing spintronics and other technologies. Here we report a method for imaging surface domain structures on bulk samples by scanning electron microscopy (SEM). Complex magnetic domains, referred to as the maze state in CoPt/FePt alloys, were observed at a spatial resolution of less than 100 nm by using an in-lens annular detector. The method allows for imaging almost all the domain walls in the mazy structure, whereas the visualisation of the domain walls with the classical SEM method was limited. Our method provides a simple way to analyse surface domain structures in the bulk state that can be used in combination with SEM functions such as orientation or composition analysis. Thus, the method extends applications of SEM-based magnetic imaging, and is promising for resolving various problems at the forefront of fields including physics, magnetics, materials science, engineering, and chemistry.

On LSB Spatial Domain Steganography and Channel Capacity

DTIC Science & Technology

2008-03-21

reveal the hidden information should not be taken as proof that the image is now clean. The survivability of LSB type spatial domain steganography ...the mindset that JPEG compressing an image is sufficient to destroy the steganography for spatial domain LSB type stego. We agree that JPEGing...modeling of 2 bit LSB steganography shows that theoretically there is non-zero stego payload possible even though the image has been JPEGed. We wish to

Distinct self-interaction domains promote Multi Sex Combs accumulation in and formation of the Drosophila histone locus body.

PubMed

Terzo, Esteban A; Lyons, Shawn M; Poulton, John S; Temple, Brenda R S; Marzluff, William F; Duronio, Robert J

2015-04-15

Nuclear bodies (NBs) are structures that concentrate proteins, RNAs, and ribonucleoproteins that perform functions essential to gene expression. How NBs assemble is not well understood. We studied the Drosophila histone locus body (HLB), a NB that concentrates factors required for histone mRNA biosynthesis at the replication-dependent histone gene locus. We coupled biochemical analysis with confocal imaging of both fixed and live tissues to demonstrate that the Drosophila Multi Sex Combs (Mxc) protein contains multiple domains necessary for HLB assembly. An important feature of this assembly process is the self-interaction of Mxc via two conserved N-terminal domains: a LisH domain and a novel self-interaction facilitator (SIF) domain immediately downstream of the LisH domain. Molecular modeling suggests that the LisH and SIF domains directly interact, and mutation of either the LisH or the SIF domain severely impairs Mxc function in vivo, resulting in reduced histone mRNA accumulation. A region of Mxc between amino acids 721 and 1481 is also necessary for HLB assembly independent of the LisH and SIF domains. Finally, the C-terminal 195 amino acids of Mxc are required for recruiting FLASH, an essential histone mRNA-processing factor, to the HLB. We conclude that multiple domains of the Mxc protein promote HLB assembly in order to concentrate factors required for histone mRNA biosynthesis. © 2015 Terzo et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Compressed domain indexing of losslessly compressed images

NASA Astrophysics Data System (ADS)

Schaefer, Gerald

2001-12-01

Image retrieval and image compression have been pursued separately in the past. Only little research has been done on a synthesis of the two by allowing image retrieval to be performed directly in the compressed domain of images without the need to uncompress them first. In this paper methods for image retrieval in the compressed domain of losslessly compressed images are introduced. While most image compression techniques are lossy, i.e. discard visually less significant information, lossless techniques are still required in fields like medical imaging or in situations where images must not be changed due to legal reasons. The algorithms in this paper are based on predictive coding methods where a pixel is encoded based on the pixel values of its (already encoded) neighborhood. The first method is based on an understanding that predictively coded data is itself indexable and represents a textural description of the image. The second method operates directly on the entropy encoded data by comparing codebooks of images. Experiments show good image retrieval results for both approaches.

Holistic processing of fingerprints by expert forensic examiners.

PubMed

Vogelsang, Macgregor D; Palmeri, Thomas J; Busey, Thomas A

2017-01-01

Holistic processing is often characterized as a process by which objects are perceived as a whole rather than a compilation of individual features. This mechanism may play an important role in the development of perceptual expertise because it allows for rapid integration across image regions. The present work explores whether holistic processing is present in latent fingerprint examiners, who compare fingerprints collected from crime scenes against a set of standards taken from a suspect. We adapted a composite task widely used in the face recognition and perceptual expertise literatures, in which participants were asked to match only a particular half of a fingerprint with a previous image while ignoring the other half. We tested both experts and novices, using both upright and inverted fingerprints. For upright fingerprints, we found weak evidence for holistic processing, but with no differences between experts and novices with respect to holistic processing. For inverted fingerprints, we found stronger evidence of holistic processing, with weak evidence for differences between experts and novices. These relatively weak holistic processing effects contrast with robust evidence for holistic processing with faces and with objects in other domains of perceptual expertise. The data constrain models of holistic processing by demonstrating that latent fingerprint experts and novices may not substantively differ in terms of the amount of holistic processing and that inverted stimuli actually produced more evidence for holistic processing than upright stimuli. Important differences between the present fingerprint stimuli and those in the literature include the lack of verbal labels for experts and the absence of strong vertical asymmetries, both of which might contribute to stronger holistic processing signatures in other stimulus domains.

Retrosplenial Cortex Indexes Stability beyond the Spatial Domain

PubMed Central

2018-01-01

Retrosplenial cortex (RSC) is highly responsive to landmarks in the environment that remain fixed in a permanent location, and this has been linked with its known involvement in scene and spatial processing. However, it is unclear whether RSC representations of permanence are a purely spatial phenomenon or whether they extend into behavioral and conceptual domains. To test this, during functional MRI scanning, we had people (males and females) read three different types of sentences that described either something permanent or transient. The first two sentence types were imageable, with a focus either on a spatial landmark or on an action. The third type of sentence involved non-imageable abstract concepts. We found that, in addition to being more active for sentences describing landmarks with a permanent location in space, RSC was also significantly engaged by sentences describing stable and consistent behaviors or actions, as long as they were rooted within a concrete imageable setting. RSC was not responsive to abstract concepts, even those that embodied the notion of stability. Similarly, it was not engaged by imageable sentences with transient contents. In contrast, parahippocampal cortex was more engaged by imageable sentences describing landmarks, whereas the hippocampus was active for all imageable sentences. In addition, for imageable sentences describing permanence, there was bidirectional functional coupling between RSC and these medial temporal lobe structures. It appears, therefore, that RSC-mediated permanence representations could be helpful for more than spatially mapping environments and may also provide information about the reliability of events occurring within them. SIGNIFICANCE STATEMENT The retrosplenial cortex (RSC) is known to process information about landmarks in the environment that have a fixed, permanent location. Here we tested whether this permanence response was apparent beyond the spatial domain, which could have implications for understanding the role of the RSC more widely across cognition. We found that the RSC was engaged not only by permanent landmarks but also by stable and consistent actions. It was not responsive to transient landmarks or actions or to abstract concepts, even those that embodied the notion of stability. We conclude that the RSC might do more than help to map spatial environments, by possibly also providing information about the reliability of events occurring within them. PMID:29311139

Inflammasome activation causes dual recruitment of NLRC4 and NLRP3 to the same macromolecular complex.

PubMed

Man, Si Ming; Hopkins, Lee J; Nugent, Eileen; Cox, Susan; Glück, Ivo M; Tourlomousis, Panagiotis; Wright, John A; Cicuta, Pietro; Monie, Tom P; Bryant, Clare E

2014-05-20

Pathogen recognition by nucleotide-binding oligomerization domain-like receptor (NLR) results in the formation of a macromolecular protein complex (inflammasome) that drives protective inflammatory responses in the host. It is thought that the number of inflammasome complexes forming in a cell is determined by the number of NLRs being activated, with each NLR initiating its own inflammasome assembly independent of one another; however, we show here that the important foodborne pathogen Salmonella enterica serovar Typhimurium (S. Typhimurium) simultaneously activates at least two NLRs, whereas only a single inflammasome complex is formed in a macrophage. Both nucleotide-binding domain and leucine-rich repeat caspase recruitment domain 4 and nucleotide-binding domain and leucine-rich repeat pyrin domain 3 are simultaneously present in the same inflammasome, where both NLRs are required to drive IL-1β processing within the Salmonella-infected cell and to regulate the bacterial burden in mice. Superresolution imaging of Salmonella-infected macrophages revealed a macromolecular complex with an outer ring of apoptosis-associated speck-like protein containing a caspase activation and recruitment domain and an inner ring of NLRs, with active caspase effectors containing the pro-IL-1β substrate localized internal to the ring structure. Our data reveal the spatial localization of different components of the inflammasome and how different members of the NLR family cooperate to drive robust IL-1β processing during Salmonella infection.

Predicting detection performance with model observers: Fourier domain or spatial domain?

PubMed

Chen, Baiyu; Yu, Lifeng; Leng, Shuai; Kofler, James; Favazza, Christopher; Vrieze, Thomas; McCollough, Cynthia

2016-02-27

The use of Fourier domain model observer is challenged by iterative reconstruction (IR), because IR algorithms are nonlinear and IR images have noise texture different from that of FBP. A modified Fourier domain model observer, which incorporates nonlinear noise and resolution properties, has been proposed for IR and needs to be validated with human detection performance. On the other hand, the spatial domain model observer is theoretically applicable to IR, but more computationally intensive than the Fourier domain method. The purpose of this study is to compare the modified Fourier domain model observer to the spatial domain model observer with both FBP and IR images, using human detection performance as the gold standard. A phantom with inserts of various low contrast levels and sizes was repeatedly scanned 100 times on a third-generation, dual-source CT scanner at 5 dose levels and reconstructed using FBP and IR algorithms. The human detection performance of the inserts was measured via a 2-alternative-forced-choice (2AFC) test. In addition, two model observer performances were calculated, including a Fourier domain non-prewhitening model observer and a spatial domain channelized Hotelling observer. The performance of these two mode observers was compared in terms of how well they correlated with human observer performance. Our results demonstrated that the spatial domain model observer correlated well with human observers across various dose levels, object contrast levels, and object sizes. The Fourier domain observer correlated well with human observers using FBP images, but overestimated the detection performance using IR images.

Predicting detection performance with model observers: Fourier domain or spatial domain?

PubMed Central

Chen, Baiyu; Yu, Lifeng; Leng, Shuai; Kofler, James; Favazza, Christopher; Vrieze, Thomas; McCollough, Cynthia

2016-01-01

The use of Fourier domain model observer is challenged by iterative reconstruction (IR), because IR algorithms are nonlinear and IR images have noise texture different from that of FBP. A modified Fourier domain model observer, which incorporates nonlinear noise and resolution properties, has been proposed for IR and needs to be validated with human detection performance. On the other hand, the spatial domain model observer is theoretically applicable to IR, but more computationally intensive than the Fourier domain method. The purpose of this study is to compare the modified Fourier domain model observer to the spatial domain model observer with both FBP and IR images, using human detection performance as the gold standard. A phantom with inserts of various low contrast levels and sizes was repeatedly scanned 100 times on a third-generation, dual-source CT scanner at 5 dose levels and reconstructed using FBP and IR algorithms. The human detection performance of the inserts was measured via a 2-alternative-forced-choice (2AFC) test. In addition, two model observer performances were calculated, including a Fourier domain non-prewhitening model observer and a spatial domain channelized Hotelling observer. The performance of these two mode observers was compared in terms of how well they correlated with human observer performance. Our results demonstrated that the spatial domain model observer correlated well with human observers across various dose levels, object contrast levels, and object sizes. The Fourier domain observer correlated well with human observers using FBP images, but overestimated the detection performance using IR images. PMID:27239086

Wavefront Control and Image Restoration with Less Computing

NASA Technical Reports Server (NTRS)

Lyon, Richard G.

2010-01-01

PseudoDiversity is a method of recovering the wavefront in a sparse- or segmented- aperture optical system typified by an interferometer or a telescope equipped with an adaptive primary mirror consisting of controllably slightly moveable segments. (PseudoDiversity should not be confused with a radio-antenna-arraying method called pseudodiversity.) As in the cases of other wavefront- recovery methods, the streams of wavefront data generated by means of PseudoDiversity are used as feedback signals for controlling electromechanical actuators of the various segments so as to correct wavefront errors and thereby, for example, obtain a clearer, steadier image of a distant object in the presence of atmospheric turbulence. There are numerous potential applications in astronomy, remote sensing from aircraft and spacecraft, targeting missiles, sighting military targets, and medical imaging (including microscopy) through such intervening media as cells or water. In comparison with prior wavefront-recovery methods used in adaptive optics, PseudoDiversity involves considerably simpler equipment and procedures and less computation. For PseudoDiversity, there is no need to install separate metrological equipment or to use any optomechanical components beyond those that are already parts of the optical system to which the method is applied. In Pseudo- Diversity, the actuators of a subset of the segments or subapertures are driven to make the segments dither in the piston, tilt, and tip degrees of freedom. Each aperture is dithered at a unique frequency at an amplitude of a half wavelength of light. During the dithering, images on the focal plane are detected and digitized at a rate of at least four samples per dither period. In the processing of the image samples, the use of different dither frequencies makes it possible to determine the separate effects of the various dithered segments or apertures. The digitized image-detector outputs are processed in the spatial-frequency (Fourier-transform) domain to obtain measures of the piston, tip, and tilt errors over each segment or subaperture. Once these measures are known, they are fed back to the actuators to correct the errors. In addition, measures of errors that remain after correction by use of the actuators are further utilized in an algorithm in which the image is phase-corrected in the spatial-frequency domain and then transformed back to the spatial domain at each time step and summed with the images from all previous time steps to obtain a final image having a greater signal-to-noise ratio (and, hence, a visual quality) higher than would otherwise be attainable.

Literature Review of Cognitive Neuroscience and Anorexia Nervosa.

PubMed

Reville, Marie-Claire; O'Connor, Lorna; Frampton, Ian

2016-02-01

Studies published between the beginning of 2013 and May 2015 on the neuropsychological functioning of patients with anorexia nervosa compared with healthy participants framed in the context of the Research Domain Criteria matrix identifies evidence for functional differences in three domains: Negative Valance Systems-negative attentional biases and lack of neural responsivity to hunger; Cognitive Systems-limited congruence between clinical and cognitive performance, poorer non-verbal than verbal performance, altered attentional styles to disorder related stimuli, perceptual processing impairment in discriminating body images, weaknesses in central coherence, set shifting weaknesses at low weight status, decision-making weaknesses, and greater neural resources required for working memory; Systems for Social Processes-patients appear to have a different attentional response to faces, and perception and understanding of self and others. Hence, there is evidence to suggest that patients with anorexia nervosa have a specific neuropsychological performance style across tasks in three domains of functioning. Some current controversies and areas for future development are identified.

The neural architecture of expert calendar calculation: a matter of strategy?

PubMed

Fehr, Thorsten; Wallace, Gregory L; Erhard, Peter; Herrmann, Manfred

2011-08-01

Savants and prodigies are individuals with exceptional skills in particular mental domains. In the present study we used functional magnetic resonance imaging to examine neural correlates of calendar calculation in two individuals, a savant with Asperger's disorder and a self-taught mathematical prodigy. If there is a modular neural organization of exceptional performance in a specific mental domain, calendar calculation should be reflected in a considerable overlap in the recruitment of brain circuits across expert individuals. However, considerable individual differences in activation patterns during calendar calculation were noted. The present results indicate that activation patterns produced by complex mental processing, such as calendar calculation, seem to be influenced strongly by learning history and idiosyncratic strategy usage rather than a modular neural organization. Thus, well-known individual differences in complex cognition play a major role even in experts with exceptional abilities in a particular mental domain and should in particular be considered when examining the neural architecture of complex mental processes and skills.

Ferroelectric and multiferroic domain imaging by Laser-induced photoemission microscopy

NASA Astrophysics Data System (ADS)

Hoefer, Anke; Fechner, Michael; Duncker, Klaus; Mertig, Ingrid; Widdra, Wolf

2013-03-01

The ferroelectric as well as multiferroic surface domain structures of BaTiO3(001) and BiFeO3(001) are imaged based on photoemission electron microscopy (PEEM) by femtosecond laser threshold excitation under UHV conditions. For well-prepared BaTiO3(001), three ferroelectric domain types are clearly discriminable due to work function differences. At room temperature, the surface domains resemble the known ferroelectric domain structure of the bulk. Upon heating above the Curie point of 400 K, the specific surface domain pattern remains up to 500 K. Ab-initio calculations explain this observation by a remaining tetragonal distortion of the topmost unit cells stabilized by a surface relaxation. The (001) surface of the single-phase multiferroic BiFeO3 which is ferroelectric and antiferromagnetic, shows clear ferroelectric work function contrast in PEEM. Additionally, the multiferroic domains show significant linear dichroism. The observation of a varying dichroism for different ferroelectric domains can be explained based on the coupled ferroelectric-antiferromagnetic order in BiFeO3. It demonstrates multiferroic imaging of different domain types within a single, lab-based experiment.

Adaptive Optics Optical Coherence Tomography in Glaucoma

PubMed Central

Dong, Zachary M.; Wollstein, Gadi; Wang, Bo; Schuman, Joel S.

2016-01-01

Since the introduction of commercial optical coherence tomography (OCT) systems, the ophthalmic imaging modality has rapidly expanded and it has since changed the paradigm of visualization of the retina and revolutionized the management and diagnosis of neuro-retinal diseases, including glaucoma. OCT remains a dynamic and evolving imaging modality, growing from time-domain OCT to the improved spectral-domain OCT, adapting novel image analysis and processing methods, and onto the newer swept-source OCT and the implementation of adaptive optics (AO) into OCT. The incorporation of AO into ophthalmic imaging modalities has enhanced OCT by improving image resolution and quality, particularly in the posterior segment of the eye. Although OCT previously captured in-vivo cross-sectional images with unparalleled high resolution in the axial direction, monochromatic aberrations of the eye limit transverse or lateral resolution to about 15-20 μm and reduce overall image quality. In pairing AO technology with OCT, it is now possible to obtain diffraction-limited resolution images of the optic nerve head and retina in three-dimensions, increasing resolution down to a theoretical 3 μm3. It is now possible to visualize discrete structures within the posterior eye, such as photoreceptors, retinal nerve fiber layer bundles, the lamina cribrosa, and other structures relevant to glaucoma. Despite its limitations and barriers to widespread commercialization, the expanding role of AO in OCT is propelling this technology into clinical trials and onto becoming an invaluable modality in the clinician's arsenal. PMID:27916682

The role of domain-general cognitive control in language comprehension

PubMed Central

Fedorenko, Evelina

2014-01-01

What role does domain-general cognitive control play in understanding linguistic input? Although much evidence has suggested that domain-general cognitive control and working memory resources are sometimes recruited during language comprehension, many aspects of this relationship remain elusive. For example, how frequently do cognitive control mechanisms get engaged when we understand language? And is this engagement necessary for successful comprehension? I here (a) review recent brain imaging evidence for the neural separability of the brain regions that support high-level linguistic processing vs. those that support domain-general cognitive control abilities; (b) define the space of possibilities for the relationship between these sets of brain regions; and (c) review the available evidence that constrains these possibilities to some extent. I argue that we should stop asking whether domain-general cognitive control mechanisms play a role in language comprehension, and instead focus on characterizing the division of labor between the cognitive control brain regions and the more functionally specialized language regions. PMID:24803909

Methods and apparatus for constructing and implementing a universal extension module for processing objects in a database

NASA Technical Reports Server (NTRS)

Li, Chung-Sheng (Inventor); Smith, John R. (Inventor); Chang, Yuan-Chi (Inventor); Jhingran, Anant D. (Inventor); Padmanabhan, Sriram K. (Inventor); Hsiao, Hui-I (Inventor); Choy, David Mun-Hien (Inventor); Lin, Jy-Jine James (Inventor); Fuh, Gene Y. C. (Inventor); Williams, Robin (Inventor)

2004-01-01

Methods and apparatus for providing a multi-tier object-relational database architecture are disclosed. In one illustrative embodiment of the present invention, a multi-tier database architecture comprises an object-relational database engine as a top tier, one or more domain-specific extension modules as a bottom tier, and one or more universal extension modules as a middle tier. The individual extension modules of the bottom tier operationally connect with the one or more universal extension modules which, themselves, operationally connect with the database engine. The domain-specific extension modules preferably provide such functions as search, index, and retrieval services of images, video, audio, time series, web pages, text, XML, spatial data, etc. The domain-specific extension modules may include one or more IBM DB2 extenders, Oracle data cartridges and/or Informix datablades, although other domain-specific extension modules may be used.

Creation and Validation of the Self-esteem/Self-image Female Sexuality (SESIFS) Questionnaire

PubMed Central

Lordello, Maria CO; Ambrogini, Carolina C; Fanganiello, Ana L; Embiruçu, Teresa R; Zaneti, Marina M; Veloso, Laise; Piccirillo, Livia B; Crude, Bianca L; Haidar, Mauro; Silva, Ivaldo

2014-01-01

INTRODUCTION Self-esteem and self-image are psychological aspects that affect sexual function. AIMS To validate a new measurement tool that correlates the concepts of self-esteem, self-image, and sexuality. METHODS A 20-question test (the self-esteem/self-image female sexuality [SESIFS] questionnaire) was created and tested on 208 women. Participants answered: Rosenberg’s self-esteem scale, the female sexual quotient (FSQ), and the SESIFS questionnaire. Pearson’s correlation coefficient was used to test concurrent validity of the SESIFS against Rosenberg’s self-esteem scale and the FSQ. Reliability was tested using the Cronbach’s alpha coefficient. RESULT The new questionnaire had a good overall reliability (Cronbach’s alpha r = 0.862, p < 0.001), but the sexual domain scored lower than expected (r = 0.65). The validity was good: overall score r = 0.38, p < 0.001, self-esteem domain r = 0.32, p < 0.001, self-image domain r = 0.31, p < 0.001, sexual domain r = 0.29, p < 0.001. CONCLUSIONS The SESIFS questionnaire has limitations in measuring the correlation among self-esteem, self-image, and sexuality domains. A new, revised version is being tested and will be presented in an upcoming publication. PMID:25574149

Creation and Validation of the Self-esteem/Self-image Female Sexuality (SESIFS) Questionnaire.

PubMed

Lordello, Maria Co; Ambrogini, Carolina C; Fanganiello, Ana L; Embiruçu, Teresa R; Zaneti, Marina M; Veloso, Laise; Piccirillo, Livia B; Crude, Bianca L; Haidar, Mauro; Silva, Ivaldo

2014-01-01

Self-esteem and self-image are psychological aspects that affect sexual function. To validate a new measurement tool that correlates the concepts of self-esteem, self-image, and sexuality. A 20-question test (the self-esteem/self-image female sexuality [SESIFS] questionnaire) was created and tested on 208 women. Participants answered: Rosenberg's self-esteem scale, the female sexual quotient (FSQ), and the SESIFS questionnaire. Pearson's correlation coefficient was used to test concurrent validity of the SESIFS against Rosenberg's self-esteem scale and the FSQ. Reliability was tested using the Cronbach's alpha coefficient. The new questionnaire had a good overall reliability (Cronbach's alpha r = 0.862, p < 0.001), but the sexual domain scored lower than expected (r = 0.65). The validity was good: overall score r = 0.38, p < 0.001, self-esteem domain r = 0.32, p < 0.001, self-image domain r = 0.31, p < 0.001, sexual domain r = 0.29, p < 0.001. The SESIFS questionnaire has limitations in measuring the correlation among self-esteem, self-image, and sexuality domains. A new, revised version is being tested and will be presented in an upcoming publication.

DICOM relay over the cloud.

PubMed

Silva, Luís A Bastião; Costa, Carlos; Oliveira, José Luis

2013-05-01

Healthcare institutions worldwide have adopted picture archiving and communication system (PACS) for enterprise access to images, relying on Digital Imaging Communication in Medicine (DICOM) standards for data exchange. However, communication over a wider domain of independent medical institutions is not well standardized. A DICOM-compliant bridge was developed for extending and sharing DICOM services across healthcare institutions without requiring complex network setups or dedicated communication channels. A set of DICOM routers interconnected through a public cloud infrastructure was implemented to support medical image exchange among institutions. Despite the advantages of cloud computing, new challenges were encountered regarding data privacy, particularly when medical data are transmitted over different domains. To address this issue, a solution was introduced by creating a ciphered data channel between the entities sharing DICOM services. Two main DICOM services were implemented in the bridge: Storage and Query/Retrieve. The performance measures demonstrated it is quite simple to exchange information and processes between several institutions. The solution can be integrated with any currently installed PACS-DICOM infrastructure. This method works transparently with well-known cloud service providers. Cloud computing was introduced to augment enterprise PACS by providing standard medical imaging services across different institutions, offering communication privacy and enabling creation of wider PACS scenarios with suitable technical solutions.

Quantitative imaging biomarker ontology (QIBO) for knowledge representation of biomedical imaging biomarkers.

PubMed

Buckler, Andrew J; Liu, Tiffany Ting; Savig, Erica; Suzek, Baris E; Ouellette, M; Danagoulian, J; Wernsing, G; Rubin, Daniel L; Paik, David

2013-08-01

A widening array of novel imaging biomarkers is being developed using ever more powerful clinical and preclinical imaging modalities. These biomarkers have demonstrated effectiveness in quantifying biological processes as they occur in vivo and in the early prediction of therapeutic outcomes. However, quantitative imaging biomarker data and knowledge are not standardized, representing a critical barrier to accumulating medical knowledge based on quantitative imaging data. We use an ontology to represent, integrate, and harmonize heterogeneous knowledge across the domain of imaging biomarkers. This advances the goal of developing applications to (1) improve precision and recall of storage and retrieval of quantitative imaging-related data using standardized terminology; (2) streamline the discovery and development of novel imaging biomarkers by normalizing knowledge across heterogeneous resources; (3) effectively annotate imaging experiments thus aiding comprehension, re-use, and reproducibility; and (4) provide validation frameworks through rigorous specification as a basis for testable hypotheses and compliance tests. We have developed the Quantitative Imaging Biomarker Ontology (QIBO), which currently consists of 488 terms spanning the following upper classes: experimental subject, biological intervention, imaging agent, imaging instrument, image post-processing algorithm, biological target, indicated biology, and biomarker application. We have demonstrated that QIBO can be used to annotate imaging experiments with standardized terms in the ontology and to generate hypotheses for novel imaging biomarker-disease associations. Our results established the utility of QIBO in enabling integrated analysis of quantitative imaging data.

Meta-Stable Magnetic Domain States That Prevent Reliable Absolute Palaeointensity Experiments Revealed By Magnetic Force Microscopy

NASA Astrophysics Data System (ADS)

de Groot, L. V.; Fabian, K.; Bakelaar, I. A.; Dekkers, M. J.

2014-12-01

Obtaining reliable estimates of the absolute palaeointensity of the Earth's magnetic field is notoriously difficult. Many methods to obtain paleointensities from suitable records such as lavas and archeological artifacts involve heating the samples. These heating steps are believed to induce 'magnetic alteration' - a process that is still poorly understood but prevents obtaining correct paleointensity estimates. To observe this magnetic alteration directly we imaged the magnetic domain state of titanomagnetite particles - a common carrier of the magnetic remanence in samples used for paleointensity studies. We selected samples from the 1971-flow of Mt. Etna from a site that systematically yields underestimates of the known intensity of the paleofield - in spite of rigorous testing by various groups. Magnetic Force Microscope images were taken before and after a heating step typically used in absolute palaeointensity experiments. Before heating, the samples feature distinct, blocky domains that sometimes seem to resemble a classical magnetite domain structure. After imparting a partial thermo-remanent magnetization at a temperature often critical to paleointensity experiments (250 °C) the domain state of the same titanomagnetite grains changes into curvier, wavy domains. Furthermore, these structures appeared to be unstable over time: after one-year storage in a magnetic field-free environment the domain states evolved into a viscous remanent magnetization state. Our observations may qualitatively explain reported underestimates from technically successful paleointensity experiments for this site and other sites reported previously. Furthermore the occurrence of intriguing observations such as 'the drawer storage effect' by Shaar et al (EPSL, 2011), and viscous magnetizations observed by Muxworthy and Williams (JGR, 2006) may be (partially) explained by our observations. The major implications of our study for all palaeointensity methods involving heating may be evident.

Object-Oriented Query Language For Events Detection From Images Sequences

NASA Astrophysics Data System (ADS)

Ganea, Ion Eugen

2015-09-01

In this paper is presented a method to represent the events extracted from images sequences and the query language used for events detection. Using an object oriented model the spatial and temporal relationships between salient objects and also between events are stored and queried. This works aims to unify the storing and querying phases for video events processing. The object oriented language syntax used for events processing allow the instantiation of the indexes classes in order to improve the accuracy of the query results. The experiments were performed on images sequences provided from sport domain and it shows the reliability and the robustness of the proposed language. To extend the language will be added a specific syntax for constructing the templates for abnormal events and for detection of the incidents as the final goal of the research.

Combined spectral-domain optical coherence tomography and hyperspectral imaging applied for tissue analysis: Preliminary results

NASA Astrophysics Data System (ADS)

Dontu, S.; Miclos, S.; Savastru, D.; Tautan, M.

2017-09-01

In recent years many optoelectronic techniques have been developed for improvement and the development of devices for tissue analysis. Spectral-Domain Optical Coherence Tomography (SD-OCT) is a new medical interferometric imaging modality that provides depth resolved tissue structure information with resolution in the μm range. However, SD-OCT has its own limitations and cannot offer the biochemical information of the tissue. These data can be obtained with hyperspectral imaging, a non-invasive, sensitive and real time technique. In the present study we have combined Spectral-Domain Optical Coherence Tomography (SD-OCT) with Hyperspectral imaging (HSI) for tissue analysis. The Spectral-Domain Optical Coherence Tomography (SD-OCT) and Hyperspectral imaging (HSI) are two methods that have demonstrated significant potential in this context. Preliminary results using different tissue have highlighted the capabilities of this technique of combinations.

A design of real time image capturing and processing system using Texas Instrument's processor

NASA Astrophysics Data System (ADS)

Wee, Toon-Joo; Chaisorn, Lekha; Rahardja, Susanto; Gan, Woon-Seng

2007-09-01

In this work, we developed and implemented an image capturing and processing system that equipped with capability of capturing images from an input video in real time. The input video can be a video from a PC, video camcorder or DVD player. We developed two modes of operation in the system. In the first mode, an input image from the PC is processed on the processing board (development platform with a digital signal processor) and is displayed on the PC. In the second mode, current captured image from the video camcorder (or from DVD player) is processed on the board but is displayed on the LCD monitor. The major difference between our system and other existing conventional systems is that image-processing functions are performed on the board instead of the PC (so that the functions can be used for further developments on the board). The user can control the operations of the board through the Graphic User Interface (GUI) provided on the PC. In order to have a smooth image data transfer between the PC and the board, we employed Real Time Data Transfer (RTDX TM) technology to create a link between them. For image processing functions, we developed three main groups of function: (1) Point Processing; (2) Filtering and; (3) 'Others'. Point Processing includes rotation, negation and mirroring. Filter category provides median, adaptive, smooth and sharpen filtering in the time domain. In 'Others' category, auto-contrast adjustment, edge detection, segmentation and sepia color are provided, these functions either add effect on the image or enhance the image. We have developed and implemented our system using C/C# programming language on TMS320DM642 (or DM642) board from Texas Instruments (TI). The system was showcased in College of Engineering (CoE) exhibition 2006 at Nanyang Technological University (NTU) and have more than 40 users tried our system. It is demonstrated that our system is adequate for real time image capturing. Our system can be used or applied for applications such as medical imaging, video surveillance, etc.

Co-registration of ultrasound and frequency-domain photoacoustic radar images and image improvement for tumor detection

NASA Astrophysics Data System (ADS)

Dovlo, Edem; Lashkari, Bahman; Choi, Sung soo Sean; Mandelis, Andreas

2015-03-01

This paper demonstrates the co-registration of ultrasound (US) and frequency domain photoacoustic radar (FD-PAR) images with significant image improvement from applying image normalization, filtering and amplification techniques. Achieving PA imaging functionality on a commercial Ultrasound instrument could accelerate clinical acceptance and use. Experimental results presented demonstrate live animal testing and show enhancements in signal-to-noise ratio (SNR), contrast and spatial resolution. The co-registered image produced from the US and phase PA images, provides more information than both images independently.

Neurocomputational mechanisms underlying subjective valuation of effort costs

PubMed Central

Giehl, Kathrin; Sillence, Annie

2017-01-01

In everyday life, we have to decide whether it is worth exerting effort to obtain rewards. Effort can be experienced in different domains, with some tasks requiring significant cognitive demand and others being more physically effortful. The motivation to exert effort for reward is highly subjective and varies considerably across the different domains of behaviour. However, very little is known about the computational or neural basis of how different effort costs are subjectively weighed against rewards. Is there a common, domain-general system of brain areas that evaluates all costs and benefits? Here, we used computational modelling and functional magnetic resonance imaging (fMRI) to examine the mechanisms underlying value processing in both the cognitive and physical domains. Participants were trained on two novel tasks that parametrically varied either cognitive or physical effort. During fMRI, participants indicated their preferences between a fixed low-effort/low-reward option and a variable higher-effort/higher-reward offer for each effort domain. Critically, reward devaluation by both cognitive and physical effort was subserved by a common network of areas, including the dorsomedial and dorsolateral prefrontal cortex, the intraparietal sulcus, and the anterior insula. Activity within these domain-general areas also covaried negatively with reward and positively with effort, suggesting an integration of these parameters within these areas. Additionally, the amygdala appeared to play a unique, domain-specific role in processing the value of rewards associated with cognitive effort. These results are the first to reveal the neurocomputational mechanisms underlying subjective cost–benefit valuation across different domains of effort and provide insight into the multidimensional nature of motivation. PMID:28234892

Wave Propagation, Scattering and Imaging Using Dual-domain One-way and One-return Propagators

NASA Astrophysics Data System (ADS)

Wu, R.-S.

- Dual-domain one-way propagators implement wave propagation in heterogeneous media in mixed domains (space-wavenumber domains). One-way propagators neglect wave reverberations between heterogeneities but correctly handle the forward multiple-scattering including focusing/defocusing, diffraction, refraction and interference of waves. The algorithm shuttles between space-domain and wavenumber-domain using FFT, and the operations in the two domains are self-adaptive to the complexity of the media. The method makes the best use of the operations in each domain, resulting in efficient and accurate propagators. Due to recent progress, new versions of dual-domain methods overcame some limitations of the classical dual-domain methods (phase-screen or split-step Fourier methods) and can propagate large-angle waves quite accurately in media with strong velocity contrasts. These methods can deliver superior image quality (high resolution/high fidelity) for complex subsurface structures. One-way and one-return (De Wolf approximation) propagators can be also applied to wave-field modeling and simulations for some geophysical problems. In the article, a historical review and theoretical analysis of the Born, Rytov, and De Wolf approximations are given. A review on classical phase-screen or split-step Fourier methods is also given, followed by a summary and analysis of the new dual-domain propagators. The applications of the new propagators to seismic imaging and modeling are reviewed with several examples. For seismic imaging, the advantages and limitations of the traditional Kirchhoff migration and time-space domain finite-difference migration, when applied to 3-D complicated structures, are first analyzed. Then the special features, and applications of the new dual-domain methods are presented. Three versions of GSP (generalized screen propagators), the hybrid pseudo-screen, the wide-angle Padé-screen, and the higher-order generalized screen propagators are discussed. Recent progress also makes it possible to use the dual-domain propagators for modeling elastic reflections for complex structures and long-range propagations of crustal guided waves. Examples of 2-D and 3-D imaging and modeling using GSP methods are given.

Time-domain imaging

NASA Technical Reports Server (NTRS)

Tolliver, C. L.

1989-01-01

The quest for the highest resolution microwave imaging and principle of time-domain imaging has been the primary motivation for recent developments in time-domain techniques. With the present technology, fast time varying signals can now be measured and recorded both in magnitude and in-phase. It has also enhanced our ability to extract relevant details concerning the scattering object. In the past, the interface of object geometry or shape for scattered signals has received substantial attention in radar technology. Various scattering theories were proposed to develop analytical solutions to this problem. Furthermore, the random inversion, frequency swept holography, and the synthetic radar imaging, have two things in common: (1) the physical optic far-field approximation, and (2) the utilization of channels as an extra physical dimension, were also advanced. Despite the inherent vectorial nature of electromagnetic waves, these scalar treatments have brought forth some promising results in practice with notable examples in subsurface and structure sounding. The development of time-domain techniques are studied through the theoretical aspects as well as experimental verification. The use of time-domain imaging for space robotic vision applications has been suggested.

Region-based multifocus image fusion for the precise acquisition of Pap smear images.

PubMed

Tello-Mijares, Santiago; Bescós, Jesús

2018-05-01

A multifocus image fusion method to obtain a single focused image from a sequence of microscopic high-magnification Papanicolau source (Pap smear) images is presented. These images, captured each in a different position of the microscope lens, frequently show partially focused cells or parts of cells, which makes them unpractical for the direct application of image analysis techniques. The proposed method obtains a focused image with a high preservation of original pixels information while achieving a negligible visibility of the fusion artifacts. The method starts by identifying the best-focused image of the sequence; then, it performs a mean-shift segmentation over this image; the focus level of the segmented regions is evaluated in all the images of the sequence, and best-focused regions are merged in a single combined image; finally, this image is processed with an adaptive artifact removal process. The combination of a region-oriented approach, instead of block-based approaches, and a minimum modification of the value of focused pixels in the original images achieve a highly contrasted image with no visible artifacts, which makes this method especially convenient for the medical imaging domain. The proposed method is compared with several state-of-the-art alternatives over a representative dataset. The experimental results show that our proposal obtains the best and more stable quality indicators. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Sparsity based target detection for compressive spectral imagery

NASA Astrophysics Data System (ADS)

Boada, David Alberto; Arguello Fuentes, Henry

2016-09-01

Hyperspectral imagery provides significant information about the spectral characteristics of objects and materials present in a scene. It enables object and feature detection, classification, or identification based on the acquired spectral characteristics. However, it relies on sophisticated acquisition and data processing systems able to acquire, process, store, and transmit hundreds or thousands of image bands from a given area of interest which demands enormous computational resources in terms of storage, computationm, and I/O throughputs. Specialized optical architectures have been developed for the compressed acquisition of spectral images using a reduced set of coded measurements contrary to traditional architectures that need a complete set of measurements of the data cube for image acquisition, dealing with the storage and acquisition limitations. Despite this improvement, if any processing is desired, the image has to be reconstructed by an inverse algorithm in order to be processed, which is also an expensive task. In this paper, a sparsity-based algorithm for target detection in compressed spectral images is presented. Specifically, the target detection model adapts a sparsity-based target detector to work in a compressive domain, modifying the sparse representation basis in the compressive sensing problem by means of over-complete training dictionaries and a wavelet basis representation. Simulations show that the presented method can achieve even better detection results than the state of the art methods.

Soft x-ray coherent diffraction imaging on magnetic nanostructures

NASA Astrophysics Data System (ADS)

Shi, Xiaowen; Lee, James; Mishra, Shrawan; Parks, Daniel; Tyliszczak, Tolek; Shapiro, David; Roy, Sujoy; Kevan, Steve; Stxm Team At Als Collaboration; Soft X-Ray Microscopy Group At Als Collaboration; Soft X-ray scattering at ALS, LBL Team

2014-03-01

Coherent soft X-rays diffraction imaging enable coherent magnetic resonance scattering at transition metal L-edge to be probed so that magnetic domains could be imaged with very high spatial resolution with phase contrast, reaching sub-10nm. One of the overwhelming advantages of using coherent X-rays is the ability to resolve phase contrast images with linearly polarized light with both phase and absorption contrast comparing to real-space imaging, which can only be studied with circularly polarized light with absorption contrast only. Here we report our first results on high-resolution of magnetic domains imaging of CoPd multilayer thin film with coherent soft X-ray ptychography method. We are aiming to resolve and understand magnetic domain wall structures with the highest obtainable resolution here at Advanced Light Source. In principle types of magnetic domain walls could be studied so that Neel or Bloch walls can be distinguished by imaging. This work at LBNL was supported by the Director, Office of Science, Office of Basic Energy Sciences, of the US Department of Energy (contract no. DE-AC02- 05CH11231).

Signal digitizing system and method based on amplitude-to-time optical mapping

DOEpatents

Chou, Jason; Bennett, Corey V; Hernandez, Vince

2015-01-13

A signal digitizing system and method based on analog-to-time optical mapping, optically maps amplitude information of an analog signal of interest first into wavelength information using an amplitude tunable filter (ATF) to impress spectral changes induced by the amplitude of the analog signal onto a carrier signal, i.e. a train of optical pulses, and next from wavelength information to temporal information using a dispersive element so that temporal information representing the amplitude information is encoded in the time domain in the carrier signal. Optical-to-electrical conversion of the optical pulses into voltage waveforms and subsequently digitizing the voltage waveforms into a digital image enables the temporal information to be resolved and quantized in the time domain. The digital image may them be digital signal processed to digitally reconstruct the analog signal based on the temporal information with high fidelity.

2.5D transient electromagnetic inversion with OCCAM method

NASA Astrophysics Data System (ADS)

Li, R.; Hu, X.

2016-12-01

In the application of time-domain electromagnetic method (TEM), some multidimensional inversion schemes are applied for imaging in the past few decades to overcome great error produced by 1D model inversion when the subsurface structure is complex. The current mainstream multidimensional inversion for EM data, with the finite-difference time-domain (FDTD) forward method, mainly implemented by Nonlinear Conjugate Gradient (NLCG). But the convergence rate of NLCG heavily depends on Lagrange multiplier and maybe fail to converge. We use the OCCAM inversion method to avoid the weakness. OCCAM inversion is proven to be a more stable and reliable method to image the subsurface 2.5D electrical conductivity. Firstly, we simulate the 3D transient EM fields governed by Maxwell's equations with FDTD method. Secondly, we use the OCCAM inversion scheme with the appropriate objective error functional we established to image the 2.5D structure. And the data space OCCAM's inversion (DASOCC) strategy based on OCCAM scheme were given in this paper. The sensitivity matrix is calculated with the method of time-integrated back-propagated fields. Imaging result of example model shown in Fig. 1 have proven that the OCCAM scheme is an efficient inversion method for TEM with FDTD method. The processes of the inversion iterations have shown the great ability of convergence with few iterations. Summarizing the process of the imaging, we can make the following conclusions. Firstly, the 2.5D imaging in FDTD system with OCCAM inversion demonstrates that we could get desired imaging results for the resistivity structure in the homogeneous half-space. Secondly, the imaging results usually do not over-depend on the initial model, but the iteration times can be reduced distinctly if the background resistivity of initial model get close to the truthful model. So it is batter to set the initial model based on the other geologic information in the application. When the background resistivity fit the truthful model well, the imaging of anomalous body only need a few iteration steps. Finally, the speed of imaging vertical boundaries is slower than the speed of imaging the horizontal boundaries.

Pulse compression favourable aperiodic infrared imaging approach for non-destructive testing and evaluation of bio-materials

NASA Astrophysics Data System (ADS)

Mulaveesala, Ravibabu; Dua, Geetika; Arora, Vanita; Siddiqui, Juned A.; Muniyappa, Amarnath

2017-05-01

In recent years, aperiodic, transient pulse compression favourable infrared imaging methodologies demonstrated as reliable, quantitative, remote characterization and evaluation techniques for testing and evaluation of various biomaterials. This present work demonstrates a pulse compression favourable aperiodic thermal wave imaging technique, frequency modulated thermal wave imaging technique for bone diagnostics, especially by considering the bone with tissue, skin and muscle over layers. In order to find the capabilities of the proposed frequency modulated thermal wave imaging technique to detect the density variations in a multi layered skin-fat-muscle-bone structure, finite element modeling and simulation studies have been carried out. Further, frequency and time domain post processing approaches have been adopted on the temporal temperature data in order to improve the detection capabilities of frequency modulated thermal wave imaging.

Three-dimensional near-field MIMO array imaging using range migration techniques.

PubMed

Zhuge, Xiaodong; Yarovoy, Alexander G

2012-06-01

This paper presents a 3-D near-field imaging algorithm that is formulated for 2-D wideband multiple-input-multiple-output (MIMO) imaging array topology. The proposed MIMO range migration technique performs the image reconstruction procedure in the frequency-wavenumber domain. The algorithm is able to completely compensate the curvature of the wavefront in the near-field through a specifically defined interpolation process and provides extremely high computational efficiency by the application of the fast Fourier transform. The implementation aspects of the algorithm and the sampling criteria of a MIMO aperture are discussed. The image reconstruction performance and computational efficiency of the algorithm are demonstrated both with numerical simulations and measurements using 2-D MIMO arrays. Real-time 3-D near-field imaging can be achieved with a real-aperture array by applying the proposed MIMO range migration techniques.

Deformable Medical Image Registration: A Survey

PubMed Central

Sotiras, Aristeidis; Davatzikos, Christos; Paragios, Nikos

2013-01-01

Deformable image registration is a fundamental task in medical image processing. Among its most important applications, one may cite: i) multi-modality fusion, where information acquired by different imaging devices or protocols is fused to facilitate diagnosis and treatment planning; ii) longitudinal studies, where temporal structural or anatomical changes are investigated; and iii) population modeling and statistical atlases used to study normal anatomical variability. In this paper, we attempt to give an overview of deformable registration methods, putting emphasis on the most recent advances in the domain. Additional emphasis has been given to techniques applied to medical images. In order to study image registration methods in depth, their main components are identified and studied independently. The most recent techniques are presented in a systematic fashion. The contribution of this paper is to provide an extensive account of registration techniques in a systematic manner. PMID:23739795

Motion compensation for ultra wide band SAR

NASA Technical Reports Server (NTRS)

Madsen, S.

2001-01-01

This paper describes an algorithm that combines wavenumber domain processing with a procedure that enables motion compensation to be applied as a function of target range and azimuth angle. First, data are processed with nominal motion compensation applied, partially focusing the image, then the motion compensation of individual subpatches is refined. The results show that the proposed algorithm is effective in compensating for deviations from a straight flight path, from both a performance and a computational efficiency point of view.

The role of the striatum in rule application: the model of Huntington's disease at early stage.

PubMed

Teichmann, Marc; Dupoux, Emmanuel; Kouider, Sid; Brugières, Pierre; Boissé, Marie-Françoise; Baudic, Sophie; Cesaro, Pierre; Peschanski, Marc; Bachoud-Lévi, Anne-Catherine

2005-05-01

The role of the basal ganglia, and more specifically of the striatum, in language is still debated. Recent studies have proposed that linguistic abilities involve two distinct types of processes: the retrieving of stored information, implicating temporal lobe areas, and the application of combinatorial rules, implicating fronto-striatal circuits. Studies of patients with focal lesions and neurodegenerative diseases have suggested a role for the striatum in morphological rule application, but functional imaging studies found that the left caudate was involved in syntactic processing and not morphological processing. In the present study, we tested the view that the basal ganglia are involved in rule application and not in lexical retrieving in a model of striatal dysfunction, namely Huntington's disease at early stages. We assessed the rule-lexicon dichotomy in the linguistic domain with morphology (conjugation of non-verbs and verbs) and syntax (sentence comprehension) and in a non-linguistic domain with arithmetic operations (subtraction and multiplication). Thirty Huntington's disease patients (15 at stage I and 15 at stage II) and 20 controls matched for their age and cultural level were included in this study. Huntington's disease patients were also assessed using the Unified Huntington's Disease Rating Scale (UHDRS) and MRI. We found that early Huntington's disease patients were impaired in rule application in the linguistic and non-linguistic domains (morphology, syntax and subtraction), whereas they were broadly spared with lexical processing. The pattern of performance was similar in patients at stage I and stage II, except that stage II patients were more impaired in all tasks assessing rules and had in addition a very slight impairment in the lexical condition of conjugation. Finally, syntactic rule abilities correlated with all markers of the disease evolution including bicaudate ratio and performance in executive function, whereas there was no correlation with arithmetic and morphological abilities. Together, this suggests that the striatum is involved in rule processing more than in lexical processing and that it extends to linguistic and non-linguistic domains. These results are discussed in terms of domain-specific versus domain-general processes of rule application.

The Effect of Non-Visual Working Memory Load on Top-Down Modulation of Visual Processing

ERIC Educational Resources Information Center

Rissman, Jesse; Gazzaley, Adam; D'Esposito, Mark

2009-01-01

While a core function of the working memory (WM) system is the active maintenance of behaviorally relevant sensory representations, it is also critical that distracting stimuli are appropriately ignored. We used functional magnetic resonance imaging to examine the role of domain-general WM resources in the top-down attentional modulation of…

Newborns' Face Recognition Is Based on Spatial Frequencies below 0.5 Cycles per Degree

ERIC Educational Resources Information Center

de Heering, Adelaide; Turati, Chiara; Rossion, Bruno; Bulf, Hermann; Goffaux, Valerie; Simion, Francesca

2008-01-01

A critical question in Cognitive Science concerns how knowledge of specific domains emerges during development. Here we examined how limitations of the visual system during the first days of life may shape subsequent development of face processing abilities. By manipulating the bands of spatial frequencies of face images, we investigated what is…

Fine-grained leukocyte classification with deep residual learning for microscopic images.

PubMed

Qin, Feiwei; Gao, Nannan; Peng, Yong; Wu, Zizhao; Shen, Shuying; Grudtsin, Artur

2018-08-01

Leukocyte classification and cytometry have wide applications in medical domain, previous researches usually exploit machine learning techniques to classify leukocytes automatically. However, constrained by the past development of machine learning techniques, for example, extracting distinctive features from raw microscopic images are difficult, the widely used SVM classifier only has relative few parameters to tune, these methods cannot efficiently handle fine-grained classification cases when the white blood cells have up to 40 categories. Based on deep learning theory, a systematic study is conducted on finer leukocyte classification in this paper. A deep residual neural network based leukocyte classifier is constructed at first, which can imitate the domain expert's cell recognition process, and extract salient features robustly and automatically. Then the deep neural network classifier's topology is adjusted according to the prior knowledge of white blood cell test. After that the microscopic image dataset with almost one hundred thousand labeled leukocytes belonging to 40 categories is built, and combined training strategies are adopted to make the designed classifier has good generalization ability. The proposed deep residual neural network based classifier was tested on microscopic image dataset with 40 leukocyte categories. It achieves top-1 accuracy of 77.80%, top-5 accuracy of 98.75% during the training procedure. The average accuracy on the test set is nearly 76.84%. This paper presents a fine-grained leukocyte classification method for microscopic images, based on deep residual learning theory and medical domain knowledge. Experimental results validate the feasibility and effectiveness of our approach. Extended experiments support that the fine-grained leukocyte classifier could be used in real medical applications, assist doctors in diagnosing diseases, reduce human power significantly. Copyright © 2018 Elsevier B.V. All rights reserved.

Photoreceptor layer map using spectral-domain optical coherence tomography.

PubMed

Lee, Ji Eun; Lim, Dae Won; Bae, Han Yong; Park, Hyun Jin

2009-12-01

To develop a novel method for analysis of the photoreceptor layer map (PLM) generated using spectral-domain optical coherence tomography (OCT). OCT scans were obtained from 20 eyes, 10 with macular holes (MH) and 10 with central serous chorioretinopathy (CSC) using the Macular Cube (512 x 128) protocol of the Cirrus HD-OCT (Carl Zeiss). The scanned data were processed using embedded tools of the advanced visualization. A partial thickness OCT fundus image of the photoreceptor layer was generated by setting the region of interest to a 50-microm thick layer that was parallel and adjacent to the retinal pigment epithelium. The resulting image depicted the photoreceptor layer as a map of the reflectivity in OCT. The PLM was compared with fundus photography, auto-fluorescence, tomography, and retinal thickness map. The signal from the photoreceptor layer of every OCT scan in each case was demonstrated as a single image of PLM in a fundus photograph fashion. In PLM images, detachment of the sensory retina is depicted as a hypo-reflective area, which represents the base of MH and serous detachment in CSC. Relative hypo-reflectivity, which was also noted at closed MH and at recently reattached retina in CSC, was associated with reduced signal from the junction between the inner and outer segments of photoreceptors in OCT images. Using PLM, changes in the area of detachment and reflectivity of the photoreceptor layer could be efficiently monitored. The photoreceptor layer can be analyzed as a map using spectral-domain OCT. In the treatment of both MH and CSC, PLM may provide new pathological information about the photoreceptor layer to expand our understanding of these diseases.

Prostate segmentation by feature enhancement using domain knowledge and adaptive region based operations

NASA Astrophysics Data System (ADS)

Nanayakkara, Nuwan D.; Samarabandu, Jagath; Fenster, Aaron

2006-04-01

Estimation of prostate location and volume is essential in determining a dose plan for ultrasound-guided brachytherapy, a common prostate cancer treatment. However, manual segmentation is difficult, time consuming and prone to variability. In this paper, we present a semi-automatic discrete dynamic contour (DDC) model based image segmentation algorithm, which effectively combines a multi-resolution model refinement procedure together with the domain knowledge of the image class. The segmentation begins on a low-resolution image by defining a closed DDC model by the user. This contour model is then deformed progressively towards higher resolution images. We use a combination of a domain knowledge based fuzzy inference system (FIS) and a set of adaptive region based operators to enhance the edges of interest and to govern the model refinement using a DDC model. The automatic vertex relocation process, embedded into the algorithm, relocates deviated contour points back onto the actual prostate boundary, eliminating the need of user interaction after initialization. The accuracy of the prostate boundary produced by the proposed algorithm was evaluated by comparing it with a manually outlined contour by an expert observer. We used this algorithm to segment the prostate boundary in 114 2D transrectal ultrasound (TRUS) images of six patients scheduled for brachytherapy. The mean distance between the contours produced by the proposed algorithm and the manual outlines was 2.70 ± 0.51 pixels (0.54 ± 0.10 mm). We also showed that the algorithm is insensitive to variations of the initial model and parameter values, thus increasing the accuracy and reproducibility of the resulting boundaries in the presence of noise and artefacts.

Assuring image authenticity within a data grid using lossless digital signature embedding and a HIPAA-compliant auditing system

NASA Astrophysics Data System (ADS)

Lee, Jasper C.; Ma, Kevin C.; Liu, Brent J.

2008-03-01

A Data Grid for medical images has been developed at the Image Processing and Informatics Laboratory, USC to provide distribution and fault-tolerant storage of medical imaging studies across Internet2 and public domain. Although back-up policies and grid certificates guarantee privacy and authenticity of grid-access-points, there still lacks a method to guarantee the sensitive DICOM images have not been altered or corrupted during transmission across a public domain. This paper takes steps toward achieving full image transfer security within the Data Grid by utilizing DICOM image authentication and a HIPAA-compliant auditing system. The 3-D lossless digital signature embedding procedure involves a private 64 byte signature that is embedded into each original DICOM image volume, whereby on the receiving end the signature can to be extracted and verified following the DICOM transmission. This digital signature method has also been developed at the IPILab. The HIPAA-Compliant Auditing System (H-CAS) is required to monitor embedding and verification events, and allows monitoring of other grid activity as well. The H-CAS system federates the logs of transmission and authentication events at each grid-access-point and stores it into a HIPAA-compliant database. The auditing toolkit is installed at the local grid-access-point and utilizes Syslog [1], a client-server standard for log messaging over an IP network, to send messages to the H-CAS centralized database. By integrating digital image signatures and centralized logging capabilities, DICOM image integrity within the Medical Imaging and Informatics Data Grid can be monitored and guaranteed without loss to any image quality.

Robust feature estimation by non-rigid hierarchical image registration and its application in disparity measurement

NASA Astrophysics Data System (ADS)

Badshah, Amir; Choudhry, Aadil Jaleel; Ullah, Shan

2017-03-01

Industries are moving towards automation in order to increase productivity and ensure quality. Variety of electronic and electromagnetic systems are being employed to assist human operator in fast and accurate quality inspection of products. Majority of these systems are equipped with cameras and rely on diverse image processing algorithms. Information is lost in 2D image, therefore acquiring accurate 3D data from 2D images is an open issue. FAST, SURF and SIFT are well-known spatial domain techniques for features extraction and henceforth image registration to find correspondence between images. The efficiency of these methods is measured in terms of the number of perfect matches found. A novel fast and robust technique for stereo-image processing is proposed. It is based on non-rigid registration using modified normalized phase correlation. The proposed method registers two images in hierarchical fashion using quad-tree structure. The registration process works through global to local level resulting in robust matches even in presence of blur and noise. The computed matches can further be utilized to determine disparity and depth for industrial product inspection. The same can be used in driver assistance systems. The preliminary tests on Middlebury dataset produced satisfactory results. The execution time for a 413 x 370 stereo-pair is 500ms approximately on a low cost DSP.

Broadband seismic : case study modeling and data processing

NASA Astrophysics Data System (ADS)

Cahyaningtyas, M. B.; Bahar, A.

2018-03-01

Seismic data with wide range of frequency is needed due to its close relation to resolution and the depth of the target. Low frequency provides deeper penetration for the imaging of deep target. In addition, the wider the frequency bandwidth, the sharper the wavelet. Sharp wavelet is responsible for high-resolution imaging and is very helpful to resolve thin bed. As a result, the demand for broadband seismic data is rising and it spurs the technology development of broadband seismic in oil and gas industry. An obstacle that is frequently found on marine seismic data is the existence of ghost that affects the frequency bandwidth contained on the seismic data. Ghost alters bandwidth to bandlimited. To reduce ghost effect and to acquire broadband seismic data, lots of attempts are used, both on the acquisition and on the processing of seismic data. One of the acquisition technique applied is the multi-level streamer, where some streamers are towed on some levels of depth. Multi-level streamer will yield data with varied ghost notch shown on frequency domain. If the ghost notches are not overlapping, the summation of multi-level streamer data will reduce the ghost effect. The result of the multi-level streamer data processing shows that reduction of ghost notch on frequency domain indeed takes place.

Real-time Graphics Processing Unit Based Fourier Domain Optical Coherence Tomography and Surgical Applications

NASA Astrophysics Data System (ADS)

Zhang, Kang

2011-12-01

In this dissertation, real-time Fourier domain optical coherence tomography (FD-OCT) capable of multi-dimensional micrometer-resolution imaging targeted specifically for microsurgical intervention applications was developed and studied. As a part of this work several ultra-high speed real-time FD-OCT imaging and sensing systems were proposed and developed. A real-time 4D (3D+time) OCT system platform using the graphics processing unit (GPU) to accelerate OCT signal processing, the imaging reconstruction, visualization, and volume rendering was developed. Several GPU based algorithms such as non-uniform fast Fourier transform (NUFFT), numerical dispersion compensation, and multi-GPU implementation were developed to improve the impulse response, SNR roll-off and stability of the system. Full-range complex-conjugate-free FD-OCT was also implemented on the GPU architecture to achieve doubled image range and improved SNR. These technologies overcome the imaging reconstruction and visualization bottlenecks widely exist in current ultra-high speed FD-OCT systems and open the way to interventional OCT imaging for applications in guided microsurgery. A hand-held common-path optical coherence tomography (CP-OCT) distance-sensor based microsurgical tool was developed and validated. Through real-time signal processing, edge detection and feed-back control, the tool was shown to be capable of track target surface and compensate motion. The micro-incision test using a phantom was performed using a CP-OCT-sensor integrated hand-held tool, which showed an incision error less than +/-5 microns, comparing to >100 microns error by free-hand incision. The CP-OCT distance sensor has also been utilized to enhance the accuracy and safety of optical nerve stimulation. Finally, several experiments were conducted to validate the system for surgical applications. One of them involved 4D OCT guided micro-manipulation using a phantom. Multiple volume renderings of one 3D data set were performed with different view angles to allow accurate monitoring of the micro-manipulation, and the user to clearly monitor tool-to-target spatial relation in real-time. The system was also validated by imaging multiple biological samples, such as human fingerprint, human cadaver head and small animals. Compared to conventional surgical microscopes, GPU-based real-time FD-OCT can provide the surgeons with a real-time comprehensive spatial view of the microsurgical region and accurate depth perception.

Quantifying water flow and retention in an unsaturated fracture-facial domain

USGS Publications Warehouse

Nimmo, John R.; Malek-Mohammadi, Siamak

2015-01-01

Hydrologically significant flow and storage of water occur in macropores and fractures that are only partially filled. To accommodate such processes in flow models, we propose a three-domain framework. Two of the domains correspond to water flow and water storage in a fracture-facial region, in addition to the third domain of matrix water. The fracture-facial region, typically within a fraction of a millimeter of the fracture wall, includes a flowing phase whose fullness is determined by the availability and flux of preferentially flowing water, and a static storage portion whose fullness is determined by the local matric potential. The flow domain can be modeled with the source-responsive preferential flow model, and the roughness-storage domain can be modeled with capillary relations applied on the fracture-facial area. The matrix domain is treated using traditional unsaturated flow theory. We tested the model with application to the hydrology of the Chalk formation in southern England, coherently linking hydrologic information including recharge estimates, streamflow, water table fluctuation, imaging by electron microscopy, and surface roughness. The quantitative consistency of the three-domain matrix-microcavity-film model with this body of diverse data supports the hypothesized distinctions and active mechanisms of the three domains and establishes the usefulness of this framework.

A new visual feedback-based magnetorheological haptic master for robot-assisted minimally invasive surgery

NASA Astrophysics Data System (ADS)

Choi, Seung-Hyun; Kim, Soomin; Kim, Pyunghwa; Park, Jinhyuk; Choi, Seung-Bok

2015-06-01

In this study, we developed a novel four-degrees-of-freedom haptic master using controllable magnetorheological (MR) fluid. We also integrated the haptic master with a vision device with image processing for robot-assisted minimally invasive surgery (RMIS). The proposed master can be used in RMIS as a haptic interface to provide the surgeon with a sense of touch by using both kinetic and kinesthetic information. The slave robot, which is manipulated with a proportional-integrative-derivative controller, uses a force sensor to obtain the desired forces from tissue contact, and these desired repulsive forces are then embodied through the MR haptic master. To verify the effectiveness of the haptic master, the desired force and actual force are compared in the time domain. In addition, a visual feedback system is implemented in the RMIS experiment to distinguish between the tumor and organ more clearly and provide better visibility to the operator. The hue-saturation-value color space is adopted for the image processing since it is often more intuitive than other color spaces. The image processing and haptic feedback are realized on surgery performance. In this work, tumor-cutting experiments are conducted under four different operating conditions: haptic feedback on, haptic feedback off, image processing on, and image processing off. The experimental realization shows that the performance index, which is a function of pixels, is different in the four operating conditions.

Meteor tracking via local pattern clustering in spatio-temporal domain

NASA Astrophysics Data System (ADS)

Kukal, Jaromír.; Klimt, Martin; Švihlík, Jan; Fliegel, Karel

2016-09-01

Reliable meteor detection is one of the crucial disciplines in astronomy. A variety of imaging systems is used for meteor path reconstruction. The traditional approach is based on analysis of 2D image sequences obtained from a double station video observation system. Precise localization of meteor path is difficult due to atmospheric turbulence and other factors causing spatio-temporal fluctuations of the image background. The proposed technique performs non-linear preprocessing of image intensity using Box-Cox transform as recommended in our previous work. Both symmetric and asymmetric spatio-temporal differences are designed to be robust in the statistical sense. Resulting local patterns are processed by data whitening technique and obtained vectors are classified via cluster analysis and Self-Organized Map (SOM).

Vision, healing brush, and fiber bundles

NASA Astrophysics Data System (ADS)

Georgiev, Todor

2005-03-01

The Healing Brush is a tool introduced for the first time in Adobe Photoshop (2002) that removes defects in images by seamless cloning (gradient domain fusion). The Healing Brush algorithms are built on a new mathematical approach that uses Fibre Bundles and Connections to model the representation of images in the visual system. Our mathematical results are derived from first principles of human vision, related to adaptation transforms of von Kries type and Retinex theory. In this paper we present the new result of Healing in arbitrary color space. In addition to supporting image repair and seamless cloning, our approach also produces the exact solution to the problem of high dynamic range compression of17 and can be applied to other image processing algorithms.

Restoration of high-resolution AFM images captured with broken probes

NASA Astrophysics Data System (ADS)

Wang, Y. F.; Corrigan, D.; Forman, C.; Jarvis, S.; Kokaram, A.

2012-03-01

A type of artefact is induced by damage of the scanning probe when the Atomic Force Microscope (AFM) captures a material surface structure with nanoscale resolution. This artefact has a dramatic form of distortion rather than the traditional blurring artefacts. Practically, it is not easy to prevent the damage of the scanning probe. However, by using natural image deblurring techniques in image processing domain, a comparatively reliable estimation of the real sample surface structure can be generated. This paper introduces a novel Hough Transform technique as well as a Bayesian deblurring algorithm to remove this type of artefact. The deblurring result is successful at removing blur artefacts in the AFM artefact images. And the details of the fibril surface topography are well preserved.

Wavelet domain image restoration with adaptive edge-preserving regularization.

PubMed

Belge, M; Kilmer, M E; Miller, E L

2000-01-01

In this paper, we consider a wavelet based edge-preserving regularization scheme for use in linear image restoration problems. Our efforts build on a collection of mathematical results indicating that wavelets are especially useful for representing functions that contain discontinuities (i.e., edges in two dimensions or jumps in one dimension). We interpret the resulting theory in a statistical signal processing framework and obtain a highly flexible framework for adapting the degree of regularization to the local structure of the underlying image. In particular, we are able to adapt quite easily to scale-varying and orientation-varying features in the image while simultaneously retaining the edge preservation properties of the regularizer. We demonstrate a half-quadratic algorithm for obtaining the restorations from observed data.

Representing and Inferring Visual Perceptual Skills in Dermatological Image Understanding

ERIC Educational Resources Information Center

Li, Rui

2013-01-01

Experts have a remarkable capability of locating, perceptually organizing, identifying, and categorizing objects in images specific to their domains of expertise. Eliciting and representing their visual strategies and some aspects of domain knowledge will benefit a wide range of studies and applications. For example, image understanding may be…

The pupil's response to affective pictures: Role of image duration, habituation, and viewing mode

PubMed Central

O'Farrell, Katherine R.; Burley, Daniel; Erichsen, Jonathan T.; Newton, Naomi V.; Gray, Nicola S.

2016-01-01

Abstract The pupil has been shown to be sensitive to the emotional content of stimuli. We examined this phenomenon by comparing fearful and neutral images carefully matched in the domains of luminance, image contrast, image color, and complexity of content. The pupil was more dilated after viewing affective pictures, and this effect was (a) shown to be independent of the presentation time of the images (from 100–3,000 ms), (b) not diminished by repeated presentations of the images, and (c) not affected by actively naming the emotion of the stimuli in comparison to passive viewing. Our results show that the emotional modulation of the pupil is present over a range of variables that typically vary from study to study (image duration, number of trials, free viewing vs. task), and encourages the use of pupillometry as a measure of emotional processing in populations where alternative techniques may not be appropriate. PMID:27172997

Realisation and robustness evaluation of a blind spatial domain watermarking technique

NASA Astrophysics Data System (ADS)

Parah, Shabir A.; Sheikh, Javaid A.; Assad, Umer I.; Bhat, Ghulam M.

2017-04-01

A blind digital image watermarking scheme based on spatial domain is presented and investigated in this paper. The watermark has been embedded in intermediate significant bit planes besides the least significant bit plane at the address locations determined by pseudorandom address vector (PAV). The watermark embedding using PAV makes it difficult for an adversary to locate the watermark and hence adds to security of the system. The scheme has been evaluated to ascertain the spatial locations that are robust to various image processing and geometric attacks JPEG compression, additive white Gaussian noise, salt and pepper noise, filtering and rotation. The experimental results obtained, reveal an interesting fact, that, for all the above mentioned attacks, other than rotation, higher the bit plane in which watermark is embedded more robust the system. Further, the perceptual quality of the watermarked images obtained in the proposed system has been compared with some state-of-art watermarking techniques. The proposed technique outperforms the techniques under comparison, even if compared with the worst case peak signal-to-noise ratio obtained in our scheme.

In-vivo and in-situ detection of atherosclerotic plaques using full-range complex-conjugate-free spectral domain optical coherence tomography in the murine carotid

NASA Astrophysics Data System (ADS)

Huang, Yong; Wicks, Robert; Zhang, Kang; Zhao, Mingtao; Tyler, Betty M.; Hwang, Lee; Pradilla, Gustavo; Kang, Jin U.

2013-03-01

Carotid endarterectomy is a common vascular surgical procedure which may help prevent patients' risk of having a stroke. A high resolution real-time imaging technique that can detect the position and size of vascular plaques would provide great value to reduce the risk level and increase the surgical outcome. Optical coherence tomography (OCT), as a high resolution high speed noninvasive imaging technique, was evaluated in this study. Twenty-four 24-week old apolipoprotein E-deficient (ApoE-/-) mice were divided into three groups with 8 in each. One served as the control group fed with normal diet. One served as the study group fed with high-fat diet to induce atherosclerosis. The last served as the treatment group fed with both high-fat diet and medicine to treat atherosclerosis. Full-range, complex-conjugate-free spectral-domain OCT was used to image the mouse aorta near the neck area in-vivo with aorta exposed to the imaging head through surgical procedure. 2D and 3D images of the area of interest were presented real-time through graphics processing unit accelerated algorithm. In-situ imaging of all the mice after perfusion were performed again to validate the invivo detection result and to show potential capability of OCT if combined with surgical saline flush. Later all the imaged arteries were stained with H and E to perform histology analysis. Preliminary results confirmed the accuracy and fast imaging speed of OCT imaging technique in determining atherosclerosis.

Pseudo-shading technique in the two-dimensional domain: a post-processing algorithm for enhancing the Z-buffer of a three-dimensional binary image.

PubMed

Tan, A C; Richards, R

1989-01-01

Three-dimensional (3D) medical graphics is becoming popular in clinical use on tomographic scanners. Research work in 3D reconstructive display of computerized tomography (CT) and magnetic resonance imaging (MRI) scans on conventional computers has produced many so-called pseudo-3D images. The quality of these images depends on the rendering algorithm, the coarseness of the digitized object, the number of grey levels and the image screen resolution. CT and MRI data are fundamentally voxel based and they produce images that are coarse because of the resolution of the data acquisition system. 3D images produced by the Z-buffer depth shading technique suffer loss of detail when complex objects with fine textural detail need to be displayed. Attempts have been made to improve the display of voxel objects, and existing techniques have shown the improvement possible using these post-processing algorithms. The improved rendering technique works on the Z-buffer image to generate a shaded image using a single light source in any direction. The effectiveness of the technique in generating a shaded image has been shown to be a useful means of presenting 3D information for clinical use.

Combined endeavor of Neutrosophic Set and Chan-Vese model to extract accurate liver image from CT scan.

PubMed

Siri, Sangeeta K; Latte, Mrityunjaya V

2017-11-01

Many different diseases can occur in the liver, including infections such as hepatitis, cirrhosis, cancer and over effect of medication or toxins. The foremost stage for computer-aided diagnosis of liver is the identification of liver region. Liver segmentation algorithms extract liver image from scan images which helps in virtual surgery simulation, speedup the diagnosis, accurate investigation and surgery planning. The existing liver segmentation algorithms try to extort exact liver image from abdominal Computed Tomography (CT) scan images. It is an open problem because of ambiguous boundaries, large variation in intensity distribution, variability of liver geometry from patient to patient and presence of noise. A novel approach is proposed to meet challenges in extracting the exact liver image from abdominal CT scan images. The proposed approach consists of three phases: (1) Pre-processing (2) CT scan image transformation to Neutrosophic Set (NS) and (3) Post-processing. In pre-processing, the noise is removed by median filter. The "new structure" is designed to transform a CT scan image into neutrosophic domain which is expressed using three membership subset: True subset (T), False subset (F) and Indeterminacy subset (I). This transform approximately extracts the liver image structure. In post processing phase, morphological operation is performed on indeterminacy subset (I) and apply Chan-Vese (C-V) model with detection of initial contour within liver without user intervention. This resulted in liver boundary identification with high accuracy. Experiments show that, the proposed method is effective, robust and comparable with existing algorithm for liver segmentation of CT scan images. Copyright © 2017 Elsevier B.V. All rights reserved.

A Comprehensive Study of Retinal Vessel Classification Methods in Fundus Images

PubMed Central

Miri, Maliheh; Amini, Zahra; Rabbani, Hossein; Kafieh, Raheleh

2017-01-01

Nowadays, it is obvious that there is a relationship between changes in the retinal vessel structure and diseases such as diabetic, hypertension, stroke, and the other cardiovascular diseases in adults as well as retinopathy of prematurity in infants. Retinal fundus images provide non-invasive visualization of the retinal vessel structure. Applying image processing techniques in the study of digital color fundus photographs and analyzing their vasculature is a reliable approach for early diagnosis of the aforementioned diseases. Reduction in the arteriolar–venular ratio of retina is one of the primary signs of hypertension, diabetic, and cardiovascular diseases which can be calculated by analyzing the fundus images. To achieve a precise measuring of this parameter and meaningful diagnostic results, accurate classification of arteries and veins is necessary. Classification of vessels in fundus images faces with some challenges that make it difficult. In this paper, a comprehensive study of the proposed methods for classification of arteries and veins in fundus images is presented. Considering that these methods are evaluated on different datasets and use different evaluation criteria, it is not possible to conduct a fair comparison of their performance. Therefore, we evaluate the classification methods from modeling perspective. This analysis reveals that most of the proposed approaches have focused on statistics, and geometric models in spatial domain and transform domain models have received less attention. This could suggest the possibility of using transform models, especially data adaptive ones, for modeling of the fundus images in future classification approaches. PMID:28553578

Exemplary design of a DICOM structured report template for CBIR integration into radiological routine

NASA Astrophysics Data System (ADS)

Welter, Petra; Deserno, Thomas M.; Gülpers, Ralph; Wein, Berthold B.; Grouls, Christoph; Günther, Rolf W.

2010-03-01

The large and continuously growing amount of medical image data demands access methods with regards to content rather than simple text-based queries. The potential benefits of content-based image retrieval (CBIR) systems for computer-aided diagnosis (CAD) are evident and have been approved. Still, CBIR is not a well-established part of daily routine of radiologists. We have already presented a concept of CBIR integration for the radiology workflow in accordance with the Integrating the Healthcare Enterprise (IHE) framework. The retrieval result is composed as a Digital Imaging and Communication in Medicine (DICOM) Structured Reporting (SR) document. The use of DICOM SR provides interchange with PACS archive and image viewer. It offers the possibility of further data mining and automatic interpretation of CBIR results. However, existing standard templates do not address the domain of CBIR. We present a design of a SR template customized for CBIR. Our approach is based on the DICOM standard templates and makes use of the mammography and chest CAD SR templates. Reuse of approved SR sub-trees promises a reliable design which is further adopted to the CBIR domain. We analyze the special CBIR requirements and integrate the new concept of similar images into our template. Our approach also includes the new concept of a set of selected images for defining the processed images for CBIR. A commonly accepted pre-defined template for the presentation and exchange of results in a standardized format promotes the widespread application of CBIR in radiological routine.

Medical image processing using neural networks based on multivalued and universal binary neurons

NASA Astrophysics Data System (ADS)

Aizenberg, Igor N.; Aizenberg, Naum N.; Gotko, Eugen S.; Sochka, Vladimir A.

1998-06-01

Cellular Neural Networks (CNN) has become a very good mean for solution of the different kind of image processing problems. CNN based on multi-valued neurons (CNN-MVN) and CNN based on universal binary neurons (CNN-UBN) are the specific kinds of the CNN. MVN and UBN are neurons with complex-valued weights, and complex internal arithmetic. Their main feature is possibility of implementation of the arbitrary mapping between inputs and output described by the MVN, and arbitrary (not only threshold) Boolean function (UBN). Great advantage of the CNN is possibility of implementation of the any linear and many non-linear filters in spatial domain. Together with noise removing using CNN it is possible to implement filters, which can amplify high and medium frequencies. These filters are a very good mean for solution of the enhancement problem, and problem of details extraction against complex background. So, CNN make it possible to organize all the processing process from filtering until extraction of the important details. Organization of this process for medical image processing is considered in the paper. A major attention will be concentrated on the processing of the x-ray and ultrasound images corresponding to different oncology (or closed to oncology) pathologies. Additionally we will consider new structure of the neural network for solution of the problem of differential diagnostics of breast cancer.

Selections from 2017: Image Processing with AstroImageJ

NASA Astrophysics Data System (ADS)

Kohler, Susanna

2017-12-01

Editors note:In these last two weeks of 2017, well be looking at a few selections that we havent yet discussed on AAS Nova from among the most-downloaded paperspublished in AAS journals this year. The usual posting schedule will resume in January.AstroImageJ: Image Processing and Photometric Extraction for Ultra-Precise Astronomical Light CurvesPublished January2017The AIJ image display. A wide range of astronomy specific image display options and image analysis tools are available from the menus, quick access icons, and interactive histogram. [Collins et al. 2017]Main takeaway:AstroImageJ is a new integrated software package presented in a publication led byKaren Collins(Vanderbilt University,Fisk University, andUniversity of Louisville). Itenables new users even at the level of undergraduate student, high school student, or amateur astronomer to quickly start processing, modeling, and plotting astronomical image data.Why its interesting:Science doesnt just happen the momenta telescope captures a picture of a distantobject. Instead, astronomical images must firstbe carefully processed to clean up thedata, and this data must then be systematically analyzed to learn about the objects within it. AstroImageJ as a GUI-driven, easily installed, public-domain tool is a uniquelyaccessible tool for thisprocessing and analysis, allowing even non-specialist users to explore and visualizeastronomical data.Some features ofAstroImageJ:(as reported by Astrobites)Image calibration:generate master flat, dark, and bias framesImage arithmetic:combineimages viasubtraction, addition, division, multiplication, etc.Stack editing:easily perform operations on a series of imagesImage stabilization and image alignment featuresPrecise coordinate converters:calculate Heliocentric and Barycentric Julian DatesWCS coordinates:determine precisely where atelescope was pointed for an image by PlateSolving using Astronomy.netMacro and plugin support:write your own macrosMulti-aperture photometry with interactive light curve fitting:plot light curves of a star in real timeCitationKaren A. Collins et al 2017 AJ 153 77. doi:10.3847/1538-3881/153/2/77

Real-time acquisition and display of flow contrast using speckle variance optical coherence tomography in a graphics processing unit.

PubMed

Xu, Jing; Wong, Kevin; Jian, Yifan; Sarunic, Marinko V

2014-02-01

In this report, we describe a graphics processing unit (GPU)-accelerated processing platform for real-time acquisition and display of flow contrast images with Fourier domain optical coherence tomography (FDOCT) in mouse and human eyes in vivo. Motion contrast from blood flow is processed using the speckle variance OCT (svOCT) technique, which relies on the acquisition of multiple B-scan frames at the same location and tracking the change of the speckle pattern. Real-time mouse and human retinal imaging using two different custom-built OCT systems with processing and display performed on GPU are presented with an in-depth analysis of performance metrics. The display output included structural OCT data, en face projections of the intensity data, and the svOCT en face projections of retinal microvasculature; these results compare projections with and without speckle variance in the different retinal layers to reveal significant contrast improvements. As a demonstration, videos of real-time svOCT for in vivo human and mouse retinal imaging are included in our results. The capability of performing real-time svOCT imaging of the retinal vasculature may be a useful tool in a clinical environment for monitoring disease-related pathological changes in the microcirculation such as diabetic retinopathy.

Bayesian demosaicing using Gaussian scale mixture priors with local adaptivity in the dual tree complex wavelet packet transform domain

NASA Astrophysics Data System (ADS)

Goossens, Bart; Aelterman, Jan; Luong, Hiep; Pizurica, Aleksandra; Philips, Wilfried

2013-02-01

In digital cameras and mobile phones, there is an ongoing trend to increase the image resolution, decrease the sensor size and to use lower exposure times. Because smaller sensors inherently lead to more noise and a worse spatial resolution, digital post-processing techniques are required to resolve many of the artifacts. Color filter arrays (CFAs), which use alternating patterns of color filters, are very popular because of price and power consumption reasons. However, color filter arrays require the use of a post-processing technique such as demosaicing to recover full resolution RGB images. Recently, there has been some interest in techniques that jointly perform the demosaicing and denoising. This has the advantage that the demosaicing and denoising can be performed optimally (e.g. in the MSE sense) for the considered noise model, while avoiding artifacts introduced when using demosaicing and denoising sequentially. In this paper, we will continue the research line of the wavelet-based demosaicing techniques. These approaches are computationally simple and very suited for combination with denoising. Therefore, we will derive Bayesian Minimum Squared Error (MMSE) joint demosaicing and denoising rules in the complex wavelet packet domain, taking local adaptivity into account. As an image model, we will use Gaussian Scale Mixtures, thereby taking advantage of the directionality of the complex wavelets. Our results show that this technique is well capable of reconstructing fine details in the image, while removing all of the noise, at a relatively low computational cost. In particular, the complete reconstruction (including color correction, white balancing etc) of a 12 megapixel RAW image takes 3.5 sec on a recent mid-range GPU.

Multivariate statistical characterization of charged and uncharged domain walls in multiferroic hexagonal YMnO3 single crystal visualized by a spherical aberration-corrected STEM.

PubMed

Matsumoto, Takao; Ishikawa, Ryo; Tohei, Tetsuya; Kimura, Hideo; Yao, Qiwen; Zhao, Hongyang; Wang, Xiaolin; Chen, Dapeng; Cheng, Zhenxiang; Shibata, Naoya; Ikuhara, Yuichi

2013-10-09

A state-of-the-art spherical aberration-corrected STEM was fully utilized to directly visualize the multiferroic domain structure in a hexagonal YMnO3 single crystal at atomic scale. With the aid of multivariate statistical analysis (MSA), we obtained unbiased and quantitative maps of ferroelectric domain structures with atomic resolution. Such a statistical image analysis of the transition region between opposite polarizations has confirmed atomically sharp transitions of ferroelectric polarization both in antiparallel (uncharged) and tail-to-tail 180° (charged) domain boundaries. Through the analysis, a correlated subatomic image shift of Mn-O layers with that of Y layers, exhibiting a double-arc shape of reversed curvatures, have been elucidated. The amount of image shift in Mn-O layers along the c-axis is statistically significant as small as 0.016 nm, roughly one-third of the evident image shift of 0.048 nm in Y layers. Interestingly, a careful analysis has shown that such a subatomic image shift in Mn-O layers vanishes at the tail-to-tail 180° domain boundaries. Furthermore, taking advantage of the annular bright field (ABF) imaging technique combined with MSA, the tilting of MnO5 bipyramids, the very core mechanism of multiferroicity of the material, is evaluated.

Toward More Accurate Iris Recognition Using Cross-Spectral Matching.

PubMed

Nalla, Pattabhi Ramaiah; Kumar, Ajay

2017-01-01

Iris recognition systems are increasingly deployed for large-scale applications such as national ID programs, which continue to acquire millions of iris images to establish identity among billions. However, with the availability of variety of iris sensors that are deployed for the iris imaging under different illumination/environment, significant performance degradation is expected while matching such iris images acquired under two different domains (either sensor-specific or wavelength-specific). This paper develops a domain adaptation framework to address this problem and introduces a new algorithm using Markov random fields model to significantly improve cross-domain iris recognition. The proposed domain adaptation framework based on the naive Bayes nearest neighbor classification uses a real-valued feature representation, which is capable of learning domain knowledge. Our approach to estimate corresponding visible iris patterns from the synthesis of iris patches in the near infrared iris images achieves outperforming results for the cross-spectral iris recognition. In this paper, a new class of bi-spectral iris recognition system that can simultaneously acquire visible and near infra-red images with pixel-to-pixel correspondences is proposed and evaluated. This paper presents experimental results from three publicly available databases; PolyU cross-spectral iris image database, IIITD CLI and UND database, and achieve outperforming results for the cross-sensor and cross-spectral iris matching.

A Shearlet-based algorithm for quantum noise removal in low-dose CT images

NASA Astrophysics Data System (ADS)

Zhang, Aguan; Jiang, Huiqin; Ma, Ling; Liu, Yumin; Yang, Xiaopeng

2016-03-01

Low-dose CT (LDCT) scanning is a potential way to reduce the radiation exposure of X-ray in the population. It is necessary to improve the quality of low-dose CT images. In this paper, we propose an effective algorithm for quantum noise removal in LDCT images using shearlet transform. Because the quantum noise can be simulated by Poisson process, we first transform the quantum noise by using anscombe variance stabilizing transform (VST), producing an approximately Gaussian noise with unitary variance. Second, the non-noise shearlet coefficients are obtained by adaptive hard-threshold processing in shearlet domain. Third, we reconstruct the de-noised image using the inverse shearlet transform. Finally, an anscombe inverse transform is applied to the de-noised image, which can produce the improved image. The main contribution is to combine the anscombe VST with the shearlet transform. By this way, edge coefficients and noise coefficients can be separated from high frequency sub-bands effectively. A number of experiments are performed over some LDCT images by using the proposed method. Both quantitative and visual results show that the proposed method can effectively reduce the quantum noise while enhancing the subtle details. It has certain value in clinical application.

A manual for microcomputer image analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rich, P.M.; Ranken, D.M.; George, J.S.

1989-12-01

This manual is intended to serve three basic purposes: as a primer in microcomputer image analysis theory and techniques, as a guide to the use of IMAGE{copyright}, a public domain microcomputer program for image analysis, and as a stimulus to encourage programmers to develop microcomputer software suited for scientific use. Topics discussed include the principals of image processing and analysis, use of standard video for input and display, spatial measurement techniques, and the future of microcomputer image analysis. A complete reference guide that lists the commands for IMAGE is provided. IMAGE includes capabilities for digitization, input and output of images,more » hardware display lookup table control, editing, edge detection, histogram calculation, measurement along lines and curves, measurement of areas, examination of intensity values, output of analytical results, conversion between raster and vector formats, and region movement and rescaling. The control structure of IMAGE emphasizes efficiency, precision of measurement, and scientific utility. 18 refs., 18 figs., 2 tabs.« less

Terahertz Imaging of Three-Dimensional Dehydrated Breast Cancer Tumors

NASA Astrophysics Data System (ADS)

Bowman, Tyler; Wu, Yuhao; Gauch, John; Campbell, Lucas K.; El-Shenawee, Magda

2017-06-01

This work presents the application of terahertz imaging to three-dimensional formalin-fixed, paraffin-embedded human breast cancer tumors. The results demonstrate the capability of terahertz for in-depth scanning to produce cross section images without the need to slice the tumor. Samples of tumors excised from women diagnosed with infiltrating ductal carcinoma and lobular carcinoma are investigated using a pulsed terahertz time domain imaging system. A time of flight estimation is used to obtain vertical and horizontal cross section images of tumor tissues embedded in paraffin block. Strong agreement is shown comparing the terahertz images obtained by electronically scanning the tumor in-depth in comparison with histopathology images. The detection of cancer tissue inside the block is found to be accurate to depths over 1 mm. Image processing techniques are applied to provide improved contrast and automation of the obtained terahertz images. In particular, unsharp masking and edge detection methods are found to be most effective for three-dimensional block imaging.

Generation and assessment of turntable SAR data for the support of ATR development

NASA Astrophysics Data System (ADS)

Cohen, Marvin N.; Showman, Gregory A.; Sangston, K. James; Sylvester, Vincent B.; Gostin, Lamar; Scheer, C. Ruby

1998-10-01

Inverse synthetic aperture radar (ISAR) imaging on a turntable-tower test range permits convenient generation of high resolution two-dimensional images of radar targets under controlled conditions for testing SAR image processing and for supporting automatic target recognition (ATR) algorithm development. However, turntable ISAR images are often obtained under near-field geometries and hence may suffer geometric distortions not present in airborne SAR images. In this paper, turntable data collected at Georgia Tech's Electromagnetic Test Facility are used to begin to assess the utility of two- dimensional ISAR imaging algorithms in forming images to support ATR development. The imaging algorithms considered include a simple 2D discrete Fourier transform (DFT), a 2-D DFT with geometric correction based on image domain resampling, and a computationally-intensive geometric matched filter solution. Images formed with the various algorithms are used to develop ATR templates, which are then compared with an eye toward utilization in an ATR algorithm.

Adaptive multiple super fast simulated annealing for stochastic microstructure reconstruction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ryu, Seun; Lin, Guang; Sun, Xin

2013-01-01

Fast image reconstruction from statistical information is critical in image fusion from multimodality chemical imaging instrumentation to create high resolution image with large domain. Stochastic methods have been used widely in image reconstruction from two point correlation function. The main challenge is to increase the efficiency of reconstruction. A novel simulated annealing method is proposed for fast solution of image reconstruction. Combining the advantage of very fast cooling schedules, dynamic adaption and parallelization, the new simulation annealing algorithm increases the efficiencies by several orders of magnitude, making the large domain image fusion feasible.

Medical Image Data and Datasets in the Era of Machine Learning-Whitepaper from the 2016 C-MIMI Meeting Dataset Session.

PubMed

Kohli, Marc D; Summers, Ronald M; Geis, J Raymond

2017-08-01

At the first annual Conference on Machine Intelligence in Medical Imaging (C-MIMI), held in September 2016, a conference session on medical image data and datasets for machine learning identified multiple issues. The common theme from attendees was that everyone participating in medical image evaluation with machine learning is data starved. There is an urgent need to find better ways to collect, annotate, and reuse medical imaging data. Unique domain issues with medical image datasets require further study, development, and dissemination of best practices and standards, and a coordinated effort among medical imaging domain experts, medical imaging informaticists, government and industry data scientists, and interested commercial, academic, and government entities. High-level attributes of reusable medical image datasets suitable to train, test, validate, verify, and regulate ML products should be better described. NIH and other government agencies should promote and, where applicable, enforce, access to medical image datasets. We should improve communication among medical imaging domain experts, medical imaging informaticists, academic clinical and basic science researchers, government and industry data scientists, and interested commercial entities.

Imaging of the interaction of low frequency electric fields with biological tissues by optical coherence tomography

NASA Astrophysics Data System (ADS)

Peña, Adrian F.; Devine, Jack; Doronin, Alexander; Meglinski, Igor

2014-03-01

We report the use of conventional Optical Coherence Tomography (OCT) for visualization of propagation of low frequency electric field in soft biological tissues ex vivo. To increase the overall quality of the experimental images an adaptive Wiener filtering technique has been employed. Fourier domain correlation has been subsequently applied to enhance spatial resolution of images of biological tissues influenced by low frequency electric field. Image processing has been performed on Graphics Processing Units (GPUs) utilizing Compute Unified Device Architecture (CUDA) framework in the frequencydomain. The results show that variation in voltage and frequency of the applied electric field relates exponentially to the magnitude of its influence on biological tissue. The magnitude of influence is about twice more for fresh tissue samples in comparison to non-fresh ones. The obtained results suggest that OCT can be used for observation and quantitative evaluation of the electro-kinetic changes in biological tissues under different physiological conditions, functional electrical stimulation, and potentially can be used non-invasively for food quality control.

An image processing and analysis tool for identifying and analysing complex plant root systems in 3D soil using non-destructive analysis: Root1.

PubMed

Flavel, Richard J; Guppy, Chris N; Rabbi, Sheikh M R; Young, Iain M

2017-01-01

The objective of this study was to develop a flexible and free image processing and analysis solution, based on the Public Domain ImageJ platform, for the segmentation and analysis of complex biological plant root systems in soil from x-ray tomography 3D images. Contrasting root architectures from wheat, barley and chickpea root systems were grown in soil and scanned using a high resolution micro-tomography system. A macro (Root1) was developed that reliably identified with good to high accuracy complex root systems (10% overestimation for chickpea, 1% underestimation for wheat, 8% underestimation for barley) and provided analysis of root length and angle. In-built flexibility allowed the user interaction to (a) amend any aspect of the macro to account for specific user preferences, and (b) take account of computational limitations of the platform. The platform is free, flexible and accurate in analysing root system metrics.

Automated Ontology Generation Using Spatial Reasoning

NASA Astrophysics Data System (ADS)

Coalter, Alton; Leopold, Jennifer L.

Recently there has been much interest in using ontologies to facilitate knowledge representation, integration, and reasoning. Correspondingly, the extent of the information embodied by an ontology is increasing beyond the conventional is_a and part_of relationships. To address these requirements, a vast amount of digitally available information may need to be considered when building ontologies, prompting a desire for software tools to automate at least part of the process. The main efforts in this direction have involved textual information retrieval and extraction methods. For some domains extension of the basic relationships could be enhanced further by the analysis of 2D and/or 3D images. For this type of media, image processing algorithms are more appropriate than textual analysis methods. Herein we present an algorithm that, given a collection of 3D image files, utilizes Qualitative Spatial Reasoning (QSR) to automate the creation of an ontology for the objects represented by the images, relating the objects in terms of is_a and part_of relationships and also through unambiguous Relational Connection Calculus (RCC) relations.

A spectrum fractal feature classification algorithm for agriculture crops with hyper spectrum image

NASA Astrophysics Data System (ADS)

Su, Junying

2011-11-01

A fractal dimension feature analysis method in spectrum domain for hyper spectrum image is proposed for agriculture crops classification. Firstly, a fractal dimension calculation algorithm in spectrum domain is presented together with the fast fractal dimension value calculation algorithm using the step measurement method. Secondly, the hyper spectrum image classification algorithm and flowchart is presented based on fractal dimension feature analysis in spectrum domain. Finally, the experiment result of the agricultural crops classification with FCL1 hyper spectrum image set with the proposed method and SAM (spectral angle mapper). The experiment results show it can obtain better classification result than the traditional SAM feature analysis which can fulfill use the spectrum information of hyper spectrum image to realize precision agricultural crops classification.

Wavelet-domain de-noising of OCT images of human brain malignant glioma

NASA Astrophysics Data System (ADS)

Dolganova, I. N.; Aleksandrova, P. V.; Beshplav, S.-I. T.; Chernomyrdin, N. V.; Dubyanskaya, E. N.; Goryaynov, S. A.; Kurlov, V. N.; Reshetov, I. V.; Potapov, A. A.; Tuchin, V. V.; Zaytsev, K. I.

2018-04-01

We have proposed a wavelet-domain de-noising technique for imaging of human brain malignant glioma by optical coherence tomography (OCT). It implies OCT image decomposition using the direct fast wavelet transform, thresholding of the obtained wavelet spectrum and further inverse fast wavelet transform for image reconstruction. By selecting both wavelet basis and thresholding procedure, we have found an optimal wavelet filter, which application improves differentiation of the considered brain tissue classes - i.e. malignant glioma and normal/intact tissue. Namely, it allows reducing the scattering noise in the OCT images and retaining signal decrement for each tissue class. Therefore, the observed results reveals the wavelet-domain de-noising as a prospective tool for improved characterization of biological tissue using the OCT.

Single-pixel imaging based on compressive sensing with spectral-domain optical mixing

NASA Astrophysics Data System (ADS)

Zhu, Zhijing; Chi, Hao; Jin, Tao; Zheng, Shilie; Jin, Xiaofeng; Zhang, Xianmin

2017-11-01

In this letter a single-pixel imaging structure is proposed based on compressive sensing using a spatial light modulator (SLM)-based spectrum shaper. In the approach, an SLM-based spectrum shaper, the pattern of which is a predetermined pseudorandom bit sequence (PRBS), spectrally codes the optical pulse carrying image information. The energy of the spectrally mixed pulse is detected by a single-pixel photodiode and the measurement results are used to reconstruct the image via a sparse recovery algorithm. As the mixing of the image signal and the PRBS is performed in the spectral domain, optical pulse stretching, modulation, compression and synchronization in the time domain are avoided. Experiments are implemented to verify the feasibility of the approach.

The allosteric communication pathways in KIX domain of CBP.

PubMed

Palazzesi, Ferruccio; Barducci, Alessandro; Tollinger, Martin; Parrinello, Michele

2013-08-27

Allosteric regulation plays an important role in a myriad of biomacromolecular processes. Specifically, in a protein, the process of allostery refers to the transmission of a local perturbation, such as ligand binding, to a distant site. Decades after the discovery of this phenomenon, models built on static images of proteins are being reconsidered with the knowledge that protein dynamics plays an important role in its function. Molecular dynamics simulations are a valuable tool for studying complex biomolecular systems, providing an atomistic description of their structure and dynamics. Unfortunately, their predictive power has been limited by the complexity of the biomolecule free-energy surface and by the length of the allosteric timescale (in the order of milliseconds). In this work, we are able to probe the origins of the allosteric changes that transcription factor mixed lineage leukemia (MLL) causes to the interactions of KIX domain of CREB-binding protein (CBP) with phosphorylated kinase inducible domain (pKID), by combing all-atom molecular dynamics with enhanced sampling methods recently developed in our group. We discuss our results in relation to previous NMR studies. We also develop a general simulations protocol to study allosteric phenomena and many other biological processes that occur in the micro/milliseconds timescale.

Image segmentation-based robust feature extraction for color image watermarking

NASA Astrophysics Data System (ADS)

Li, Mianjie; Deng, Zeyu; Yuan, Xiaochen

2018-04-01

This paper proposes a local digital image watermarking method based on Robust Feature Extraction. The segmentation is achieved by Simple Linear Iterative Clustering (SLIC) based on which an Image Segmentation-based Robust Feature Extraction (ISRFE) method is proposed for feature extraction. Our method can adaptively extract feature regions from the blocks segmented by SLIC. This novel method can extract the most robust feature region in every segmented image. Each feature region is decomposed into low-frequency domain and high-frequency domain by Discrete Cosine Transform (DCT). Watermark images are then embedded into the coefficients in the low-frequency domain. The Distortion-Compensated Dither Modulation (DC-DM) algorithm is chosen as the quantization method for embedding. The experimental results indicate that the method has good performance under various attacks. Furthermore, the proposed method can obtain a trade-off between high robustness and good image quality.

THz time-domain spectroscopy imaging for mail inspection

NASA Astrophysics Data System (ADS)

Zhang, Liquan; Wang, Zhongdong; Ma, Yanmei; Hao, Erjuan

2011-08-01

Acquiring messages from the mail but not destroying the envelope is a big challenge in the war of intelligence. If one can read the message of the mail when the envelope is closed, he will benefit from the message asymmetry and be on a good wicket in the competition. In this paper, we presented a transmitted imaging system using THz time-domain spectroscopy technology. We applied the system to image the mail inside an envelope by step-scanning imaging technology. The experimental results show that the THz spectroscopy can image the mail in an envelope. The words in the paper can be identified easily from the background. We also present the THz image of a metal blade in the envelope, in which we can see the metal blade clearly. The results show that it is feasible of THz Time-Domain Spectroscopy Imaging for mail inspection applications.

Full waveform inversion in the frequency domain using classified time-domain residual wavefields

NASA Astrophysics Data System (ADS)

Son, Woohyun; Koo, Nam-Hyung; Kim, Byoung-Yeop; Lee, Ho-Young; Joo, Yonghwan

2017-04-01

We perform the acoustic full waveform inversion in the frequency domain using residual wavefields that have been separated in the time domain. We sort the residual wavefields in the time domain according to the order of absolute amplitudes. Then, the residual wavefields are separated into several groups in the time domain. To analyze the characteristics of the residual wavefields, we compare the residual wavefields of conventional method with those of our residual separation method. From the residual analysis, the amplitude spectrum obtained from the trace before separation appears to have little energy at the lower frequency bands. However, the amplitude spectrum obtained from our strategy is regularized by the separation process, which means that the low-frequency components are emphasized. Therefore, our method helps to emphasize low-frequency components of residual wavefields. Then, we generate the frequency-domain residual wavefields by taking the Fourier transform of the separated time-domain residual wavefields. With these wavefields, we perform the gradient-based full waveform inversion in the frequency domain using back-propagation technique. Through a comparison of gradient directions, we confirm that our separation method can better describe the sub-salt image than the conventional approach. The proposed method is tested on the SEG/EAGE salt-dome model. The inversion results show that our algorithm is better than the conventional gradient based waveform inversion in the frequency domain, especially for deeper parts of the velocity model.

Watermarking scheme for authentication of compressed image

NASA Astrophysics Data System (ADS)

Hsieh, Tsung-Han; Li, Chang-Tsun; Wang, Shuo

2003-11-01

As images are commonly transmitted or stored in compressed form such as JPEG, to extend the applicability of our previous work, a new scheme for embedding watermark in compressed domain without resorting to cryptography is proposed. In this work, a target image is first DCT transformed and quantised. Then, all the coefficients are implicitly watermarked in order to minimize the risk of being attacked on the unwatermarked coefficients. The watermarking is done through registering/blending the zero-valued coefficients with a binary sequence to create the watermark and involving the unembedded coefficients during the process of embedding the selected coefficients. The second-order neighbors and the block itself are considered in the process of the watermark embedding in order to thwart different attacks such as cover-up, vector quantisation, and transplantation. The experiments demonstrate the capability of the proposed scheme in thwarting local tampering, geometric transformation such as cropping, and common signal operations such as lowpass filtering.

An indirect method of imaging the Stokes parameters of a submicron particle with sub-diffraction scattering

NASA Astrophysics Data System (ADS)

Ullah, Kaleem; Garcia-Camara, Braulio; Habib, Muhammad; Yadav, N. P.; Liu, Xuefeng

2018-07-01

In this work, we report an indirect way to image the Stokes parameters of a sample under test (SUT) with sub-diffraction scattering information. We apply our previously reported technique called parametric indirect microscopic imaging (PIMI) based on a fitting and filtration process to measure the Stokes parameters of a submicron particle. A comparison with a classical Stokes measurement is also shown. By modulating the incident field in a precise way, fitting and filtration process at each pixel of the detector in PIMI make us enable to resolve and sense the scattering information of SUT and map them in terms of the Stokes parameters. We believe that our finding can be very useful in fields like singular optics, optical nanoantenna, biomedicine and much more. The spatial signature of the Stokes parameters given by our method has been confirmed with finite difference time domain (FDTD) method.

Optimization of the segmented method for optical compression and multiplexing system

NASA Astrophysics Data System (ADS)

Al Falou, Ayman

2002-05-01

Because of the constant increasing demands of images exchange, and despite the ever increasing bandwidth of the networks, compression and multiplexing of images is becoming inseparable from their generation and display. For high resolution real time motion pictures, electronic performing of compression requires complex and time-consuming processing units. On the contrary, by its inherent bi-dimensional character, coherent optics is well fitted to perform such processes that are basically bi-dimensional data handling in the Fourier domain. Additionally, the main limiting factor that was the maximum frame rate is vanishing because of the recent improvement of spatial light modulator technology. The purpose of this communication is to benefit from recent optical correlation algorithms. The segmented filtering used to store multi-references in a given space bandwidth product optical filter can be applied to networks to compress and multiplex images in a given bandwidth channel.

Impact induced damage assessment by means of Lamb wave image processing

NASA Astrophysics Data System (ADS)

Kudela, Pawel; Radzienski, Maciej; Ostachowicz, Wieslaw

2018-03-01

The aim of this research is an analysis of full wavefield Lamb wave interaction with impact-induced damage at various impact energies in order to find out the limitation of the wavenumber adaptive image filtering method. In other words, the relation between impact energy and damage detectability will be shown. A numerical model based on the time domain spectral element method is used for modeling of Lamb wave propagation and interaction with barely visible impact damage in a carbon-epoxy laminate. Numerical studies are followed by experimental research on the same material with an impact damage induced by various energy and also a Teflon insert simulating delamination. Wavenumber adaptive image filtering and signal processing are used for damage visualization and assessment for both numerical and experimental full wavefield data. It is shown that it is possible to visualize and assess the impact damage location, size and to some extent severity by using the proposed technique.

The current and ideal state of anatomic pathology patient safety.

PubMed

Raab, Stephen Spencer

2014-01-01

An anatomic pathology diagnostic error may be secondary to a number of active and latent technical and/or cognitive components, which may occur anywhere along the total testing process in clinical and/or laboratory domains. For the pathologist interpretive steps of diagnosis, we examine Kahneman's framework of slow and fast thinking to explain different causes of error in precision (agreement) and in accuracy (truth). The pathologist cognitive diagnostic process involves image pattern recognition and a slow thinking error may be caused by the application of different rationally-constructed mental maps of image criteria/patterns by different pathologists. This type of error is partly related to a system failure in standardizing the application of these maps. A fast thinking error involves the flawed leap from image pattern to incorrect diagnosis. In the ideal state, anatomic pathology systems would target these cognitive error causes as well as the technical latent factors that lead to error.

Imaging of gaseous oxygen through DFB laser illumination

NASA Astrophysics Data System (ADS)

Cocola, L.; Fedel, M.; Tondello, G.; Poletto, L.

2016-05-01

A Tunable Diode Laser Absorption Spectroscopy setup with Wavelength Modulation has been used together with a synchronous sampling imaging sensor to obtain two-dimensional transmission-mode images of oxygen content. Modulated laser light from a 760nm DFB source has been used to illuminate a scene from the back while image frames were acquired with a high dynamic range camera. Thanks to synchronous timing between the imaging device and laser light modulation, the traditional lock-in approach used in Wavelength Modulation Spectroscopy was replaced by image processing techniques, and many scanning periods were averaged together to allow resolution of small intensity variation over the already weak absorption signals from oxygen absorption band. After proper binning and filtering, the time-domain waveform obtained from each pixel in a set of frames representing the wavelength scan was used as the single detector signal in a traditional TDLAS-WMS setup, and so processed through a software defined digital lock-in demodulation and a second harmonic signal fitting routine. In this way the WMS artifacts of a gas absorption feature were obtained from each pixel together with intensity normalization parameter, allowing a reconstruction of oxygen distribution in a two-dimensional scene regardless from broadband transmitted intensity. As a first demonstration of the effectiveness of this setup, oxygen absorption images of similar containers filled with either oxygen or nitrogen were acquired and processed.

[An effective method for improving the imaging spatial resolution of terahertz time domain spectroscopy system].

PubMed

Zhang, Zeng-yan; Ji, Te; Zhu, Zhi-yong; Zhao, Hong-wei; Chen, Min; Xiao, Ti-qiao; Guo, Zhi

2015-01-01

Terahertz radiation is an electromagnetic radiation in the range between millimeter waves and far infrared. Due to its low energy and non-ionizing characters, THz pulse imaging emerges as a novel tool in many fields, such as material, chemical, biological medicine, and food safety. Limited spatial resolution is a significant restricting factor of terahertz imaging technology. Near field imaging method was proposed to improve the spatial resolution of terahertz system. Submillimeter scale's spauial resolution can be achieved if the income source size is smaller than the wawelength of the incoming source and the source is very close to the sample. But many changes were needed to the traditional terahertz time domain spectroscopy system, and it's very complex to analyze sample's physical parameters through the terahertz signal. A method of inserting a pinhole upstream to the sample was first proposed in this article to improve the spatial resolution of traditional terahertz time domain spectroscopy system. The measured spatial resolution of terahertz time domain spectroscopy system by knife edge method can achieve spatial resolution curves. The moving stage distance between 10 % and 90 Yo of the maximum signals respectively was defined as the, spatial resolution of the system. Imaging spatial resolution of traditional terahertz time domain spectroscopy system was improved dramatically after inserted a pinhole with diameter 0. 5 mm, 2 mm upstream to the sample. Experimental results show that the spatial resolution has been improved from 1. 276 mm to 0. 774 mm, with the increment about 39 %. Though this simple method, the spatial resolution of traditional terahertz time domain spectroscopy system was increased from millimeter scale to submillimeter scale. A pinhole with diameter 1 mm on a polyethylene plate was taken as sample, to terahertz imaging study. The traditional terahertz time domain spectroscopy system and pinhole inserted terahertz time domain spectroscopy system were applied in the imaging experiment respectively. The relative THz-power loss imaging of samples were use in this article. This method generally delivers the best signal to noise ratio in loss images, dispersion effects are cancelled. Terahertz imaging results show that the sample's boundary was more distinct after inserting the pinhole in front of, sample. The results also conform that inserting pinhole in front of sample can improve the imaging spatial resolution effectively. The theoretical analyses of the method which improve the spatial resolution by inserting a pinhole in front of sample were given in this article. The analyses also indicate that the smaller the pinhole size, the longer spatial coherence length of the system, the better spatial resolution of the system. At the same time the terahertz signal will be reduced accordingly. All the experimental results and theoretical analyses indicate that the method of inserting a pinhole in front of sample can improve the spatial resolution of traditional terahertz time domain spectroscopy system effectively, and it will further expand the application of terahertz imaging technology.

DOCLIB: a software library for document processing

NASA Astrophysics Data System (ADS)

Jaeger, Stefan; Zhu, Guangyu; Doermann, David; Chen, Kevin; Sampat, Summit

2006-01-01

Most researchers would agree that research in the field of document processing can benefit tremendously from a common software library through which institutions are able to develop and share research-related software and applications across academic, business, and government domains. However, despite several attempts in the past, the research community still lacks a widely-accepted standard software library for document processing. This paper describes a new library called DOCLIB, which tries to overcome the drawbacks of earlier approaches. Many of DOCLIB's features are unique either in themselves or in their combination with others, e.g. the factory concept for support of different image types, the juxtaposition of image data and metadata, or the add-on mechanism. We cherish the hope that DOCLIB serves the needs of researchers better than previous approaches and will readily be accepted by a larger group of scientists.

DAGAN: Deep De-Aliasing Generative Adversarial Networks for Fast Compressed Sensing MRI Reconstruction.

PubMed

Yang, Guang; Yu, Simiao; Dong, Hao; Slabaugh, Greg; Dragotti, Pier Luigi; Ye, Xujiong; Liu, Fangde; Arridge, Simon; Keegan, Jennifer; Guo, Yike; Firmin, David; Keegan, Jennifer; Slabaugh, Greg; Arridge, Simon; Ye, Xujiong; Guo, Yike; Yu, Simiao; Liu, Fangde; Firmin, David; Dragotti, Pier Luigi; Yang, Guang; Dong, Hao

2018-06-01

Compressed sensing magnetic resonance imaging (CS-MRI) enables fast acquisition, which is highly desirable for numerous clinical applications. This can not only reduce the scanning cost and ease patient burden, but also potentially reduce motion artefacts and the effect of contrast washout, thus yielding better image quality. Different from parallel imaging-based fast MRI, which utilizes multiple coils to simultaneously receive MR signals, CS-MRI breaks the Nyquist-Shannon sampling barrier to reconstruct MRI images with much less required raw data. This paper provides a deep learning-based strategy for reconstruction of CS-MRI, and bridges a substantial gap between conventional non-learning methods working only on data from a single image, and prior knowledge from large training data sets. In particular, a novel conditional Generative Adversarial Networks-based model (DAGAN)-based model is proposed to reconstruct CS-MRI. In our DAGAN architecture, we have designed a refinement learning method to stabilize our U-Net based generator, which provides an end-to-end network to reduce aliasing artefacts. To better preserve texture and edges in the reconstruction, we have coupled the adversarial loss with an innovative content loss. In addition, we incorporate frequency-domain information to enforce similarity in both the image and frequency domains. We have performed comprehensive comparison studies with both conventional CS-MRI reconstruction methods and newly investigated deep learning approaches. Compared with these methods, our DAGAN method provides superior reconstruction with preserved perceptual image details. Furthermore, each image is reconstructed in about 5 ms, which is suitable for real-time processing.

Frequency domain phosphorescence lifetime Imaging measurements and applications by ISS FastFLIM and multi pulse excitation

NASA Astrophysics Data System (ADS)

Coskun, Ulas C.; Lam, Sandra; Sun, Yuansheng; Liao, Shih-Chu Jeff; George, Steven C.; Barbieri, Beniamino

2017-02-01

Phosphorescence probes can have significantly long lifetimes, on the order of micro- to milli-seconds or longer. In addition, environmental changes can affect the lifetimes of these phosphorescence probes. Thus, Phosphorescence Lifetime Imaging Microscopy (PLIM) is a very useful tool to localize the phosphorescence probes based on their lifetimes to study the variance in the lifetimes due to the micro environmental changes. Since the probes respond to the biologically relevant parameters like oxygen concentration, they can be used to study various biologically relevant processes like cellular metabolism, protein interaction etc. In this case, we study the effects of oxygen on Oxyphor G4 with PLIM. Since The Oxyphor G4 can be quenched by O2, it is a good example of such a probe and has a lifetime around 250us. Here we present the digital frequency domain PLIM technique and study the lifetime of the Oxyphor G4 as a function of the O2 concentration. The lifetime data are successfully presented in a phasor plot for various O2 concentrations and are consistent with the time domain data. Overall, we can analyze the oxygen consumption of varying cells using this technique.

Phasor-based single-molecule fluorescence lifetime imaging using a wide-field photon-counting detector

PubMed Central

Colyer, R.; Siegmund, O.; Tremsin, A.; Vallerga, J.; Weiss, S.; Michalet, X.

2011-01-01

Fluorescence lifetime imaging (FLIM) is a powerful approach to studying the immediate environment of molecules. For example, it is used in biology to study changes in the chemical environment, or to study binding processes, aggregation, and conformational changes by measuring Förster resonance energy transfer (FRET) between donor and acceptor fluorophores. FLIM can be acquired by time-domain measurements (time-correlated single-photon counting) or frequency-domain measurements (with PMT modulation or digital frequency domain acquisition) in a confocal setup, or with wide-field systems (using time-gated cameras). In the best cases, the resulting data is analyzed in terms of multicomponent fluorescence lifetime decays with demanding requirements in terms of signal level (and therefore limited frame rate). Recently, the phasor approach has been proposed as a powerful alternative for fluorescence lifetime analysis of FLIM, ensemble, and single-molecule experiments. Here we discuss the advantages of combining phasor analysis with a new type of FLIM acquisition hardware presented previously, consisting of a high temporal and spatial resolution wide-field single-photon counting device (the H33D detector). Experimental data with live cells and quantum dots will be presented as an illustration of this new approach. PMID:21625298

Defect-induced local variation of crystal phase transition temperature in metal-halide perovskites.

PubMed

Dobrovolsky, Alexander; Merdasa, Aboma; Unger, Eva L; Yartsev, Arkady; Scheblykin, Ivan G

2017-06-26

Solution-processed organometal halide perovskites are hybrid crystalline semiconductors highly interesting for low-cost and efficient optoelectronics. Their properties are dependent on the crystal structure. Literature shows a variety of crystal phase transition temperatures and often a spread of the transition over tens of degrees Kelvin. We explain this inconsistency by demonstrating that the temperature of the tetragonal-to-orthorhombic phase transition in methylammonium lead triiodide depends on the concentration and nature of local defects. Phase transition in individual nanowires was studied by photoluminescence microspectroscopy and super-resolution imaging. We propose that upon cooling from 160 to 140 K, domains of the crystal containing fewer defects stay in the tetragonal phase longer than highly defected domains that readily transform to the high bandgap orthorhombic phase at higher temperatures. The existence of relatively pure tetragonal domains during the phase transition leads to drastic photoluminescence enhancement, which is inhomogeneously distributed across perovskite microcrystals.Understanding crystal phase transition in materials is of fundamental importance. Using luminescence spectroscopy and super-resolution imaging, Dobrovolsky et al. study the transition from the tetragonal to orthorhombic crystal phase in methylammonium lead triiodide nanowires at low temperature.

Hydro morphodynamic modelling in Mediterranean storms: errors and uncertainties under sharp gradients

NASA Astrophysics Data System (ADS)

Sánchez-Arcilla, A.; Gracia, V.; García, M.

2014-02-01

This paper deals with the limits in hydrodynamic and morphodynamic predictions for semi-enclosed coastal domains subject to sharp gradients (in bathymetry, topography, sediment transport and coastal damages). It starts with an overview of wave prediction limits (based on satellite images) in a restricted domain such as is the Mediterranean basin, followed by an in-depth analysis of the Catalan coast, one of the land boundaries of such a domain. The morphodynamic modeling for such gradient regions is next illustrated with the simulation of the largest recorded storm in the Catalan coast, whose morphological impact is a key element of the storm impact. The driving wave and surge conditions produce a morphodynamic response that is validated against the pre and post storm beach state, recovered from two LIDAR images. The quality of the fit is discussed in terms of the physical processes and the suitability of the employed modeling equations. Some remarks about the role of the numerical discretization and boundary conditions are also included in the analysis. From here an assessment of errors and uncertainties is presented, with the aim of establishing the prediction limits for coastal engineering flooding and erosion analyses.

Image-guided biopsy in the esophagus through comprehensive optical frequency domain imaging and laser marking: a study in living swine.

PubMed

Suter, Melissa J; Jillella, Priyanka A; Vakoc, Benjamin J; Halpern, Elkan F; Mino-Kenudson, Mari; Lauwers, Gregory Y; Bouma, Brett E; Nishioka, Norman S; Tearney, Guillermo J

2010-02-01

Random biopsy esophageal surveillance can be subject to sampling errors, resulting in diagnostic uncertainty. Optical frequency domain imaging (OFDI) is a high-speed, 3-dimensional endoscopic microscopy technique. When deployed through a balloon-centering catheter, OFDI can automatically image the entire distal esophagus (6.0 cm length) in approximately 2 minutes. To test a new platform for guided biopsy that allows the operator to select target regions of interest on an OFDI dataset, and then use a laser to mark the esophagus at corresponding locations. The specific goals include determining the optimal laser parameters, testing the accuracy of the laser marking process, evaluating the endoscopic visibility of the laser marks, and assessing the amount of mucosal damage produced by the laser. Experimental study conducted in 5 swine in vivo. Massachusetts General Hospital. Success rate, including endoscopic visibility of laser marks and accuracy of the laser marking process for selected target sites, and extent of the thermal damage caused by the laser marks. All of the laser-induced marks were visible by endoscopy. Target locations were correctly marked with a success rate of 97.07% (95% confidence interval, 89.8%-99.7%). Thermal damage was limited to the superficial layers of the mucosa and was observed to partially heal within 2 days. An animal study with artificially placed targets to simulate pathology. The study demonstrates that laser marking of esophageal sites identified in comprehensive OFDI datasets is feasible and can be performed with sufficient accuracy, precision, and visibility to guide biopsy in vivo.

Quantitative phase imaging and complex field reconstruction by pupil modulation differential phase contrast

PubMed Central

Lu, Hangwen; Chung, Jaebum; Ou, Xiaoze; Yang, Changhuei

2016-01-01

Differential phase contrast (DPC) is a non-interferometric quantitative phase imaging method achieved by using an asymmetric imaging procedure. We report a pupil modulation differential phase contrast (PMDPC) imaging method by filtering a sample’s Fourier domain with half-circle pupils. A phase gradient image is captured with each half-circle pupil, and a quantitative high resolution phase image is obtained after a deconvolution process with a minimum of two phase gradient images. Here, we introduce PMDPC quantitative phase image reconstruction algorithm and realize it experimentally in a 4f system with an SLM placed at the pupil plane. In our current experimental setup with the numerical aperture of 0.36, we obtain a quantitative phase image with a resolution of 1.73μm after computationally removing system aberrations and refocusing. We also extend the depth of field digitally by 20 times to ±50μm with a resolution of 1.76μm. PMID:27828473

High-resolution frequency domain second harmonic optical coherence tomography

NASA Astrophysics Data System (ADS)

Su, Jianping; Tomov, I. V.; Jiang, Yi; Chen, Zhongping

2007-02-01

We used continuum generated in an 8.5 cm long fiber by a femtosecond Yb fiber laser to improve threefold the axial resolution of frequency domain SH-OCT to 12μm. The acquisition time was shortened by more than two orders of magnitude compared to time domain SH-OCT. The system was applied to image biological tissue of fish scales, pig leg tendon and rabbit eye sclera. Highly organized collagen fibrils can be visualized in the recorded images. Polarization dependence on second harmonic has been used to obtain polarization resolved images.

Synthetic aperture radar image formation for the moving-target and near-field bistatic cases

NASA Astrophysics Data System (ADS)

Ding, Yu

This dissertation addresses topics in two areas of synthetic aperture radar (SAR) image formation: time-frequency based SAR imaging of moving targets and a fast backprojection (BP) algorithm for near-field bistatic SAR imaging. SAR imaging of a moving target is a challenging task due to unknown motion of the target. We approach this problem in a theoretical way, by analyzing the Wigner-Ville distribution (WVD) based SAR imaging technique. We derive approximate closed-form expressions for the point-target response of the SAR imaging system, which quantify the image resolution, and show how the blurring in conventional SAR imaging can be eliminated, while the target shift still remains. Our analyses lead to accurate prediction of the target position in the reconstructed images. The derived expressions also enable us to further study additional aspects of WVD-based SAR imaging. Bistatic SAR imaging is more involved than the monostatic SAR case, because of the separation of the transmitter and the receiver, and possibly the changing bistatic geometry. For near-field bistatic SAR imaging, we develop a novel fast BP algorithm, motivated by a newly proposed fast BP algorithm in computer tomography. First we show that the BP algorithm is the spatial-domain counterpart of the benchmark o -- k algorithm in bistatic SAR imaging, yet it avoids the frequency-domain interpolation in the o -- k algorithm, which may cause artifacts in the reconstructed image. We then derive the band-limited property for BP methods in both monostatic and bistatic SAR imaging, which is the basis for developing the fast BP algorithm. We compare our algorithm with other frequency-domain based algorithms, and show that it achieves better reconstructed image quality, while having the same computational complexity as that of the frequency-domain based algorithms.

The elimination of zero-order diffraction of 10.6 μm infrared digital holography

NASA Astrophysics Data System (ADS)

Liu, Ning; Yang, Chao

2017-05-01

A new method of eliminating the zero-order diffraction in infrared digital holography has been raised in this paper. Usually in the reconstruction of digital holography, the spatial frequency of the infrared thermal imager, such as microbolometer, cannot be compared to the common visible CCD or CMOS devices. The infrared imager suffers the problems of large pixel size and low spatial resolution, which cause the zero-order diffraction a severe influence of the reconstruction process of digital holograms. The zero-order diffraction has very large energy and occupies the central region in the spectrum domain. In this paper, we design a new filtering strategy to overcome this problem. This filtering strategy contains two kinds of filtering process which are the Gaussian low-frequency filter and the high-pass phase averaging filter. With the correct set of the calculating parameters, these filtering strategies can work effectively on the holograms and fully eliminate the zero-order diffraction, as well as the two crossover bars shown in the spectrum domain. Detailed explanation and discussion about the new method have been proposed in this paper, and the experiment results are also demonstrated to prove the performance of this method.

[One decade of functional imaging in schizophrenia research. From visualisation of basic information processing steps to molecular-genetic oriented imaging].

PubMed

Tost, H; Meyer-Lindenberg, A; Ruf, M; Demirakça, T; Grimm, O; Henn, F A; Ende, G

2005-02-01

Modern neuroimaging techniques such as magnetic resonance imaging (MRI) and positron emission tomography (PET) have contributed tremendously to our current understanding of psychiatric disorders in the context of functional, biochemical and microstructural alterations of the brain. Since the mid-nineties, functional MRI has provided major insights into the neurobiological correlates of signs and symptoms in schizophrenia. The current paper reviews important fMRI studies of the past decade in the domains of motor, visual, auditory, attentional and working memory function. Special emphasis is given to new methodological approaches, such as the visualisation of medication effects and the functional characterisation of risk genes.

Image security based on iterative random phase encoding in expanded fractional Fourier transform domains

NASA Astrophysics Data System (ADS)

Liu, Zhengjun; Chen, Hang; Blondel, Walter; Shen, Zhenmin; Liu, Shutian

2018-06-01

A novel image encryption method is proposed by using the expanded fractional Fourier transform, which is implemented with a pair of lenses. Here the centers of two lenses are separated at the cross section of axis in optical system. The encryption system is addressed with Fresnel diffraction and phase modulation for the calculation of information transmission. The iterative process with the transform unit is utilized for hiding secret image. The structure parameters of a battery of lenses can be used for additional keys. The performance of encryption method is analyzed theoretically and digitally. The results show that the security of this algorithm is enhanced markedly by the added keys.

Oriented modulation for watermarking in direct binary search halftone images.

PubMed

Guo, Jing-Ming; Su, Chang-Cheng; Liu, Yun-Fu; Lee, Hua; Lee, Jiann-Der

2012-09-01

In this paper, a halftoning-based watermarking method is presented. This method enables high pixel-depth watermark embedding, while maintaining high image quality. This technique is capable of embedding watermarks with pixel depths up to 3 bits without causing prominent degradation to the image quality. To achieve high image quality, the parallel oriented high-efficient direct binary search (DBS) halftoning is selected to be integrated with the proposed orientation modulation (OM) method. The OM method utilizes different halftone texture orientations to carry different watermark data. In the decoder, the least-mean-square-trained filters are applied for feature extraction from watermarked images in the frequency domain, and the naïve Bayes classifier is used to analyze the extracted features and ultimately to decode the watermark data. Experimental results show that the DBS-based OM encoding method maintains a high degree of image quality and realizes the processing efficiency and robustness to be adapted in printing applications.

Comparison of mechanisms involved in image enhancement of Tissue Harmonic Imaging

NASA Astrophysics Data System (ADS)

Cleveland, Robin O.; Jing, Yuan

2006-05-01

Processes that have been suggested as responsible for the improved imaging in Tissue Harmonic Imaging (THI) include: 1) reduced sensitivity to reverberation, 2) reduced sensitivity to aberration, and 3) reduction in the amplitude of diffraction side lobes. A three-dimensional model of the forward propagation of nonlinear sound beams in media with arbitrary spatial properties (a generalized KZK equation) was developed and solved using a time-domain code. The numerical simulations were validated through experiments with tissue mimicking phantoms. The impact of aberration from tissue-like media was determined through simulations using three-dimensional maps of tissue properties derived from datasets available through the Visible Female Project. The experiments and simulations demonstrated that second harmonic imaging suffers less clutter from reverberation and side-lobes but is not immune to aberration effects. The results indicate that side lobe suppression is the most significant reason for the improvement of second harmonic imaging.

Individual differences in solving arithmetic word problems

PubMed Central

2013-01-01

Background With the present functional magnetic resonance imaging (fMRI) study at 3 T, we investigated the neural correlates of visualization and verbalization during arithmetic word problem solving. In the domain of arithmetic, visualization might mean to visualize numbers and (intermediate) results while calculating, and verbalization might mean that numbers and (intermediate) results are verbally repeated during calculation. If the brain areas involved in number processing are domain-specific as assumed, that is, that the left angular gyrus (AG) shows an affinity to the verbal domain, and that the left and right intraparietal sulcus (IPS) shows an affinity to the visual domain, the activation of these areas should show a dependency on an individual’s cognitive style. Methods 36 healthy young adults participated in the fMRI study. The participants habitual use of visualization and verbalization during solving arithmetic word problems was assessed with a short self-report assessment. During the fMRI measurement, arithmetic word problems that had to be solved by the participants were presented in an event-related design. Results We found that visualizers showed greater brain activation in brain areas involved in visual processing, and that verbalizers showed greater brain activation within the left angular gyrus. Conclusions Our results indicate that cognitive styles or preferences play an important role in understanding brain activation. Our results confirm, that strong visualizers use mental imagery more strongly than weak visualizers during calculation. Moreover, our results suggest that the left AG shows a specific affinity to the verbal domain and subserves number processing in a modality-specific way. PMID:23883107

Toward a Unified Theory of Visual Area V4

PubMed Central

Roe, Anna W.; Chelazzi, Leonardo; Connor, Charles E.; Conway, Bevil R.; Fujita, Ichiro; Gallant, Jack L.; Lu, Haidong; Vanduffel, Wim

2016-01-01

Visual area V4 is a midtier cortical area in the ventral visual pathway. It is crucial for visual object recognition and has been a focus of many studies on visual attention. However, there is no unifying view of V4’s role in visual processing. Neither is there an understanding of how its role in feature processing interfaces with its role in visual attention. This review captures our current knowledge of V4, largely derived from electrophysiological and imaging studies in the macaque monkey. Based on recent discovery of functionally specific domains in V4, we propose that the unifying function of V4 circuitry is to enable selective extraction of specific functional domain-based networks, whether it be by bottom-up specification of object features or by top-down attentionally driven selection. PMID:22500626

Tension modulates actin filament polymerization mediated by formin and profilin

PubMed Central

Courtemanche, Naomi; Lee, Ja Yil; Pollard, Thomas D.; Greene, Eric C.

2013-01-01

Formins promote processive elongation of actin filaments for cytokinetic contractile rings and other cellular structures. In vivo, these structures are exposed to tension, but the effect of tension on these processes was unknown. Here we used single-molecule imaging to investigate the effects of tension on actin polymerization mediated by yeast formin Bni1p. Small forces on the filaments dramatically slowed formin-mediated polymerization in the absence of profilin, but resulted in faster polymerization in the presence of profilin. We propose that force shifts the conformational equilibrium of the end of a filament associated with formin homology 2 domains toward the closed state that precludes polymerization, but that profilin–actin associated with formin homology 1 domains reverses this effect. Thus, physical forces strongly influence actin assembly by formin Bni1p. PMID:23716666

An improved interface to process GPR data by means of microwave tomography

NASA Astrophysics Data System (ADS)

Catapano, Ilaria; Affinito, Antonio; Soldovieri, Francesco

2015-04-01

Ground Penetrating Radar (GPR) systems are well assessed non-invasive diagnostic tools, which are worth being considered in civil engineering surveys since they allow to gather information on constructive materials and techniques of manmade structures as well as on the aging and risk factors affecting their healthiness. However, the practical use of GPR depends strictly on the availability of data processing tools, on one hand, capable of providing reliable and easily interpretable images of the probed scenarios and, on the other side, easy to be used by not expert users. In this frame, 2D and full 3D microwave tomographic approaches based on the Born approximation have been developed and proved to be effective in several practical conditions [1, 2]. Generally speaking, a GPR data processing chain exploiting microwave tomography is made by two main steps: the pre-processing and the data inversion. The pre-processing groups standard procedures like start time correction, muting and background removal, which are performed in time domain to remove the direct antennas coupling, to reduce noise and to improve the targets footprint. The data inversion faces the imaging as the solution of a linear inverse scattering problem in the frequency domain. Hence, a linear integral equation relating the scattered field (i.e. the data) to the unknown electric contrast function is solved by using the truncated Singular Value Decomposition (SVD) as a regularized inversion scheme. Pre-processing and the data inversion are linked by a Discrete Fourier Transform (DFT), which allows to pass from the time domain to the frequency domain. In this respect, a frequency analysis of the GPR signals (traces) is also performed to identify the actual frequency range of the data. Unfortunately, the adoption of microwave tomography is strongly subjected to the involvement of expert people capable of managing properly the processing chain. To overcome this drawback, a couple of years ago, an end-user friendly software interface was developed to make possible a simple management of 2D microwave tomographic approaches [3]. Aim of this communication, is to present a novel interface, which is a significantly improved version with respect to the previous one. In particular, the new interface allows both 2D and full 3D imaging by taking as input GPR data gathered by means of different measurement configurations, i.e. by using down looking systems, with the antenna located close to the air-medium interface or at non negligible (in terms of the probing wavelength) distance from it, as well as by means of airborne and forward looking systems. In this frame, the users can select the data format among those of the most common commercial GPR systems or process data gathered by means of GPR prototypes, provided that they are saved in ASCII format. Moreover, the users can perform all the steps, which are needed to obtain tomographic images, and select the Born approximation based approach most suitable to the adopted measurement configuration. Raw-radargrams, intermediate and final results can be displayed for users convenience. REFERENCES [1] I. Catapano, R. Di Napoli, F. Soldovieri, M. Bavusi, A. Loperte, J. Dumoulin, "Structural monitoring via microwave tomography-enhanced GPR: the Montagnole test site", J. Geophys. Eng. 9, S100-S107, 2012. [2] I. Catapano, A. Affinito, G. Gennarelli, F.di Maio, A. Loperte, F. Soldovieri, "Full three-dimensional imaging via ground penetrating radar: assessment in controlled conditions and on field for archaeological prospecting", Appl. Phys. A, 2013, DOI 10.1007/s00339-013-8053-0. [3] I. Catapano, A. Affinito, F. Soldovieri, A user friendly interface for microwave tomography enhanced GPR surveys", EGU General Assembly 2013, vol. 15.

Imaging first impressions: distinct neural processing of verbal and nonverbal social information.

PubMed

Kuzmanovic, Bojana; Bente, Gary; von Cramon, D Yves; Schilbach, Leonhard; Tittgemeyer, Marc; Vogeley, Kai

2012-03-01

First impressions profoundly influence our attitudes and behavior toward others. However, little is known about whether and to what degree the cognitive processes that underlie impression formation depend on the domain of the available information about the target person. To investigate the neural bases of the influence of verbal as compared to nonverbal information on interpersonal judgments, we identified brain regions where the BOLD signal parametrically increased with increasing strength of evaluation based on either short text vignettes or mimic and gestural behavior. While for verbal stimuli the increasing strength of subjective evaluation was correlated with increased neural activation of precuneus and posterior cingulate cortex (PC/PCC), a similar effect was observed for nonverbal stimuli in the amygdala. These findings support the assumption that qualitatively different cognitive operations underlie person evaluation depending upon the stimulus domain: while the processing of nonverbal person information may be more strongly associated with affective processing as indexed by recruitment of the amygdala, verbal person information engaged the PC/PCC that has been related to social inferential processing. Copyright © 2011 Elsevier Inc. All rights reserved.

Inverse scattering pre-stack depth imaging and it's comparison to some depth migration methods for imaging rich fault complex structure

NASA Astrophysics Data System (ADS)

Nurhandoko, Bagus Endar B.; Sukmana, Indriani; Mubarok, Syahrul; Deny, Agus; Widowati, Sri; Kurniadi, Rizal

2012-06-01

Migration is important issue for seismic imaging in complex structure. In this decade, depth imaging becomes important tools for producing accurate image in depth imaging instead of time domain imaging. The challenge of depth migration method, however, is in revealing the complex structure of subsurface. There are many methods of depth migration with their advantages and weaknesses. In this paper, we show our propose method of pre-stack depth migration based on time domain inverse scattering wave equation. Hopefully this method can be as solution for imaging complex structure in Indonesia, especially in rich thrusting fault zones. In this research, we develop a recent advance wave equation migration based on time domain inverse scattering wave which use more natural wave propagation using scattering wave. This wave equation pre-stack depth migration use time domain inverse scattering wave equation based on Helmholtz equation. To provide true amplitude recovery, an inverse of divergence procedure and recovering transmission loss are considered of pre-stack migration. Benchmarking the propose inverse scattering pre-stack depth migration with the other migration methods are also presented, i.e.: wave equation pre-stack depth migration, waveequation depth migration, and pre-stack time migration method. This inverse scattering pre-stack depth migration could image successfully the rich fault zone which consist extremely dip and resulting superior quality of seismic image. The image quality of inverse scattering migration is much better than the others migration methods.

Image reconstruction from few-view CT data by gradient-domain dictionary learning.

PubMed

Hu, Zhanli; Liu, Qiegen; Zhang, Na; Zhang, Yunwan; Peng, Xi; Wu, Peter Z; Zheng, Hairong; Liang, Dong

2016-05-21

Decreasing the number of projections is an effective way to reduce the radiation dose exposed to patients in medical computed tomography (CT) imaging. However, incomplete projection data for CT reconstruction will result in artifacts and distortions. In this paper, a novel dictionary learning algorithm operating in the gradient-domain (Grad-DL) is proposed for few-view CT reconstruction. Specifically, the dictionaries are trained from the horizontal and vertical gradient images, respectively and the desired image is reconstructed subsequently from the sparse representations of both gradients by solving the least-square method. Since the gradient images are sparser than the image itself, the proposed approach could lead to sparser representations than conventional DL methods in the image-domain, and thus a better reconstruction quality is achieved. To evaluate the proposed Grad-DL algorithm, both qualitative and quantitative studies were employed through computer simulations as well as real data experiments on fan-beam and cone-beam geometry. The results show that the proposed algorithm can yield better images than the existing algorithms.

Observation of ferroelastic domains in layered magnetic compounds using birefringence imaging

NASA Astrophysics Data System (ADS)

Miura, Yoko; Okumura, Kazuya; Manaka, Hirotaka

2018-03-01

The two-dimensional Heisenberg antiferromagnet (C2H5NH3)2CuCl4 is a candidate compound for the coexistence of ferroelectricity and ferroelasticity; however, the microscopic observations of multiferroic domains may still be unclear. In-plane birefringence imaging measurements were performed to observe the manner in which the ferroelectric and the ferroelastic domains change during phase transitions between 15 K and 300 K. It was found that 90° ferroelastic domains appeared in the ab-plane at 300 K. As the temperature decreased toward 15 K, each domain inverted at a certain temperature (T a) without structural or magnetic phase transitions. The value of T a was found to be significantly influenced by external stresses; therefore, birefringence imaging techniques are useful for investigating variations in ferroelastic domains with temperature. Furthermore, a structural phase transition from orthorhombic to monoclinic or triclinic occurred at 230 ~ 240 K; however, no spontaneous polarization appeared in the ab-plane over the entire investigated range.

Spectral domain optical coherence tomography findings in acute syphilitic posterior placoid chorioretinitis.

PubMed

Burkholder, Bryn M; Leung, Theresa G; Ostheimer, Trucian A; Butler, Nicholas J; Thorne, Jennifer E; Dunn, James P

2014-01-27

We describe the spectral domain optical coherence tomography (SD-OCT) findings in three patients with acute syphilitic posterior placoid chorioretinitis (ASPPC). The SD-OCT images demonstrate the pathologic changes in ASPPC with a high level of anatomic detail and may provide information about the pathophysiology of the disease. We report a series of three consecutive patients seen at the Wilmer Eye Institute in 2012 and 2013 who presented with clinical and laboratory findings consistent with a diagnosis of unilateral ASPPC. Two of the three patients had HIV co-infection with good immune recovery. SD-OCT images from their initial (pre-treatment) presentation demonstrated thickening and hyperreflective nodularity of the choroid-retinal pigment epithelium (RPE) complex, with focal disruption of the overlying photoreceptor inner segment-outer segment junction in the areas corresponding to the retinal lesions seen on clinical examination. These changes improved with intravenous antibiotic treatment over a 3-month period of follow-up. SD-OCT imaging in ASPPC demonstrates reversible, focal thickening, and nodularity of the RPE with disruption of the overlying photoreceptor inner segment-outer segment junction. We believe that these SD-OCT images support the concept that ASPPC involves an inflammatory process at the level of the choroid-RPE with resultant structural and functional changes in the retinal photoreceptors. Further study with OCT imaging may be helpful in better understanding this disease.