WorldWideScience

Sample records for improved imaging methods

  1. Improved radionuclide bone imaging agent injection needle withdrawal method can improve image quality

    International Nuclear Information System (INIS)

    Qin Yongmei; Wang Laihao; Zhao Lihua; Guo Xiaogang; Kong Qingfeng

    2009-01-01

    Objective: To investigate the improvement of radionuclide bone imaging agent injection needle withdrawal method on whole body bone scan image quality. Methods: Elbow vein injection syringe needle directly into the bone imaging agent in the routine group of 117 cases, with a cotton swab needle injection method for the rapid pull out the needle puncture point pressing, pressing moment. Improvement of 117 cases of needle injection method to put two needles into the skin swabs and blood vessels, pull out the needle while pressing two or more entry point 5min. After 2 hours underwent whole body bone SPECT imaging plane. Results: The conventional group at the injection site imaging agents uptake rate was 16.24%, improved group was 2.56%. Conclusion: The modified bone imaging agent injection needle withdrawal method, injection-site imaging agent uptake were significantly decreased whole body bone imaging can improve image quality. (authors)

  2. Improved image alignment method in application to X-ray images and biological images.

    Science.gov (United States)

    Wang, Ching-Wei; Chen, Hsiang-Chou

    2013-08-01

    Alignment of medical images is a vital component of a large number of applications throughout the clinical track of events; not only within clinical diagnostic settings, but prominently so in the area of planning, consummation and evaluation of surgical and radiotherapeutical procedures. However, image registration of medical images is challenging because of variations on data appearance, imaging artifacts and complex data deformation problems. Hence, the aim of this study is to develop a robust image alignment method for medical images. An improved image registration method is proposed, and the method is evaluated with two types of medical data, including biological microscopic tissue images and dental X-ray images and compared with five state-of-the-art image registration techniques. The experimental results show that the presented method consistently performs well on both types of medical images, achieving 88.44 and 88.93% averaged registration accuracies for biological tissue images and X-ray images, respectively, and outperforms the benchmark methods. Based on the Tukey's honestly significant difference test and Fisher's least square difference test tests, the presented method performs significantly better than all existing methods (P ≤ 0.001) for tissue image alignment, and for the X-ray image registration, the proposed method performs significantly better than the two benchmark b-spline approaches (P < 0.001). The software implementation of the presented method and the data used in this study are made publicly available for scientific communities to use (http://www-o.ntust.edu.tw/∼cweiwang/ImprovedImageRegistration/). cweiwang@mail.ntust.edu.tw.

  3. [An Improved Spectral Quaternion Interpolation Method of Diffusion Tensor Imaging].

    Science.gov (United States)

    Xu, Yonghong; Gao, Shangce; Hao, Xiaofei

    2016-04-01

    Diffusion tensor imaging(DTI)is a rapid development technology in recent years of magnetic resonance imaging.The diffusion tensor interpolation is a very important procedure in DTI image processing.The traditional spectral quaternion interpolation method revises the direction of the interpolation tensor and can preserve tensors anisotropy,but the method does not revise the size of tensors.The present study puts forward an improved spectral quaternion interpolation method on the basis of traditional spectral quaternion interpolation.Firstly,we decomposed diffusion tensors with the direction of tensors being represented by quaternion.Then we revised the size and direction of the tensor respectively according to different situations.Finally,we acquired the tensor of interpolation point by calculating the weighted average.We compared the improved method with the spectral quaternion method and the Log-Euclidean method by the simulation data and the real data.The results showed that the improved method could not only keep the monotonicity of the fractional anisotropy(FA)and the determinant of tensors,but also preserve the tensor anisotropy at the same time.In conclusion,the improved method provides a kind of important interpolation method for diffusion tensor image processing.

  4. Improvement of image quality using interpolated projection data estimation method in SPECT

    International Nuclear Information System (INIS)

    Takaki, Akihiro; Soma, Tsutomu; Murase, Kenya; Kojima, Akihiro; Asao, Kimie; Kamada, Shinya; Matsumoto, Masanori

    2009-01-01

    General data acquisition for single photon emission computed tomography (SPECT) is performed in 90 or 60 directions, with a coarse pitch of approximately 4-6 deg for a rotation of 360 deg or 180 deg, using a gamma camera. No data between adjacent projections will be sampled under these circumstances. The aim of the study was to develop a method to improve SPECT image quality by generating lacking projection data through interpolation of data obtained with a coarse pitch such as 6 deg. The projection data set at each individual degree in 360 directions was generated by a weighted average interpolation method from the projection data acquired with a coarse sampling angle (interpolated projection data estimation processing method, IPDE method). The IPDE method was applied to the numerical digital phantom data, actual phantom data and clinical brain data with Tc-99m ethyle cysteinate dimer (ECD). All SPECT images were reconstructed by the filtered back-projection method and compared with the original SPECT images. The results confirmed that streak artifacts decreased by apparently increasing a sampling number in SPECT after interpolation and also improved signal-to-noise (S/N) ratio of the root mean square uncertainty value. Furthermore, the normalized mean square error values, compared with standard images, had similar ones after interpolation. Moreover, the contrast and concentration ratios increased their effects after interpolation. These results indicate that effective improvement of image quality can be expected with interpolation. Thus, image quality and the ability to depict images can be improved while maintaining the present acquisition time and image quality. In addition, this can be achieved more effectively than at present even if the acquisition time is reduced. (author)

  5. A Study on the Improvement of Digital Periapical Images using Image Interpolation Methods

    International Nuclear Information System (INIS)

    Song, Nam Kyu; Koh, Kwang Joon

    1998-01-01

    Image resampling is of particular interest in digital radiology. When resampling an image to a new set of coordinate, there appears blocking artifacts and image changes. To enhance image quality, interpolation algorithms have been used. Resampling is used to increase the number of points in an image to improve its appearance for display. The process of interpolation is fitting a continuous function to the discrete points in the digital image. The purpose of this study was to determine the effects of the seven interpolation functions when image resampling in digital periapical images. The images were obtained by Digora, CDR and scanning of Ektaspeed plus periapical radiograms on the dry skull and human subject. The subjects were exposed to intraoral X-ray machine at 60 kVp and 70 kVp with exposure time varying between 0.01 and 0.50 second. To determine which interpolation method would provide the better image, seven functions were compared ; (1) nearest neighbor (2) linear (3) non-linear (4) facet model (5) cubic convolution (6) cubic spline (7) gray segment expansion. And resampled images were compared in terms of SNR (Signal to Noise Ratio) and MTF (Modulation Transfer Function) coefficient value. The obtained results were as follows ; 1. The highest SNR value (75.96 dB) was obtained with cubic convolution method and the lowest SNR value (72.44 dB) was obtained with facet model method among seven interpolation methods. 2. There were significant differences of SNR values among CDR, Digora and film scan (P 0.05). 4. There were significant differences of MTF coefficient values between linear interpolation method and the other six interpolation methods (P<0.05). 5. The speed of computation time was the fastest with nearest neighbor method and the slowest with non-linear method. 6. The better image was obtained with cubic convolution, cubic spline and gray segment method in ROC analysis. 7. The better sharpness of edge was obtained with gray segment expansion method

  6. IMPROVING THE QUALITY OF NEAR-INFRARED IMAGING OF IN VIVOBLOOD VESSELS USING IMAGE FUSION METHODS

    DEFF Research Database (Denmark)

    Jensen, Andreas Kryger; Savarimuthu, Thiusius Rajeeth; Sørensen, Anders Stengaard

    2009-01-01

    We investigate methods for improving the visual quality of in vivo images of blood vessels in the human forearm. Using a near-infrared light source and a dual CCD chip camera system capable of capturing images at visual and nearinfrared spectra, we evaluate three fusion methods in terms...... of their capability of enhancing the blood vessels while preserving the spectral signature of the original color image. Furthermore, we investigate a possibility of removing hair in the images using a fusion rule based on the "a trous" stationary wavelet decomposition. The method with the best overall performance...... with both speed and quality in mind is the Intensity Injection method. Using the developed system and the methods presented in this article, it is possible to create images of high visual quality with highly emphasized blood vessels....

  7. A method of image improvement in three-dimensional imaging

    International Nuclear Information System (INIS)

    Suto, Yasuzo; Huang, Tewen; Furuhata, Kentaro; Uchino, Masafumi.

    1988-01-01

    In general, image interpolation is required when the surface configurations of such structures as bones and organs are three-dimensionally constructed from the multi-sliced images obtained by CT. Image interpolation is a processing method whereby an artificial image is inserted between two adjacent slices to make spatial resolution equal to slice resolution in appearance. Such image interpolation makes it possible to increase the image quality of the constructed three-dimensional image. In our newly-developed algorithm, we have converted the presently and subsequently sliced images to distance images, and generated the interpolation images from these two distance images. As a result, compared with the previous method, three-dimensional images with better image quality have been constructed. (author)

  8. Improved Method of Detection Falsification Results the Digital Image in Conditions of Attacks

    Directory of Open Access Journals (Sweden)

    Kobozeva A.A.

    2016-08-01

    Full Text Available The modern level of information technologies development has led to unheard ease embodiments hitherto unauthorized modifications of digital content. At the moment, very important question is the effective expert examination of authenticity of digital images, video, audio, development of the methods for identification and localization of violations of their integrity using these contents for purposes other than entertainment. Present paper deals with the improvement of the detection method of the cloning results in digital images - one of the most frequently used in the software tools falsification realized in all modern graphics editors. The method is intended for clone detection areas and pre-image in terms of additional disturbing influences in the image after the cloning operation for "masking" of the results, which complicates the search process. The improvement is aimed at reducing the number of "false alarms", when the area of the clone / pre-image detected in the original image or the localization of the identified areas do not correspond to the real clone and pre-image. The proposed improvement, based on analysis of different sizes per-pixel image blocks with the least difference from each other, has made it possible efficient functioning of the method, regardless of the specificity of the analyzed digital image.

  9. Edge detection of optical subaperture image based on improved differential box-counting method

    Science.gov (United States)

    Li, Yi; Hui, Mei; Liu, Ming; Dong, Liquan; Kong, Lingqin; Zhao, Yuejin

    2018-01-01

    Optical synthetic aperture imaging technology is an effective approach to improve imaging resolution. Compared with monolithic mirror system, the image of optical synthetic aperture system is often more complex at the edge, and as a result of the existence of gap between segments, which makes stitching becomes a difficult problem. So it is necessary to extract the edge of subaperture image for achieving effective stitching. Fractal dimension as a measure feature can describe image surface texture characteristics, which provides a new approach for edge detection. In our research, an improved differential box-counting method is used to calculate fractal dimension of image, then the obtained fractal dimension is mapped to grayscale image to detect edges. Compared with original differential box-counting method, this method has two improvements as follows: by modifying the box-counting mechanism, a box with a fixed height is replaced by a box with adaptive height, which solves the problem of over-counting the number of boxes covering image intensity surface; an image reconstruction method based on super-resolution convolutional neural network is used to enlarge small size image, which can solve the problem that fractal dimension can't be calculated accurately under the small size image, and this method may well maintain scale invariability of fractal dimension. The experimental results show that the proposed algorithm can effectively eliminate noise and has a lower false detection rate compared with the traditional edge detection algorithms. In addition, this algorithm can maintain the integrity and continuity of image edge in the case of retaining important edge information.

  10. Improved method of in vivo respiratory-gated micro-CT imaging

    Energy Technology Data Exchange (ETDEWEB)

    Walters, Erin B; Panda, Kunal; Bankson, James A; Brown, Ellana; Cody, Dianna D [Department of Imaging Physics, Unit 56, University of Texas M. D. Anderson Cancer Center, 1515 Holcombe Blvd., Houston, TX 77030 (United States)

    2004-09-07

    The presence of motion artifacts is a typical problem in thoracic imaging. However, synchronizing the respiratory cycle with computed tomography (CT) image acquisition can reduce these artifacts. We currently employ a method of in vivo respiratory-gated micro-CT imaging for small laboratory animals (mice). This procedure involves the use of a ventilator that controls the respiratory cycle of the animal and provides a digital output signal that is used to trigger data acquisition. After inspection of the default respiratory trigger timing, we hypothesized that image quality could be improved by moving the data-acquisition window to a portion of the cycle with less respiratory motion. For this reason, we developed a simple delay circuit to adjust the timing of the ventilator signal that initiates micro-CT data acquisition. This delay circuit decreases motion artifacts and substantially improves image quality.

  11. Improved method of in vivo respiratory-gated micro-CT imaging

    International Nuclear Information System (INIS)

    Walters, Erin B; Panda, Kunal; Bankson, James A; Brown, Ellana; Cody, Dianna D

    2004-01-01

    The presence of motion artifacts is a typical problem in thoracic imaging. However, synchronizing the respiratory cycle with computed tomography (CT) image acquisition can reduce these artifacts. We currently employ a method of in vivo respiratory-gated micro-CT imaging for small laboratory animals (mice). This procedure involves the use of a ventilator that controls the respiratory cycle of the animal and provides a digital output signal that is used to trigger data acquisition. After inspection of the default respiratory trigger timing, we hypothesized that image quality could be improved by moving the data-acquisition window to a portion of the cycle with less respiratory motion. For this reason, we developed a simple delay circuit to adjust the timing of the ventilator signal that initiates micro-CT data acquisition. This delay circuit decreases motion artifacts and substantially improves image quality

  12. An improved K-means clustering method for cDNA microarray image segmentation.

    Science.gov (United States)

    Wang, T N; Li, T J; Shao, G F; Wu, S X

    2015-07-14

    Microarray technology is a powerful tool for human genetic research and other biomedical applications. Numerous improvements to the standard K-means algorithm have been carried out to complete the image segmentation step. However, most of the previous studies classify the image into two clusters. In this paper, we propose a novel K-means algorithm, which first classifies the image into three clusters, and then one of the three clusters is divided as the background region and the other two clusters, as the foreground region. The proposed method was evaluated on six different data sets. The analyses of accuracy, efficiency, expression values, special gene spots, and noise images demonstrate the effectiveness of our method in improving the segmentation quality.

  13. Method and apparatus for improving the alignment of radiographic images

    International Nuclear Information System (INIS)

    Schuller, P.D.; Hatcher, D.C.; Caelli, T.M.; Eggert, F.M.; Yuzyk, J.

    1991-01-01

    This invention relates generally to the field of radiology, and has to do particularly with a method and apparatus for improving the alignment of radiographic images taken at different times of the same tissue structure, so that the images can be sequentially shown in aligned condition, whereby changes in the structure can be noted. (author). 10 figs

  14. Cryptanalysis of "an improvement over an image encryption method based on total shuffling"

    Science.gov (United States)

    Akhavan, A.; Samsudin, A.; Akhshani, A.

    2015-09-01

    In the past two decades, several image encryption algorithms based on chaotic systems had been proposed. Many of the proposed algorithms are meant to improve other chaos based and conventional cryptographic algorithms. Whereas, many of the proposed improvement methods suffer from serious security problems. In this paper, the security of the recently proposed improvement method for a chaos-based image encryption algorithm is analyzed. The results indicate the weakness of the analyzed algorithm against chosen plain-text.

  15. A comparative study on methods of improving SCR for ship detection in SAR image

    Science.gov (United States)

    Lang, Haitao; Shi, Hongji; Tao, Yunhong; Ma, Li

    2017-10-01

    Knowledge about ship positions plays a critical role in a wide range of maritime applications. To improve the performance of ship detector in SAR image, an effective strategy is improving the signal-to-clutter ratio (SCR) before conducting detection. In this paper, we present a comparative study on methods of improving SCR, including power-law scaling (PLS), max-mean and max-median filter (MMF1 and MMF2), method of wavelet transform (TWT), traditional SPAN detector, reflection symmetric metric (RSM), scattering mechanism metric (SMM). The ability of SCR improvement to SAR image and ship detection performance associated with cell- averaging CFAR (CA-CFAR) of different methods are evaluated on two real SAR data.

  16. A method for normalizing pathology images to improve feature extraction for quantitative pathology

    International Nuclear Information System (INIS)

    Tam, Allison; Barker, Jocelyn; Rubin, Daniel

    2016-01-01

    Purpose: With the advent of digital slide scanning technologies and the potential proliferation of large repositories of digital pathology images, many research studies can leverage these data for biomedical discovery and to develop clinical applications. However, quantitative analysis of digital pathology images is impeded by batch effects generated by varied staining protocols and staining conditions of pathological slides. Methods: To overcome this problem, this paper proposes a novel, fully automated stain normalization method to reduce batch effects and thus aid research in digital pathology applications. Their method, intensity centering and histogram equalization (ICHE), normalizes a diverse set of pathology images by first scaling the centroids of the intensity histograms to a common point and then applying a modified version of contrast-limited adaptive histogram equalization. Normalization was performed on two datasets of digitized hematoxylin and eosin (H&E) slides of different tissue slices from the same lung tumor, and one immunohistochemistry dataset of digitized slides created by restaining one of the H&E datasets. Results: The ICHE method was evaluated based on image intensity values, quantitative features, and the effect on downstream applications, such as a computer aided diagnosis. For comparison, three methods from the literature were reimplemented and evaluated using the same criteria. The authors found that ICHE not only improved performance compared with un-normalized images, but in most cases showed improvement compared with previous methods for correcting batch effects in the literature. Conclusions: ICHE may be a useful preprocessing step a digital pathology image processing pipeline

  17. A method for normalizing pathology images to improve feature extraction for quantitative pathology

    Energy Technology Data Exchange (ETDEWEB)

    Tam, Allison [Stanford Institutes of Medical Research Program, Stanford University School of Medicine, Stanford, California 94305 (United States); Barker, Jocelyn [Department of Radiology, Stanford University School of Medicine, Stanford, California 94305 (United States); Rubin, Daniel [Department of Radiology, Stanford University School of Medicine, Stanford, California 94305 and Department of Medicine (Biomedical Informatics Research), Stanford University School of Medicine, Stanford, California 94305 (United States)

    2016-01-15

    Purpose: With the advent of digital slide scanning technologies and the potential proliferation of large repositories of digital pathology images, many research studies can leverage these data for biomedical discovery and to develop clinical applications. However, quantitative analysis of digital pathology images is impeded by batch effects generated by varied staining protocols and staining conditions of pathological slides. Methods: To overcome this problem, this paper proposes a novel, fully automated stain normalization method to reduce batch effects and thus aid research in digital pathology applications. Their method, intensity centering and histogram equalization (ICHE), normalizes a diverse set of pathology images by first scaling the centroids of the intensity histograms to a common point and then applying a modified version of contrast-limited adaptive histogram equalization. Normalization was performed on two datasets of digitized hematoxylin and eosin (H&E) slides of different tissue slices from the same lung tumor, and one immunohistochemistry dataset of digitized slides created by restaining one of the H&E datasets. Results: The ICHE method was evaluated based on image intensity values, quantitative features, and the effect on downstream applications, such as a computer aided diagnosis. For comparison, three methods from the literature were reimplemented and evaluated using the same criteria. The authors found that ICHE not only improved performance compared with un-normalized images, but in most cases showed improvement compared with previous methods for correcting batch effects in the literature. Conclusions: ICHE may be a useful preprocessing step a digital pathology image processing pipeline.

  18. An Improved Image Contrast Assessment Method

    Directory of Open Access Journals (Sweden)

    Yuanyuan Fan

    2013-07-01

    Full Text Available Contrast is an important factor affecting the image quality. In order to overcome the problems of local band-limited contrast, a novel image contrast assessment method based on the property of HVS is proposed. Firstly, the image by low-pass filter is performed fast wavelet decomposition. Secondly, all levels of band-pass filtered image and its corresponding low-pass filtered image are obtained by processing wavelet coefficients. Thirdly, local band-limited contrast is calculated, and the local band-limited contrast entropy is calculated according to the definition of entropy, Finally, the contrast entropy of image is obtained by averaging the local band-limited contrast entropy weighed using CSF coefficient. The experiment results show that the best contrast image can be accurately identified in the sequence images obtained by adjusting the exposure time and stretching gray respectively, the assessment results accord with human visual characteristics and make up the lack of local band-limited contrast.

  19. An improved method to estimate reflectance parameters for high dynamic range imaging

    Science.gov (United States)

    Li, Shiying; Deguchi, Koichiro; Li, Renfa; Manabe, Yoshitsugu; Chihara, Kunihiro

    2008-01-01

    Two methods are described to accurately estimate diffuse and specular reflectance parameters for colors, gloss intensity and surface roughness, over the dynamic range of the camera used to capture input images. Neither method needs to segment color areas on an image, or to reconstruct a high dynamic range (HDR) image. The second method improves on the first, bypassing the requirement for specific separation of diffuse and specular reflection components. For the latter method, diffuse and specular reflectance parameters are estimated separately, using the least squares method. Reflection values are initially assumed to be diffuse-only reflection components, and are subjected to the least squares method to estimate diffuse reflectance parameters. Specular reflection components, obtained by subtracting the computed diffuse reflection components from reflection values, are then subjected to a logarithmically transformed equation of the Torrance-Sparrow reflection model, and specular reflectance parameters for gloss intensity and surface roughness are finally estimated using the least squares method. Experiments were carried out using both methods, with simulation data at different saturation levels, generated according to the Lambert and Torrance-Sparrow reflection models, and the second method, with spectral images captured by an imaging spectrograph and a moving light source. Our results show that the second method can estimate the diffuse and specular reflectance parameters for colors, gloss intensity and surface roughness more accurately and faster than the first one, so that colors and gloss can be reproduced more efficiently for HDR imaging.

  20. Sub-piexl methods for improving vector quality in echo PIV flow, imaging technology.

    Science.gov (United States)

    Niu, Lili; Wang, Jing; Qian, Ming; Zheng, Hairong

    2009-01-01

    Developments of many cardiovascular problems have been shown to have a close relationship with arterial flow conditions. An ultrasound-based particle image velocimetry technique(Echo PIV) was recently developed to measure multi-component velocity vectors and local shear rates in arteries and opaque fluid flows by identifying and tracking flow tracers (ultrasound contrast microbubbles) within these flow fields. To improve the measurement accuracy, sub-pixel calculation method was adopted in this paper to maximize the ultrasound RF signal and B mode image correlation accuracy and increase the image spatial resolution. This algorithm is employed in processing both computer-generated particle image patterns and the B-mode images of microbubbles in rotating flows obtained by a high frame rate (up to 1000 frames per second) ultrasound imaging system. The results show the correlation of particle patterns and individual flow vector quality are improved and the overall flow mappings are also improved significantly. This would help the Echo PIV system to provide better multi-component velocity accuracy.

  1. Terahertz composite imaging method

    Institute of Scientific and Technical Information of China (English)

    QIAO Xiaoli; REN Jiaojiao; ZHANG Dandan; CAO Guohua; LI Lijuan; ZHANG Xinming

    2017-01-01

    In order to improve the imaging quality of terahertz(THz) spectroscopy, Terahertz Composite Imaging Method(TCIM) is proposed. The traditional methods of improving THz spectroscopy image quality are mainly from the aspects of de-noising and image enhancement. TCIM breaks through this limitation. A set of images, reconstructed in a single data collection, can be utilized to construct two kinds of composite images. One algorithm, called Function Superposition Imaging Algorithm(FSIA), is to construct a new gray image utilizing multiple gray images through a certain function. The features of the Region Of Interest (ROI) are more obvious after operating, and it has capability of merging ROIs in multiple images. The other, called Multi-characteristics Pseudo-color Imaging Algorithm(McPcIA), is to construct a pseudo-color image by combining multiple reconstructed gray images in a single data collection. The features of ROI are enhanced by color differences. Two algorithms can not only improve the contrast of ROIs, but also increase the amount of information resulting in analysis convenience. The experimental results show that TCIM is a simple and effective tool for THz spectroscopy image analysis.

  2. MO-DE-207A-02: A Feature-Preserving Image Reconstruction Method for Improved Pancreaticlesion Classification in Diagnostic CT Imaging

    Energy Technology Data Exchange (ETDEWEB)

    Xu, J; Tsui, B [Johns Hopkins University, Baltimore, MD (United States); Noo, F [University of Utah, Salt Lake City, UT (United States)

    2016-06-15

    Purpose: To develop a feature-preserving model based image reconstruction (MBIR) method that improves performance in pancreatic lesion classification at equal or reduced radiation dose. Methods: A set of pancreatic lesion models was created with both benign and premalignant lesion types. These two classes of lesions are distinguished by their fine internal structures; their delineation is therefore crucial to the task of pancreatic lesion classification. To reduce image noise while preserving the features of the lesions, we developed a MBIR method with curvature-based regularization. The novel regularization encourages formation of smooth surfaces that model both the exterior shape and the internal features of pancreatic lesions. Given that the curvature depends on the unknown image, image reconstruction or denoising becomes a non-convex optimization problem; to address this issue an iterative-reweighting scheme was used to calculate and update the curvature using the image from the previous iteration. Evaluation was carried out with insertion of the lesion models into the pancreas of a patient CT image. Results: Visual inspection was used to compare conventional TV regularization with our curvature-based regularization. Several penalty-strengths were considered for TV regularization, all of which resulted in erasing portions of the septation (thin partition) in a premalignant lesion. At matched noise variance (50% noise reduction in the patient stomach region), the connectivity of the septation was well preserved using the proposed curvature-based method. Conclusion: The curvature-based regularization is able to reduce image noise while simultaneously preserving the lesion features. This method could potentially improve task performance for pancreatic lesion classification at equal or reduced radiation dose. The result is of high significance for longitudinal surveillance studies of patients with pancreatic cysts, which may develop into pancreatic cancer. The

  3. Improved GO/PO method and its application to wideband SAR image of conducting objects over rough surface

    Science.gov (United States)

    Jiang, Wang-Qiang; Zhang, Min; Nie, Ding; Jiao, Yong-Chang

    2018-04-01

    To simulate the multiple scattering effect of target in synthetic aperture radar (SAR) image, the hybrid method GO/PO method, which combines the geometrical optics (GO) and physical optics (PO), is employed to simulate the scattering field of target. For ray tracing is time-consuming, the Open Graphics Library (OpenGL) is usually employed to accelerate the process of ray tracing. Furthermore, the GO/PO method is improved for the simulation in low pixel situation. For the improved GO/PO method, the pixels are arranged corresponding to the rectangular wave beams one by one, and the GO/PO result is the sum of the contribution values of all the rectangular wave beams. To get high-resolution SAR image, the wideband echo signal is simulated which includes information of many electromagnetic (EM) waves with different frequencies. Finally, the improved GO/PO method is used to simulate the SAR image of targets above rough surface. And the effects of reflected rays and the size of pixel matrix on the SAR image are also discussed.

  4. Synthesis method from low-coherence digital holograms for improvement of image quality in holographic display.

    Science.gov (United States)

    Mori, Yutaka; Nomura, Takanori

    2013-06-01

    In holographic displays, it is undesirable to observe the speckle noises with the reconstructed images. A method for improvement of reconstructed image quality by synthesizing low-coherence digital holograms is proposed. It is possible to obtain speckleless reconstruction of holograms due to low-coherence digital holography. An image sensor records low-coherence digital holograms, and the holograms are synthesized by computational calculation. Two approaches, the threshold-processing and the picking-a-peak methods, are proposed in order to reduce random noise of low-coherence digital holograms. The reconstructed image quality by the proposed methods is compared with the case of high-coherence digital holography. Quantitative evaluation is given to confirm the proposed methods. In addition, the visual evaluation by 15 people is also shown.

  5. SU-E-I-93: Improved Imaging Quality for Multislice Helical CT Via Sparsity Regularized Iterative Image Reconstruction Method Based On Tensor Framelet

    International Nuclear Information System (INIS)

    Nam, H; Guo, M; Lee, K; Li, R; Xing, L; Gao, H

    2014-01-01

    Purpose: Inspired by compressive sensing, sparsity regularized iterative reconstruction method has been extensively studied. However, its utility pertinent to multislice helical 4D CT for radiotherapy with respect to imaging quality, dose, and time has not been thoroughly addressed. As the beginning of such an investigation, this work carries out the initial comparison of reconstructed imaging quality between sparsity regularized iterative method and analytic method through static phantom studies using a state-of-art 128-channel multi-slice Siemens helical CT scanner. Methods: In our iterative method, tensor framelet (TF) is chosen as the regularization method for its superior performance from total variation regularization in terms of reduced piecewise-constant artifacts and improved imaging quality that has been demonstrated in our prior work. On the other hand, X-ray transforms and its adjoints are computed on-the-fly through GPU implementation using our previous developed fast parallel algorithms with O(1) complexity per computing thread. For comparison, both FDK (approximate analytic method) and Katsevich algorithm (exact analytic method) are used for multislice helical CT image reconstruction. Results: The phantom experimental data with different imaging doses were acquired using a state-of-art 128-channel multi-slice Siemens helical CT scanner. The reconstructed image quality was compared between TF-based iterative method, FDK and Katsevich algorithm with the quantitative analysis for characterizing signal-to-noise ratio, image contrast, and spatial resolution of high-contrast and low-contrast objects. Conclusion: The experimental results suggest that our tensor framelet regularized iterative reconstruction algorithm improves the helical CT imaging quality from FDK and Katsevich algorithm for static experimental phantom studies that have been performed

  6. Improvement image in tomosynthesis

    International Nuclear Information System (INIS)

    Gomi, Tsutomu; Umeda, Tokuo; Takeda, Tohoru; Saito, Kyouko; Sakaguchi, Kazuya; Nakajima, Masahiro; Koshida, Kichirou

    2012-01-01

    We evaluated the X-ray digital tomosynthesis (DT) reconstruction processing method for metal artifact reduction and the application of wavelet denoising to selectively remove quantum noise and suggest the possibility of image quality improvement using a novel application for chest. In orthopedic DT imaging, we developed artifact reduction methods based on a modified Shepp and Logan reconstruction filter kernel realized by taking into account additional weighing by direct current (DC) components in frequency domain space. Processing leads to an increase in the ratio of low-frequency components in an image. The effectiveness of the method in enhancing the visibility of a prosthetic case was quantified in terms of removal of ghosting artifacts. In chest DT imaging, the technique was implemented on a DT system and experimentally evaluated through chest phantom measurements, spatial resolution and compared with an existing post-reconstruction wavelet denoise algorithm by Badea et al. Our wavelet technique with balance sparsity-norm contrast-to-noise ratio (CNR) effectively decreased quantum noise in the reconstructed images with and improvement when applied to pre-reconstruction image for post-reconstruction. The results of our technique showed that although modulation transfer function (MTF) did not vary (preserving spatial resolution), the existing wavelet denoise algorithm caused MTF deterioration. (author)

  7. Improved Ordinary Measure and Image Entropy Theory based intelligent Copy Detection Method

    Directory of Open Access Journals (Sweden)

    Dengpan Ye

    2011-10-01

    Full Text Available Nowadays, more and more multimedia websites appear in social network. It brings some security problems, such as privacy, piracy, disclosure of sensitive contents and so on. Aiming at copyright protection, the copy detection technology of multimedia contents becomes a hot topic. In our previous work, a new computer-based copyright control system used to detect the media has been proposed. Based on this system, this paper proposes an improved media feature matching measure and an entropy based copy detection method. The Levenshtein Distance was used to enhance the matching degree when using for feature matching measure in copy detection. For entropy based copy detection, we make a fusion of the two features of entropy matrix of the entropy feature we extracted. Firstly,we extract the entropy matrix of the image and normalize it. Then, we make a fusion of the eigenvalue feature and the transfer matrix feature of the entropy matrix. The fused features will be used for image copy detection. The experiments show that compared to use these two kinds of features for image detection singly, using feature fusion matching method is apparent robustness and effectiveness. The fused feature has a high detection for copy images which have been received some attacks such as noise, compression, zoom, rotation and so on. Comparing with referred methods, the method proposed is more intelligent and can be achieved good performance.

  8. An Improved Variational Method for Hyperspectral Image Pansharpening with the Constraint of Spectral Difference Minimization

    Science.gov (United States)

    Huang, Z.; Chen, Q.; Shen, Y.; Chen, Q.; Liu, X.

    2017-09-01

    Variational pansharpening can enhance the spatial resolution of a hyperspectral (HS) image using a high-resolution panchromatic (PAN) image. However, this technology may lead to spectral distortion that obviously affect the accuracy of data analysis. In this article, we propose an improved variational method for HS image pansharpening with the constraint of spectral difference minimization. We extend the energy function of the classic variational pansharpening method by adding a new spectral fidelity term. This fidelity term is designed following the definition of spectral angle mapper, which means that for every pixel, the spectral difference value of any two bands in the HS image is in equal proportion to that of the two corresponding bands in the pansharpened image. Gradient descent method is adopted to find the optimal solution of the modified energy function, and the pansharpened image can be reconstructed. Experimental results demonstrate that the constraint of spectral difference minimization is able to preserve the original spectral information well in HS images, and reduce the spectral distortion effectively. Compared to original variational method, our method performs better in both visual and quantitative evaluation, and achieves a good trade-off between spatial and spectral information.

  9. Fixed-pattern noise correction method based on improved moment matching for a TDI CMOS image sensor.

    Science.gov (United States)

    Xu, Jiangtao; Nie, Huafeng; Nie, Kaiming; Jin, Weimin

    2017-09-01

    In this paper, an improved moment matching method based on a spatial correlation filter (SCF) and bilateral filter (BF) is proposed to correct the fixed-pattern noise (FPN) of a time-delay-integration CMOS image sensor (TDI-CIS). First, the values of row FPN (RFPN) and column FPN (CFPN) are estimated and added to the original image through SCF and BF, respectively. Then the filtered image will be processed by an improved moment matching method with a moving window. Experimental results based on a 128-stage TDI-CIS show that, after correcting the FPN in the image captured under uniform illumination, the standard deviation of row mean vector (SDRMV) decreases from 5.6761 LSB to 0.1948 LSB, while the standard deviation of the column mean vector (SDCMV) decreases from 15.2005 LSB to 13.1949LSB. In addition, for different images captured by different TDI-CISs, the average decrease of SDRMV and SDCMV is 5.4922/2.0357 LSB, respectively. Comparative experimental results indicate that the proposed method can effectively correct the FPNs of different TDI-CISs while maintaining image details without any auxiliary equipment.

  10. Comparative study of protoporphyrin IX fluorescence image enhancement methods to improve an optical imaging system for oral cancer detection

    Science.gov (United States)

    Jiang, Ching-Fen; Wang, Chih-Yu; Chiang, Chun-Ping

    2011-07-01

    Optoelectronics techniques to induce protoporphyrin IX fluorescence with topically applied 5-aminolevulinic acid on the oral mucosa have been developed to noninvasively detect oral cancer. Fluorescence imaging enables wide-area screening for oral premalignancy, but the lack of an adequate fluorescence enhancement method restricts the clinical imaging application of these techniques. This study aimed to develop a reliable fluorescence enhancement method to improve PpIX fluorescence imaging systems for oral cancer detection. Three contrast features, red-green-blue reflectance difference, R/B ratio, and R/G ratio, were developed first based on the optical properties of the fluorescence images. A comparative study was then carried out with one negative control and four biopsy confirmed clinical cases to validate the optimal image processing method for the detection of the distribution of malignancy. The results showed the superiority of the R/G ratio in terms of yielding a better contrast between normal and neoplastic tissue, and this method was less prone to errors in detection. Quantitative comparison with the clinical diagnoses in the four neoplastic cases showed that the regions of premalignancy obtained using the proposed method accorded with the expert's determination, suggesting the potential clinical application of this method for the detection of oral cancer.

  11. Methods for improving limited field-of-view radiotherapy reconstructions using imperfect a priori images

    International Nuclear Information System (INIS)

    Ruchala, Kenneth J.; Olivera, Gustavo H.; Kapatoes, Jeffrey M.; Reckwerdt, Paul J.; Mackie, Thomas R.

    2002-01-01

    There are many benefits to having an online CT imaging system for radiotherapy, as it helps identify changes in the patient's position and anatomy between the time of planning and treatment. However, many current online CT systems suffer from a limited field-of-view (LFOV) in that collected data do not encompass the patient's complete cross section. Reconstruction of these data sets can quantitatively distort the image values and introduce artifacts. This work explores the use of planning CT data as a priori information for improving these reconstructions. Methods are presented to incorporate this data by aligning the LFOV with the planning images and then merging the data sets in sinogram space. One alignment option is explicit fusion, producing fusion-aligned reprojection (FAR) images. For cases where explicit fusion is not viable, FAR can be implemented using the implicit fusion of normal setup error, referred to as normal-error-aligned reprojection (NEAR). These methods are evaluated for multiday patient images showing both internal and skin-surface anatomical variation. The iterative use of NEAR and FAR is also investigated, as are applications of NEAR and FAR to dose calculations and the compensation of LFOV online MVCT images with kVCT planning images. Results indicate that NEAR and FAR can utilize planning CT data as imperfect a priori information to reduce artifacts and quantitatively improve images. These benefits can also increase the accuracy of dose calculations and be used for augmenting CT images (e.g., MVCT) acquired at different energies than the planning CT

  12. Research on Adaptive Optics Image Restoration Algorithm by Improved Expectation Maximization Method

    Directory of Open Access Journals (Sweden)

    Lijuan Zhang

    2014-01-01

    Full Text Available To improve the effect of adaptive optics images’ restoration, we put forward a deconvolution algorithm improved by the EM algorithm which joints multiframe adaptive optics images based on expectation-maximization theory. Firstly, we need to make a mathematical model for the degenerate multiframe adaptive optics images. The function model is deduced for the points that spread with time based on phase error. The AO images are denoised using the image power spectral density and support constraint. Secondly, the EM algorithm is improved by combining the AO imaging system parameters and regularization technique. A cost function for the joint-deconvolution multiframe AO images is given, and the optimization model for their parameter estimations is built. Lastly, the image-restoration experiments on both analog images and the real AO are performed to verify the recovery effect of our algorithm. The experimental results show that comparing with the Wiener-IBD or RL-IBD algorithm, our iterations decrease 14.3% and well improve the estimation accuracy. The model distinguishes the PSF of the AO images and recovers the observed target images clearly.

  13. A model-based radiography restoration method based on simple scatter-degradation scheme for improving image visibility

    Science.gov (United States)

    Kim, K.; Kang, S.; Cho, H.; Kang, W.; Seo, C.; Park, C.; Lee, D.; Lim, H.; Lee, H.; Kim, G.; Park, S.; Park, J.; Kim, W.; Jeon, D.; Woo, T.; Oh, J.

    2018-02-01

    In conventional planar radiography, image visibility is often limited mainly due to the superimposition of the object structure under investigation and the artifacts caused by scattered x-rays and noise. Several methods, including computed tomography (CT) as a multiplanar imaging modality, air-gap and grid techniques for the reduction of scatters, phase-contrast imaging as another image-contrast modality, etc., have extensively been investigated in attempt to overcome these difficulties. However, those methods typically require higher x-ray doses or special equipment. In this work, as another approach, we propose a new model-based radiography restoration method based on simple scatter-degradation scheme where the intensity of scattered x-rays and the transmission function of a given object are estimated from a single x-ray image to restore the original degraded image. We implemented the proposed algorithm and performed an experiment to demonstrate its viability. Our results indicate that the degradation of image characteristics by scattered x-rays and noise was effectively recovered by using the proposed method, which improves the image visibility in radiography considerably.

  14. Quality Improvement of Liver Ultrasound Images Using Fuzzy Techniques.

    Science.gov (United States)

    Bayani, Azadeh; Langarizadeh, Mostafa; Radmard, Amir Reza; Nejad, Ahmadreza Farzaneh

    2016-12-01

    Liver ultrasound images are so common and are applied so often to diagnose diffuse liver diseases like fatty liver. However, the low quality of such images makes it difficult to analyze them and diagnose diseases. The purpose of this study, therefore, is to improve the contrast and quality of liver ultrasound images. In this study, a number of image contrast enhancement algorithms which are based on fuzzy logic were applied to liver ultrasound images - in which the view of kidney is observable - using Matlab2013b to improve the image contrast and quality which has a fuzzy definition; just like image contrast improvement algorithms using a fuzzy intensification operator, contrast improvement algorithms applying fuzzy image histogram hyperbolization, and contrast improvement algorithms by fuzzy IF-THEN rules. With the measurement of Mean Squared Error and Peak Signal to Noise Ratio obtained from different images, fuzzy methods provided better results, and their implementation - compared with histogram equalization method - led both to the improvement of contrast and visual quality of images and to the improvement of liver segmentation algorithms results in images. Comparison of the four algorithms revealed the power of fuzzy logic in improving image contrast compared with traditional image processing algorithms. Moreover, contrast improvement algorithm based on a fuzzy intensification operator was selected as the strongest algorithm considering the measured indicators. This method can also be used in future studies on other ultrasound images for quality improvement and other image processing and analysis applications.

  15. An improved method for polarimetric image restoration in interferometry

    Science.gov (United States)

    Pratley, Luke; Johnston-Hollitt, Melanie

    2016-11-01

    Interferometric radio astronomy data require the effects of limited coverage in the Fourier plane to be accounted for via a deconvolution process. For the last 40 years this process, known as `cleaning', has been performed almost exclusively on all Stokes parameters individually as if they were independent scalar images. However, here we demonstrate for the case of the linear polarization P, this approach fails to properly account for the complex vector nature resulting in a process which is dependent on the axes under which the deconvolution is performed. We present here an improved method, `Generalized Complex CLEAN', which properly accounts for the complex vector nature of polarized emission and is invariant under rotations of the deconvolution axes. We use two Australia Telescope Compact Array data sets to test standard and complex CLEAN versions of the Högbom and SDI (Steer-Dwedney-Ito) CLEAN algorithms. We show that in general the complex CLEAN version of each algorithm produces more accurate clean components with fewer spurious detections and lower computation cost due to reduced iterations than the current methods. In particular, we find that the complex SDI CLEAN produces the best results for diffuse polarized sources as compared with standard CLEAN algorithms and other complex CLEAN algorithms. Given the move to wide-field, high-resolution polarimetric imaging with future telescopes such as the Square Kilometre Array, we suggest that Generalized Complex CLEAN should be adopted as the deconvolution method for all future polarimetric surveys and in particular that the complex version of an SDI CLEAN should be used.

  16. Spectrally Consistent Satellite Image Fusion with Improved Image Priors

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Aanæs, Henrik; Jensen, Thomas B.S.

    2006-01-01

    Here an improvement to our previous framework for satellite image fusion is presented. A framework purely based on the sensor physics and on prior assumptions on the fused image. The contributions of this paper are two fold. Firstly, a method for ensuring 100% spectrally consistency is proposed......, even when more sophisticated image priors are applied. Secondly, a better image prior is introduced, via data-dependent image smoothing....

  17. Color quality improvement of reconstructed images in color digital holography using speckle method and spectral estimation

    Science.gov (United States)

    Funamizu, Hideki; Onodera, Yusei; Aizu, Yoshihisa

    2018-05-01

    In this study, we report color quality improvement of reconstructed images in color digital holography using the speckle method and the spectral estimation. In this technique, an object is illuminated by a speckle field and then an object wave is produced, while a plane wave is used as a reference wave. For three wavelengths, the interference patterns of two coherent waves are recorded as digital holograms on an image sensor. Speckle fields are changed by moving a ground glass plate in an in-plane direction, and a number of holograms are acquired to average the reconstructed images. After the averaging process of images reconstructed from multiple holograms, we use the Wiener estimation method for obtaining spectral transmittance curves in reconstructed images. The color reproducibility in this method is demonstrated and evaluated using a Macbeth color chart film and staining cells of onion.

  18. Novel driver method to improve ordinary CCD frame rate for high-speed imaging diagnosis

    Energy Technology Data Exchange (ETDEWEB)

    Luo, Tong-Ding, E-mail: snuohui@126.com; Li, Bin-Kang; Yang, Shao-Hua; Guo, Ming-An; Yan, Ming

    2016-06-21

    The use of ordinary Charge-coupled-Device (CCD) imagers for the analysis of fast physical phenomenon is restricted because of the low-speed performance resulting from their long output times. Even though the form of Intensified-CCD (ICCD), coupled with a gated image intensifier, has extended their use for high speed imaging, the deficiency remains to be solved that ICDD could record only one image in a single shot. This paper presents a novel driver method designed to significantly improve the ordinary interline CCD burst frame rate for high-speed photography. This method is based on the use of vertical registers as storage, so that a small number of additional frames comprised of reduced-spatial-resolution images obtained via a specific sampling operation can be buffered. Hence, the interval time of the received series of images is related to the exposure and vertical transfer times only and, thus, the burst frame rate can be increased significantly. A prototype camera based on this method is designed as part of this study, exhibiting a burst rate of up to 250,000 frames per second (fps) and a capacity to record three continuous images. This device exhibits a speed enhancement of approximately 16,000 times compared with the conventional speed, with a spatial resolution reduction of only 1/4.

  19. Research on Adaptive Optics Image Restoration Algorithm by Improved Expectation Maximization Method

    OpenAIRE

    Zhang, Lijuan; Li, Dongming; Su, Wei; Yang, Jinhua; Jiang, Yutong

    2014-01-01

    To improve the effect of adaptive optics images’ restoration, we put forward a deconvolution algorithm improved by the EM algorithm which joints multiframe adaptive optics images based on expectation-maximization theory. Firstly, we need to make a mathematical model for the degenerate multiframe adaptive optics images. The function model is deduced for the points that spread with time based on phase error. The AO images are denoised using the image power spectral density and support constrain...

  20. An improved image non-blind image deblurring method based on FoEs

    Science.gov (United States)

    Zhu, Qidan; Sun, Lei

    2013-03-01

    Traditional non-blind image deblurring algorithms always use maximum a posterior(MAP). MAP estimates involving natural image priors can reduce the ripples effectively in contrast to maximum likelihood(ML). However, they have been found lacking in terms of restoration performance. Based on this issue, we utilize MAP with KL penalty to replace traditional MAP. We develop an image reconstruction algorithm that minimizes the KL divergence between the reference distribution and the prior distribution. The approximate KL penalty can restrain over-smooth caused by MAP. We use three groups of images and Harris corner detection to prove our method. The experimental results show that our algorithm of non-blind image restoration can effectively reduce the ringing effect and exhibit the state-of-the-art deblurring results.

  1. Improving Hyperspectral Image Classification Method for Fine Land Use Assessment Application Using Semisupervised Machine Learning

    Directory of Open Access Journals (Sweden)

    Chunyang Wang

    2015-01-01

    Full Text Available Study on land use/cover can reflect changing rules of population, economy, agricultural structure adjustment, policy, and traffic and provide better service for the regional economic development and urban evolution. The study on fine land use/cover assessment using hyperspectral image classification is a focal growing area in many fields. Semisupervised learning method which takes a large number of unlabeled samples and minority labeled samples, improving classification and predicting the accuracy effectively, has been a new research direction. In this paper, we proposed improving fine land use/cover assessment based on semisupervised hyperspectral classification method. The test analysis of study area showed that the advantages of semisupervised classification method could improve the high precision overall classification and objective assessment of land use/cover results.

  2. HDR Pathological Image Enhancement Based on Improved Bias Field Correction and Guided Image Filter

    Directory of Open Access Journals (Sweden)

    Qingjiao Sun

    2016-01-01

    Full Text Available Pathological image enhancement is a significant topic in the field of pathological image processing. This paper proposes a high dynamic range (HDR pathological image enhancement method based on improved bias field correction and guided image filter (GIF. Firstly, a preprocessing including stain normalization and wavelet denoising is performed for Haematoxylin and Eosin (H and E stained pathological image. Then, an improved bias field correction model is developed to enhance the influence of light for high-frequency part in image and correct the intensity inhomogeneity and detail discontinuity of image. Next, HDR pathological image is generated based on least square method using low dynamic range (LDR image, H and E channel images. Finally, the fine enhanced image is acquired after the detail enhancement process. Experiments with 140 pathological images demonstrate the performance advantages of our proposed method as compared with related work.

  3. Dual-energy imaging method to improve the image quality and the accuracy of dose calculation for cone-beam computed tomography.

    Science.gov (United States)

    Men, Kuo; Dai, Jianrong; Chen, Xinyuan; Li, Minghui; Zhang, Ke; Huang, Peng

    2017-04-01

    To improve the image quality and accuracy of dose calculation for cone-beam computed tomography (CT) images through implementation of a dual-energy cone-beam computed tomography method (DE-CBCT), and evaluate the improvement quantitatively. Two sets of CBCT projections were acquired using the X-ray volumetric imaging (XVI) system on a Synergy (Elekta, Stockholm, Sweden) system with 120kV (high) and 70kV (low) X-rays, respectively. Then, the electron density relative to water (relative electron density (RED)) of each voxel was calculated using a projection-based dual-energy decomposition method. As a comparison, single-energy cone-beam computed tomography (SE-CBCT) was used to calculate RED with the Hounsfield unit-RED calibration curve generated by a CIRS phantom scan with identical imaging parameters. The imaging dose was measured with a dosimetry phantom. The image quality was evaluated quantitatively using a Catphan 503 phantom with the evaluation indices of the reproducibility of the RED values, high-contrast resolution (MTF 50% ), uniformity, and signal-to-noise ratio (SNR). Dose calculation of two simulated volumetric-modulated arc therapy plans using an Eclipse treatment-planning system (Varian Medical Systems, Palo Alto, CA, USA) was performed on an Alderson Rando Head and Neck (H&N) phantom and a Pelvis phantom. Fan-beam planning CT images for the H&N and Pelvis phantom were set as the reference. A global three-dimensional gamma analysis was used to compare dose distributions with the reference. The average gamma values for targets and OAR were analyzed with paired t-tests between DE-CBCT and SE-CBCT. In two scans (H&N scan and body scan), the imaging dose of DE-CBCT increased by 1.0% and decreased by 1.3%. It had a better reproducibility of the RED values (mean bias: 0.03 and 0.07) compared with SE-CBCT (mean bias: 0.13 and 0.16). It also improved the image uniformity (57.5% and 30.1%) and SNR (9.7% and 2.3%), but did not affect the MTF 50% . Gamma

  4. Comparative analysis of different methods for image enhancement

    Institute of Scientific and Technical Information of China (English)

    吴笑峰; 胡仕刚; 赵瑾; 李志明; 李劲; 唐志军; 席在芳

    2014-01-01

    Image enhancement technology plays a very important role to improve image quality in image processing. By enhancing some information and restraining other information selectively, it can improve image visual effect. The objective of this work is to implement the image enhancement to gray scale images using different techniques. After the fundamental methods of image enhancement processing are demonstrated, image enhancement algorithms based on space and frequency domains are systematically investigated and compared. The advantage and defect of the above-mentioned algorithms are analyzed. The algorithms of wavelet based image enhancement are also deduced and generalized. Wavelet transform modulus maxima (WTMM) is a method for detecting the fractal dimension of a signal, it is well used for image enhancement. The image techniques are compared by using the mean (μ), standard deviation (s), mean square error (MSE) and PSNR (peak signal to noise ratio). A group of experimental results demonstrate that the image enhancement algorithm based on wavelet transform is effective for image de-noising and enhancement. Wavelet transform modulus maxima method is one of the best methods for image enhancement.

  5. Human body region enhancement method based on Kinect infrared imaging

    Science.gov (United States)

    Yang, Lei; Fan, Yubo; Song, Xiaowei; Cai, Wenjing

    2016-10-01

    To effectively improve the low contrast of human body region in the infrared images, a combing method of several enhancement methods is utilized to enhance the human body region. Firstly, for the infrared images acquired by Kinect, in order to improve the overall contrast of the infrared images, an Optimal Contrast-Tone Mapping (OCTM) method with multi-iterations is applied to balance the contrast of low-luminosity infrared images. Secondly, to enhance the human body region better, a Level Set algorithm is employed to improve the contour edges of human body region. Finally, to further improve the human body region in infrared images, Laplacian Pyramid decomposition is adopted to enhance the contour-improved human body region. Meanwhile, the background area without human body region is processed by bilateral filtering to improve the overall effect. With theoretical analysis and experimental verification, the results show that the proposed method could effectively enhance the human body region of such infrared images.

  6. [An improved low spectral distortion PCA fusion method].

    Science.gov (United States)

    Peng, Shi; Zhang, Ai-Wu; Li, Han-Lun; Hu, Shao-Xing; Meng, Xian-Gang; Sun, Wei-Dong

    2013-10-01

    Aiming at the spectral distortion produced in PCA fusion process, the present paper proposes an improved low spectral distortion PCA fusion method. This method uses NCUT (normalized cut) image segmentation algorithm to make a complex hyperspectral remote sensing image into multiple sub-images for increasing the separability of samples, which can weaken the spectral distortions of traditional PCA fusion; Pixels similarity weighting matrix and masks were produced by using graph theory and clustering theory. These masks are used to cut the hyperspectral image and high-resolution image into some sub-region objects. All corresponding sub-region objects between the hyperspectral image and high-resolution image are fused by using PCA method, and all sub-regional integration results are spliced together to produce a new image. In the experiment, Hyperion hyperspectral data and Rapid Eye data were used. And the experiment result shows that the proposed method has the same ability to enhance spatial resolution and greater ability to improve spectral fidelity performance.

  7. Development and improvement of synthetic imaging methods for non-destructive ultrasonic testing of complex industrial components

    International Nuclear Information System (INIS)

    Bannouf, S.

    2013-01-01

    The goal of this thesis was, initially, to evaluate phased array methods for ultrasonic Non Destructive Testing (NDT) in order to propose optimizations, or to develop new alternative methods. In particular, this works deals with the detection of defects in complex geometries and/or materials parts. The TFM (Total Focusing Method) algorithm provides high resolution images and several representations of a same defect thanks to different reconstruction modes. These properties have been exploited judiciously in order to propose an adaptive imaging method in immersion configuration. We showed that TFM imaging can be used to characterize more precisely the defects. However, this method presents two major drawbacks: the large amount of data to be processed and a low signal-to-noise ratio (SNR), especially in noisy materials. We developed solutions to these two problems. To overcome the limitation caused by the large number of signals to be processed, we propose an algorithm that defines the sparse array to activate. As for the low SNR, it can be now improved by use of virtual sources and a new filtering method based on the DORT method (Decomposition of the Time Reversal Operator). (author) [fr

  8. Methods of digital image processing

    International Nuclear Information System (INIS)

    Doeler, W.

    1985-01-01

    Increasing use of computerized methods for diagnostical imaging of radiological problems will open up a wide field of applications for digital image processing. The requirements set by routine diagnostics in medical radiology point to picture data storage and documentation and communication as the main points of interest for application of digital image processing. As to the purely radiological problems, the value of digital image processing is to be sought in the improved interpretability of the image information in those cases where the expert's experience and image interpretation by human visual capacities do not suffice. There are many other domains of imaging in medical physics where digital image processing and evaluation is very useful. The paper reviews the various methods available for a variety of problem solutions, and explains the hardware available for the tasks discussed. (orig.) [de

  9. Dynamic PET Image reconstruction for parametric imaging using the HYPR kernel method

    Science.gov (United States)

    Spencer, Benjamin; Qi, Jinyi; Badawi, Ramsey D.; Wang, Guobao

    2017-03-01

    Dynamic PET image reconstruction is a challenging problem because of the ill-conditioned nature of PET and the lowcounting statistics resulted from short time-frames in dynamic imaging. The kernel method for image reconstruction has been developed to improve image reconstruction of low-count PET data by incorporating prior information derived from high-count composite data. In contrast to most of the existing regularization-based methods, the kernel method embeds image prior information in the forward projection model and does not require an explicit regularization term in the reconstruction formula. Inspired by the existing highly constrained back-projection (HYPR) algorithm for dynamic PET image denoising, we propose in this work a new type of kernel that is simpler to implement and further improves the kernel-based dynamic PET image reconstruction. Our evaluation study using a physical phantom scan with synthetic FDG tracer kinetics has demonstrated that the new HYPR kernel-based reconstruction can achieve a better region-of-interest (ROI) bias versus standard deviation trade-off for dynamic PET parametric imaging than the post-reconstruction HYPR denoising method and the previously used nonlocal-means kernel.

  10. [Multimodal medical image registration using cubic spline interpolation method].

    Science.gov (United States)

    He, Yuanlie; Tian, Lianfang; Chen, Ping; Wang, Lifei; Ye, Guangchun; Mao, Zongyuan

    2007-12-01

    Based on the characteristic of the PET-CT multimodal image series, a novel image registration and fusion method is proposed, in which the cubic spline interpolation method is applied to realize the interpolation of PET-CT image series, then registration is carried out by using mutual information algorithm and finally the improved principal component analysis method is used for the fusion of PET-CT multimodal images to enhance the visual effect of PET image, thus satisfied registration and fusion results are obtained. The cubic spline interpolation method is used for reconstruction to restore the missed information between image slices, which can compensate for the shortage of previous registration methods, improve the accuracy of the registration, and make the fused multimodal images more similar to the real image. Finally, the cubic spline interpolation method has been successfully applied in developing 3D-CRT (3D Conformal Radiation Therapy) system.

  11. An Improved InSAR Image Co-Registration Method for Pairs with Relatively Big Distortions or Large Incoherent Areas

    Directory of Open Access Journals (Sweden)

    Zhenwei Chen

    2016-09-01

    Full Text Available Co-registration is one of the most important steps in interferometric synthetic aperture radar (InSAR data processing. The standard offset-measurement method based on cross-correlating uniformly distributed patches takes no account of specific geometric transformation between images or characteristics of ground scatterers. Hence, it is inefficient and difficult to obtain satisfying co-registration results for image pairs with relatively big distortion or large incoherent areas. Given this, an improved co-registration strategy is proposed in this paper which takes both the geometric features and image content into consideration. Firstly, some geometric transformations including scale, flip, rotation, and shear between images were eliminated based on the geometrical information, and the initial co-registration polynomial was obtained. Then the registration points were automatically detected by integrating the signal-to-clutter-ratio (SCR thresholds and the amplitude information, and a further co-registration process was performed to refine the polynomial. Several comparison experiments were carried out using 2 TerraSAR-X data from the Hong Kong airport and 21 PALSAR data from the Donghai Bridge. Experiment results demonstrate that the proposed method brings accuracy and efficiency improvements for co-registration and processing abilities in the cases of big distortion between images or large incoherent areas in the images. For most co-registrations, the proposed method can enhance the reliability and applicability of co-registration and thus promote the automation to a higher level.

  12. An Improved InSAR Image Co-Registration Method for Pairs with Relatively Big Distortions or Large Incoherent Areas.

    Science.gov (United States)

    Chen, Zhenwei; Zhang, Lei; Zhang, Guo

    2016-09-17

    Co-registration is one of the most important steps in interferometric synthetic aperture radar (InSAR) data processing. The standard offset-measurement method based on cross-correlating uniformly distributed patches takes no account of specific geometric transformation between images or characteristics of ground scatterers. Hence, it is inefficient and difficult to obtain satisfying co-registration results for image pairs with relatively big distortion or large incoherent areas. Given this, an improved co-registration strategy is proposed in this paper which takes both the geometric features and image content into consideration. Firstly, some geometric transformations including scale, flip, rotation, and shear between images were eliminated based on the geometrical information, and the initial co-registration polynomial was obtained. Then the registration points were automatically detected by integrating the signal-to-clutter-ratio (SCR) thresholds and the amplitude information, and a further co-registration process was performed to refine the polynomial. Several comparison experiments were carried out using 2 TerraSAR-X data from the Hong Kong airport and 21 PALSAR data from the Donghai Bridge. Experiment results demonstrate that the proposed method brings accuracy and efficiency improvements for co-registration and processing abilities in the cases of big distortion between images or large incoherent areas in the images. For most co-registrations, the proposed method can enhance the reliability and applicability of co-registration and thus promote the automation to a higher level.

  13. New mobile methods for dietary assessment: review of image-assisted and image-based dietary assessment methods.

    Science.gov (United States)

    Boushey, C J; Spoden, M; Zhu, F M; Delp, E J; Kerr, D A

    2017-08-01

    For nutrition practitioners and researchers, assessing dietary intake of children and adults with a high level of accuracy continues to be a challenge. Developments in mobile technologies have created a role for images in the assessment of dietary intake. The objective of this review was to examine peer-reviewed published papers covering development, evaluation and/or validation of image-assisted or image-based dietary assessment methods from December 2013 to January 2016. Images taken with handheld devices or wearable cameras have been used to assist traditional dietary assessment methods for portion size estimations made by dietitians (image-assisted methods). Image-assisted approaches can supplement either dietary records or 24-h dietary recalls. In recent years, image-based approaches integrating application technology for mobile devices have been developed (image-based methods). Image-based approaches aim at capturing all eating occasions by images as the primary record of dietary intake, and therefore follow the methodology of food records. The present paper reviews several image-assisted and image-based methods, their benefits and challenges; followed by details on an image-based mobile food record. Mobile technology offers a wide range of feasible options for dietary assessment, which are easier to incorporate into daily routines. The presented studies illustrate that image-assisted methods can improve the accuracy of conventional dietary assessment methods by adding eating occasion detail via pictures captured by an individual (dynamic images). All of the studies reduced underreporting with the help of images compared with results with traditional assessment methods. Studies with larger sample sizes are needed to better delineate attributes with regards to age of user, degree of error and cost.

  14. Improving image quality in portal venography with spectral CT imaging

    International Nuclear Information System (INIS)

    Zhao, Li-qin; He, Wen; Li, Jian-ying; Chen, Jiang-hong; Wang, Ke-yang; Tan, Li

    2012-01-01

    Objective: To investigate the effect of energy spectral CT on the image quality of CT portal venography in cirrhosis patients. Materials and methods: 30 portal hypertension patients underwent spectral CT examination using a single-tube, fast dual tube voltage switching technique. 101 sets of monochromatic images were generated from 40 keV to 140 keV. Image noise and contrast-to-noise ratio (CNR) for portal veins from the monochromatic images were measured. An optimal monochromatic image set was selected for obtaining the best CNR for portal veins. The image noise and CNR of the intra-hepatic portal vein and extra-hepatic main stem at the selected monochromatic level were compared with those from the conventional polychromatic images. Image quality was also assessed and compared. Results: The monochromatic images at 51 keV were found to provide the best CNR for both the intra-hepatic and extra-hepatic portal veins. At this energy level, the monochromatic images had about 100% higher CNR than the polychromatic images with a moderate 30% noise increase. The qualitative image quality assessment was also statistically higher with monochromatic images at 51 keV. Conclusion: Monochromatic images at 51 keV for CT portal venography could improve CNR for displaying hepatic portal veins and improve the overall image quality.

  15. Improving image quality in portal venography with spectral CT imaging

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, Li-qin, E-mail: zhaolqzr@sohu.com [Department of Radiology, Beijing Friendship Hospital Affiliated to Capital Medical University, Beijing,100050 (China); He, Wen, E-mail: hewen1724@sina.com [Department of Radiology, Beijing Friendship Hospital Affiliated to Capital Medical University, Beijing,100050 (China); Li, Jian-ying, E-mail: jianying.li@med.ge.com [CT Advanced Application and Research, GE Healthcare, 100176 China (China); Chen, Jiang-hong, E-mail: chenjianghong1973@hotmail.com [Department of Radiology, Beijing Friendship Hospital Affiliated to Capital Medical University, Beijing,100050 (China); Wang, Ke-yang, E-mail: ke7ke@sina.com [Department of Radiology, Beijing Friendship Hospital Affiliated to Capital Medical University, Beijing,100050 (China); Tan, Li, E-mail: Litan@ge.com [CT product, GE Healthcare, 100176 China (China)

    2012-08-15

    Objective: To investigate the effect of energy spectral CT on the image quality of CT portal venography in cirrhosis patients. Materials and methods: 30 portal hypertension patients underwent spectral CT examination using a single-tube, fast dual tube voltage switching technique. 101 sets of monochromatic images were generated from 40 keV to 140 keV. Image noise and contrast-to-noise ratio (CNR) for portal veins from the monochromatic images were measured. An optimal monochromatic image set was selected for obtaining the best CNR for portal veins. The image noise and CNR of the intra-hepatic portal vein and extra-hepatic main stem at the selected monochromatic level were compared with those from the conventional polychromatic images. Image quality was also assessed and compared. Results: The monochromatic images at 51 keV were found to provide the best CNR for both the intra-hepatic and extra-hepatic portal veins. At this energy level, the monochromatic images had about 100% higher CNR than the polychromatic images with a moderate 30% noise increase. The qualitative image quality assessment was also statistically higher with monochromatic images at 51 keV. Conclusion: Monochromatic images at 51 keV for CT portal venography could improve CNR for displaying hepatic portal veins and improve the overall image quality.

  16. An Improved Filtering Method for Quantum Color Image in Frequency Domain

    Science.gov (United States)

    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.

  17. Analysis of Non Local Image Denoising Methods

    Science.gov (United States)

    Pardo, Álvaro

    Image denoising is probably one of the most studied problems in the image processing community. Recently a new paradigm on non local denoising was introduced. The Non Local Means method proposed by Buades, Morel and Coll attracted the attention of other researches who proposed improvements and modifications to their proposal. In this work we analyze those methods trying to understand their properties while connecting them to segmentation based on spectral graph properties. We also propose some improvements to automatically estimate the parameters used on these methods.

  18. Color image definition evaluation method based on deep learning method

    Science.gov (United States)

    Liu, Di; Li, YingChun

    2018-01-01

    In order to evaluate different blurring levels of color image and improve the method of image definition evaluation, this paper proposed a method based on the depth learning framework and BP neural network classification model, and presents a non-reference color image clarity evaluation method. Firstly, using VGG16 net as the feature extractor to extract 4,096 dimensions features of the images, then the extracted features and labeled images are employed in BP neural network to train. And finally achieve the color image definition evaluation. The method in this paper are experimented by using images from the CSIQ database. The images are blurred at different levels. There are 4,000 images after the processing. Dividing the 4,000 images into three categories, each category represents a blur level. 300 out of 400 high-dimensional features are trained in VGG16 net and BP neural network, and the rest of 100 samples are tested. The experimental results show that the method can take full advantage of the learning and characterization capability of deep learning. Referring to the current shortcomings of the major existing image clarity evaluation methods, which manually design and extract features. The method in this paper can extract the images features automatically, and has got excellent image quality classification accuracy for the test data set. The accuracy rate is 96%. Moreover, the predicted quality levels of original color images are similar to the perception of the human visual system.

  19. Fast method of constructing image correlations to build a free network based on image multivocabulary trees

    Science.gov (United States)

    Zhan, Zongqian; Wang, Xin; Wei, Minglu

    2015-05-01

    In image-based three-dimensional (3-D) reconstruction, one topic of growing importance is how to quickly obtain a 3-D model from a large number of images. The retrieval of the correct and relevant images for the model poses a considerable technological challenge. The "image vocabulary tree" has been proposed as a method to search for similar images. However, a significant drawback of this approach is identified in its low time efficiency and barely satisfactory classification result. The method proposed is inspired by, and improves upon, some recent methods. Specifically, vocabulary quality is considered and multivocabulary trees are designed to improve the classification result. A marked improvement was, indeed, observed in our evaluation of the proposed method. To improve time efficiency, graphics processing unit (GPU) computer unified device architecture parallel computation is applied in the multivocabulary trees. The results of the experiments showed that the GPU was three to four times more efficient than the enumeration matching and CPU methods when the number of images is large. This paper presents a reliable reference method for the rapid construction of a free network to be used for the computing of 3-D information.

  20. A Method for Improving the Progressive Image Coding Algorithms

    Directory of Open Access Journals (Sweden)

    Ovidiu COSMA

    2014-12-01

    Full Text Available This article presents a method for increasing the performance of the progressive coding algorithms for the subbands of images, by representing the coefficients with a code that reduces the truncation error.

  1. Improved CT imaging in diagnosis of ankylosing spondylitis

    International Nuclear Information System (INIS)

    Mai Yuanfeng; Sun Haixing; Ling Jian; Kuang Jianyi; Pan Ximin

    2006-01-01

    Objective: To evaluate the improved CT imaging of sacroiliac joint in diagnosis of ankylosing spondylitis (AS). Methods: 22 patients, diagnosed as AS by clinical and radiography, undertook both conventional and improved CT imaging. All images were comparatively studied. Results: With conventional CT imaging, in the 44 joints of 22 cases, unremarkable images were obtained in 3 cases; early stage AS was found in 15 joints of 9 cases; AS in progressive stage was revealed in 8 cases/16 joints, stabled AS was presented in 2 cases/4 joints. There were 23 joints in 12 cases diagnosed as early term by improved imaging, progressive staged AS was shown in 8 cases/16 joints as, stable AS was demonstrated in 2 cases/4 joints. Conclusion: The improved imaging is sensitive in the diagnosis of early staged AS, for the application of thin slice scan, which helps to reduce partial volume effect. Scanning along the longitudinal axis of the sacroiliac joint extends the observation of erosion of the joint surface. For progressive or stable staged AS, the alterations of bone and joint space are prominent, improved CT imaging is not superior to the conventional. (authors)

  2. Computational methods in molecular imaging technologies

    CERN Document Server

    Gunjan, Vinit Kumar; Venkatesh, C; Amarnath, M

    2017-01-01

    This book highlights the experimental investigations that have been carried out on magnetic resonance imaging and computed tomography (MRI & CT) images using state-of-the-art Computational Image processing techniques, and tabulates the statistical values wherever necessary. In a very simple and straightforward way, it explains how image processing methods are used to improve the quality of medical images and facilitate analysis. It offers a valuable resource for researchers, engineers, medical doctors and bioinformatics experts alike.

  3. A method for improved clustering and classification of microscopy images using quantitative co-localization coefficients

    LENUS (Irish Health Repository)

    Singan, Vasanth R

    2012-06-08

    AbstractBackgroundThe localization of proteins to specific subcellular structures in eukaryotic cells provides important information with respect to their function. Fluorescence microscopy approaches to determine localization distribution have proved to be an essential tool in the characterization of unknown proteins, and are now particularly pertinent as a result of the wide availability of fluorescently-tagged constructs and antibodies. However, there are currently very few image analysis options able to effectively discriminate proteins with apparently similar distributions in cells, despite this information being important for protein characterization.FindingsWe have developed a novel method for combining two existing image analysis approaches, which results in highly efficient and accurate discrimination of proteins with seemingly similar distributions. We have combined image texture-based analysis with quantitative co-localization coefficients, a method that has traditionally only been used to study the spatial overlap between two populations of molecules. Here we describe and present a novel application for quantitative co-localization, as applied to the study of Rab family small GTP binding proteins localizing to the endomembrane system of cultured cells.ConclusionsWe show how quantitative co-localization can be used alongside texture feature analysis, resulting in improved clustering of microscopy images. The use of co-localization as an additional clustering parameter is non-biased and highly applicable to high-throughput image data sets.

  4. A new method of the light irradiation image by the computed radiography (imaging plate) system

    International Nuclear Information System (INIS)

    Aiba, Susumu; Nishi, Katsuki.

    1997-01-01

    There are two method for the purpose of diagnosing medically by using gamma-ray light irradiation image. One is to use of the scintillation camera for gamma-ray, the other is to use of the photostimulable luminescence point by the secondary excitation of the image plate (IP) system for X-ray. The standpoint of the spatial resolution at the total medical image, using gamma-ray, the first can get the image on a short time, but the first is a poor image quality, and the second is good image quality, but the second can get the image on a long time, because of insensitive to gamma-ray. We report on the improvement for IP's week point by our proposal method, and by our clinical and quantitative analysis data, to use the highly efficient IP (ST-III). We make the improvement on the imaging time (from 30 minutes to 20 minutes), and the inprocessing time (from 33-50 minutes to 27 minutes) for a former method on an organism. We strongly believe that our convenience improvement method, and our clinical quantitative analysis data can contribute to the wide application as well as the quality up for the clinical diagnosis to use gamma-ray. (author)

  5. An Improved Method of Training Overcomplete Dictionary Pair

    Directory of Open Access Journals (Sweden)

    Zhuozheng Wang

    2014-01-01

    Full Text Available Training overcomplete dictionary pair is a critical step of the mainstream superresolution methods. For the high time complexity and susceptible to corruption characteristics of training dictionary, an improved method based on lifting wavelet transform and robust principal component analysis is reported. The high-frequency components of example images are estimated through wavelet coefficients of 3-tier lifting wavelet transform decomposition. Sparse coefficients are similar in multiframe images. Accordingly, the inexact augmented Lagrange multiplier method is employed to achieve robust principal component analysis in the process of imposing global constraints. Experiments reveal that the new algorithm not only reduces the time complexity preserving the clarity but also improves the robustness for the corrupted example images.

  6. Improved Bat Algorithm Applied to Multilevel Image Thresholding

    Directory of Open Access Journals (Sweden)

    Adis Alihodzic

    2014-01-01

    Full Text Available Multilevel image thresholding is a very important image processing technique that is used as a basis for image segmentation and further higher level processing. However, the required computational time for exhaustive search grows exponentially with the number of desired thresholds. Swarm intelligence metaheuristics are well known as successful and efficient optimization methods for intractable problems. In this paper, we adjusted one of the latest swarm intelligence algorithms, the bat algorithm, for the multilevel image thresholding problem. The results of testing on standard benchmark images show that the bat algorithm is comparable with other state-of-the-art algorithms. We improved standard bat algorithm, where our modifications add some elements from the differential evolution and from the artificial bee colony algorithm. Our new proposed improved bat algorithm proved to be better than five other state-of-the-art algorithms, improving quality of results in all cases and significantly improving convergence speed.

  7. Improvement of material decomposition and image quality in dual-energy radiography by reducing image noise

    International Nuclear Information System (INIS)

    Lee, D.; Choi, S.; Kim, H.; Kim, H.-J.; Kim, Y.-S.; Choi, S.; Lee, H.; Jo, B.D.; Jeon, P.-H.; Kim, H.; Kim, D.

    2016-01-01

    Although digital radiography has been widely used for screening human anatomical structures in clinical situations, it has several limitations due to anatomical overlapping. To resolve this problem, dual-energy imaging techniques, which provide a method for decomposing overlying anatomical structures, have been suggested as alternative imaging techniques. Previous studies have reported several dual-energy techniques, each resulting in different image qualities. In this study, we compared three dual-energy techniques: simple log subtraction (SLS), simple smoothing of a high-energy image (SSH), and anti-correlated noise reduction (ACNR) with respect to material thickness quantification and image quality. To evaluate dual-energy radiography, we conducted Monte Carlo simulation and experimental phantom studies. The Geant 4 Application for Tomographic Emission (GATE) v 6.0 and tungsten anode spectral model using interpolation polynomials (TASMIP) codes were used for simulation studies and digital radiography, and human chest phantoms were used for experimental studies. The results of the simulation study showed improved image contrast-to-noise ratio (CNR) and coefficient of variation (COV) values and bone thickness estimation accuracy by applying the ACNR and SSH methods. Furthermore, the chest phantom images showed better image quality with the SSH and ACNR methods compared to the SLS method. In particular, the bone texture characteristics were well-described by applying the SSH and ACNR methods. In conclusion, the SSH and ACNR methods improved the accuracy of material quantification and image quality in dual-energy radiography compared to SLS. Our results can contribute to better diagnostic capabilities of dual-energy images and accurate material quantification in various clinical situations.

  8. Evaluation of processing methods for static radioisotope scan images

    International Nuclear Information System (INIS)

    Oakberg, J.A.

    1976-12-01

    Radioisotope scanning in the field of nuclear medicine provides a method for the mapping of a radioactive drug in the human body to produce maps (images) which prove useful in detecting abnormalities in vital organs. At best, radioisotope scanning methods produce images with poor counting statistics. One solution to improving the body scan images is using dedicated small computers with appropriate software to process the scan data. Eleven methods for processing image data are compared

  9. Remote sensing image ship target detection method based on visual attention model

    Science.gov (United States)

    Sun, Yuejiao; Lei, Wuhu; Ren, Xiaodong

    2017-11-01

    The traditional methods of detecting ship targets in remote sensing images mostly use sliding window to search the whole image comprehensively. However, the target usually occupies only a small fraction of the image. This method has high computational complexity for large format visible image data. The bottom-up selective attention mechanism can selectively allocate computing resources according to visual stimuli, thus improving the computational efficiency and reducing the difficulty of analysis. Considering of that, a method of ship target detection in remote sensing images based on visual attention model was proposed in this paper. The experimental results show that the proposed method can reduce the computational complexity while improving the detection accuracy, and improve the detection efficiency of ship targets in remote sensing images.

  10. Improvement of Sidestream Dark Field Imaging with an Image Acquisition Stabilizer

    Directory of Open Access Journals (Sweden)

    Sjauw Krishan D

    2010-07-01

    Full Text Available Abstract Background In the present study we developed, evaluated in volunteers, and clinically validated an image acquisition stabilizer (IAS for Sidestream Dark Field (SDF imaging. Methods The IAS is a stainless steel sterilizable ring which fits around the SDF probe tip. The IAS creates adhesion to the imaged tissue by application of negative pressure. The effects of the IAS on the sublingual microcirculatory flow velocities, the force required to induce pressure artifacts (PA, the time to acquire a stable image, and the duration of stable imaging were assessed in healthy volunteers. To demonstrate the clinical applicability of the SDF setup in combination with the IAS, simultaneous bilateral sublingual imaging of the microcirculation were performed during a lung recruitment maneuver (LRM in mechanically ventilated critically ill patients. One SDF device was operated handheld; the second was fitted with the IAS and held in position by a mechanic arm. Lateral drift, number of losses of image stability and duration of stable imaging of the two methods were compared. Results Five healthy volunteers were studied. The IAS did not affect microcirculatory flow velocities. A significantly greater force had to applied onto the tissue to induced PA with compared to without IAS (0.25 ± 0.15 N without vs. 0.62 ± 0.05 N with the IAS, p Conclusions The present study has validated the use of an IAS for improvement of SDF imaging by demonstrating that the IAS did not affect microcirculatory perfusion in the microscopic field of view. The IAS improved both axial and lateral SDF image stability and thereby increased the critical force required to induce pressure artifacts. The IAS ensured a significantly increased duration of maintaining a stable image sequence.

  11. Approaches for improving image quality in magnetic induction tomography

    International Nuclear Information System (INIS)

    Maimaitijiang, Y; Roula, M A; Kahlert, J

    2010-01-01

    Magnetic induction tomography (MIT) is a contactless and non-invasive method for imaging the passive electrical properties of objects. Measuring the weak signal produced by eddy currents within biological soft tissues can be challenging in the presence of noise and the large signals resulting from the direct excitation–detection coil coupling. To detect haemorrhagic stroke in the brain, for instance, high measurement accuracy is required to enable images with enough contrast to differentiate between normal and haemorrhaged brain tissues. The reconstructed images are often very sensitive to inevitable measurement noise from the environment, system instabilities and patient-related artefacts such as movement and sweating. We propose methods for mitigating signal noise and improving image reconstruction. We evaluated and compared the use of a range wavelet transforms for signal denoising. Adaptive regularization methods including L-curve, generalized cross validation (GCV) and noise estimation were also compared. We evaluated all these described methods with measurements of in vitro tissues resembling a peripheral haemorrhagic cerebral stroke created by placing a bio-membrane package filled with 10 ml blood in a swine brain of 100 ml. We show that wavelet packet denoising combined with adaptive regularization can improve the quality of reconstructed images

  12. Improved SAR Image Coregistration Using Pixel-Offset Series

    KAUST Repository

    Wang, Teng

    2014-03-14

    Synthetic aperture radar (SAR) image coregistration is a key procedure before interferometric SAR (InSAR) time-series analysis can be started. However, many geophysical data sets suffer from severe decorrelation problems due to a variety of reasons, making precise coregistration a nontrivial task. Here, we present a new strategy that uses a pixel-offset series of detected subimage patches dominated by point-like targets (PTs) to improve SAR image coregistrations. First, all potentially coherent image pairs are coregistered in a conventional way. In this step, we propose a coregistration quality index for each image to rank its relative “significance” within the data set and to select a reference image for the SAR data set. Then, a pixel-offset series of detected PTs is made from amplitude maps to improve the geometrical mapping functions. Finally, all images are resampled depending on the pixel offsets calculated from the updated geometrical mapping functions. We used images from a rural region near the North Anatolian Fault in eastern Turkey to test the proposed method, and clear coregistration improvements were found based on amplitude stability. This enhanced the fact that the coregistration strategy should therefore lead to improved InSAR time-series analysis results.

  13. Improved SAR Image Coregistration Using Pixel-Offset Series

    KAUST Repository

    Wang, Teng; Jonsson, Sigurjon; Hanssen, Ramon F.

    2014-01-01

    Synthetic aperture radar (SAR) image coregistration is a key procedure before interferometric SAR (InSAR) time-series analysis can be started. However, many geophysical data sets suffer from severe decorrelation problems due to a variety of reasons, making precise coregistration a nontrivial task. Here, we present a new strategy that uses a pixel-offset series of detected subimage patches dominated by point-like targets (PTs) to improve SAR image coregistrations. First, all potentially coherent image pairs are coregistered in a conventional way. In this step, we propose a coregistration quality index for each image to rank its relative “significance” within the data set and to select a reference image for the SAR data set. Then, a pixel-offset series of detected PTs is made from amplitude maps to improve the geometrical mapping functions. Finally, all images are resampled depending on the pixel offsets calculated from the updated geometrical mapping functions. We used images from a rural region near the North Anatolian Fault in eastern Turkey to test the proposed method, and clear coregistration improvements were found based on amplitude stability. This enhanced the fact that the coregistration strategy should therefore lead to improved InSAR time-series analysis results.

  14. Ultrasonic particle image velocimetry for improved flow gradient imaging: algorithms, methodology and validation

    International Nuclear Information System (INIS)

    Niu Lili; Qian Ming; Yu Wentao; Jin Qiaofeng; Ling Tao; Zheng Hairong; Wan Kun; Gao Shen

    2010-01-01

    This paper presents a new algorithm for ultrasonic particle image velocimetry (Echo PIV) for improving the flow velocity measurement accuracy and efficiency in regions with high velocity gradients. The conventional Echo PIV algorithm has been modified by incorporating a multiple iterative algorithm, sub-pixel method, filter and interpolation method, and spurious vector elimination algorithm. The new algorithms' performance is assessed by analyzing simulated images with known displacements, and ultrasonic B-mode images of in vitro laminar pipe flow, rotational flow and in vivo rat carotid arterial flow. Results of the simulated images show that the new algorithm produces much smaller bias from the known displacements. For laminar flow, the new algorithm results in 1.1% deviation from the analytically derived value, and 8.8% for the conventional algorithm. The vector quality evaluation for the rotational flow imaging shows that the new algorithm produces better velocity vectors. For in vivo rat carotid arterial flow imaging, the results from the new algorithm deviate 6.6% from the Doppler-measured peak velocities averagely compared to 15% of that from the conventional algorithm. The new Echo PIV algorithm is able to effectively improve the measurement accuracy in imaging flow fields with high velocity gradients.

  15. Wavelet imaging cleaning method for atmospheric Cherenkov telescopes

    Science.gov (United States)

    Lessard, R. W.; Cayón, L.; Sembroski, G. H.; Gaidos, J. A.

    2002-07-01

    We present a new method of image cleaning for imaging atmospheric Cherenkov telescopes. The method is based on the utilization of wavelets to identify noise pixels in images of gamma-ray and hadronic induced air showers. This method selects more signal pixels with Cherenkov photons than traditional image processing techniques. In addition, the method is equally efficient at rejecting pixels with noise alone. The inclusion of more signal pixels in an image of an air shower allows for a more accurate reconstruction, especially at lower gamma-ray energies that produce low levels of light. We present the results of Monte Carlo simulations of gamma-ray and hadronic air showers which show improved angular resolution using this cleaning procedure. Data from the Whipple Observatory's 10-m telescope are utilized to show the efficacy of the method for extracting a gamma-ray signal from the background of hadronic generated images.

  16. WE-EF-303-04: An Advanced Image Processing Method to Improve the Spatial Resolution of Proton Radiographies

    International Nuclear Information System (INIS)

    Rinaldi, I; Parodi, K; Krah, N

    2015-01-01

    Purpose: We present an optimization method to improve the spatial resolution and the water equivalent thickness accuracy of proton radiographies. Methods: The method is designed for imaging systems measuring only the residual range of protons without relying on tracker detectors to determine the beam trajectory before and after the target. Specifically, the method was used for an imaging set-up consisting of a stack of 61 parallel-plate ionization chambers (PPIC) working as a range telescope. The method uses a decomposition approach of the residual range signal measured by the PPIC and constructs subimages with small size pixels geometrically rearranged and appropriately averaged to be merged into a final single radiography. The method was tested using Monte Carlo simulated and experimental proton radiographies of a PMMA step phantom and an anthropomorphic head phantom. Results: For the step phantom, the effective spatial resolution was found to be 4 and 3 times higher than the nominal resolution for the simulated and experimental radiographies, respectively. For the head phantom, a gamma index was calculated to quantify the conformity of the simulated proton radiographies with a digitally reconstructed X-ray radiography convolved with a Gaussian kernel equal to the proton beam spot-size. For DTA=2.5 mm and RD=2.5%, the passing ratio was 100%/85% for the optimized/non-optimized case, respectively. An extension of the method allows reducing the dose given to the patient during radiography acquisition. We show that despite a dose reduction of 25 times (leading to a dose of 0.016 mGy for the current imaging set-up), the image quality of the optimized radiographies remains fairly unaffected for both the simulated and experimental results. Conclusion: The optimization method leads to a significant increase of the spatial resolution allowing recovering image details that are unresolved in non-optimized radiographies. These results represent a major step towards clinical

  17. Image Processing Tools for Improved Visualization and Analysis of Remotely Sensed Images for Agriculture and Forest Classifications

    OpenAIRE

    SINHA G. R.

    2017-01-01

    This paper suggests Image Processing tools for improved visualization and better analysis of remotely sensed images. There are methods already available in literature for the purpose but the most important challenge among the limitations is lack of robustness. We propose an optimal method for image enhancement of the images using fuzzy based approaches and few optimization tools. The segmentation images subsequently obtained after de-noising will be classified into distinct information and th...

  18. Image portion identification methods, image parsing methods, image parsing systems, and articles of manufacture

    Science.gov (United States)

    Lassahn, Gordon D.; Lancaster, Gregory D.; Apel, William A.; Thompson, Vicki S.

    2013-01-08

    Image portion identification methods, image parsing methods, image parsing systems, and articles of manufacture are described. According to one embodiment, an image portion identification method includes accessing data regarding an image depicting a plurality of biological substrates corresponding to at least one biological sample and indicating presence of at least one biological indicator within the biological sample and, using processing circuitry, automatically identifying a portion of the image depicting one of the biological substrates but not others of the biological substrates.

  19. An enhanced narrow-band imaging method for the microvessel detection

    Science.gov (United States)

    Yu, Feng; Song, Enmin; Liu, Hong; Wan, Youming; Zhu, Jun; Hung, Chih-Cheng

    2018-02-01

    A medical endoscope system combined with the narrow-band imaging (NBI), has been shown to be a superior diagnostic tool for early cancer detection. The NBI can reveal the morphologic changes of microvessels in the superficial cancer. In order to improve the conspicuousness of microvessel texture, we propose an enhanced NBI method to improve the conspicuousness of endoscopic images. To obtain the more conspicuous narrow-band images, we use the edge operator to extract the edge information of the narrow-band blue and green images, and give a weight to the extracted edges. Then, the weighted edges are fused with the narrow-band blue and green images. Finally, the displayed endoscopic images are reconstructed with the enhanced narrow-band images. In addition, we evaluate the performance of enhanced narrow-band images with different edge operators. Experimental results indicate that the Sobel and Canny operators achieve the best performance of all. Compared with traditional NBI method of Olympus company, our proposed method has more conspicuous texture of microvessel.

  20. A Single Image Dehazing Method Using Average Saturation Prior

    Directory of Open Access Journals (Sweden)

    Zhenfei Gu

    2017-01-01

    Full Text Available Outdoor images captured in bad weather are prone to yield poor visibility, which is a fatal problem for most computer vision applications. The majority of existing dehazing methods rely on an atmospheric scattering model and therefore share a common limitation; that is, the model is only valid when the atmosphere is homogeneous. In this paper, we propose an improved atmospheric scattering model to overcome this inherent limitation. By adopting the proposed model, a corresponding dehazing method is also presented. In this method, we first create a haze density distribution map of a hazy image, which enables us to segment the hazy image into scenes according to the haze density similarity. Then, in order to improve the atmospheric light estimation accuracy, we define an effective weight assignment function to locate a candidate scene based on the scene segmentation results and therefore avoid most potential errors. Next, we propose a simple but powerful prior named the average saturation prior (ASP, which is a statistic of extensive high-definition outdoor images. Using this prior combined with the improved atmospheric scattering model, we can directly estimate the scene atmospheric scattering coefficient and restore the scene albedo. The experimental results verify that our model is physically valid, and the proposed method outperforms several state-of-the-art single image dehazing methods in terms of both robustness and effectiveness.

  1. Images Encryption Method using Steganographic LSB Method, AES and RSA algorithm

    Science.gov (United States)

    Moumen, Abdelkader; Sissaoui, Hocine

    2017-03-01

    Vulnerability of communication of digital images is an extremely important issue nowadays, particularly when the images are communicated through insecure channels. To improve communication security, many cryptosystems have been presented in the image encryption literature. This paper proposes a novel image encryption technique based on an algorithm that is faster than current methods. The proposed algorithm eliminates the step in which the secrete key is shared during the encryption process. It is formulated based on the symmetric encryption, asymmetric encryption and steganography theories. The image is encrypted using a symmetric algorithm, then, the secret key is encrypted by means of an asymmetrical algorithm and it is hidden in the ciphered image using a least significant bits steganographic scheme. The analysis results show that while enjoying the faster computation, our method performs close to optimal in terms of accuracy.

  2. A method for fast automated microscope image stitching.

    Science.gov (United States)

    Yang, Fan; Deng, Zhen-Sheng; Fan, Qiu-Hong

    2013-05-01

    Image stitching is an important technology to produce a panorama or larger image by combining several images with overlapped areas. In many biomedical researches, image stitching is highly desirable to acquire a panoramic image which represents large areas of certain structures or whole sections, while retaining microscopic resolution. In this study, we develop a fast normal light microscope image stitching algorithm based on feature extraction. At first, an algorithm of scale-space reconstruction of speeded-up robust features (SURF) was proposed to extract features from the images to be stitched with a short time and higher repeatability. Then, the histogram equalization (HE) method was employed to preprocess the images to enhance their contrast for extracting more features. Thirdly, the rough overlapping zones of the images preprocessed were calculated by phase correlation, and the improved SURF was used to extract the image features in the rough overlapping areas. Fourthly, the features were corresponded by matching algorithm and the transformation parameters were estimated, then the images were blended seamlessly. Finally, this procedure was applied to stitch normal light microscope images to verify its validity. Our experimental results demonstrate that the improved SURF algorithm is very robust to viewpoint, illumination, blur, rotation and zoom of the images and our method is able to stitch microscope images automatically with high precision and high speed. Also, the method proposed in this paper is applicable to registration and stitching of common images as well as stitching the microscope images in the field of virtual microscope for the purpose of observing, exchanging, saving, and establishing a database of microscope images. Copyright © 2013 Elsevier Ltd. All rights reserved.

  3. Reconstruction of CT images by the Bayes- back projection method

    CERN Document Server

    Haruyama, M; Takase, M; Tobita, H

    2002-01-01

    In the course of research on quantitative assay of non-destructive measurement of radioactive waste, the have developed a unique program based on the Bayesian theory for reconstruction of transmission computed tomography (TCT) image. The reconstruction of cross-section images in the CT technology usually employs the Filtered Back Projection method. The new imaging reconstruction program reported here is based on the Bayesian Back Projection method, and it has a function of iterative improvement images by every step of measurement. Namely, this method has the capability of prompt display of a cross-section image corresponding to each angled projection data from every measurement. Hence, it is possible to observe an improved cross-section view by reflecting each projection data in almost real time. From the basic theory of Baysian Back Projection method, it can be not only applied to CT types of 1st, 2nd, and 3rd generation. This reported deals with a reconstruction program of cross-section images in the CT of ...

  4. Accelerated gradient methods for constrained image deblurring

    International Nuclear Information System (INIS)

    Bonettini, S; Zanella, R; Zanni, L; Bertero, M

    2008-01-01

    In this paper we propose a special gradient projection method for the image deblurring problem, in the framework of the maximum likelihood approach. We present the method in a very general form and we give convergence results under standard assumptions. Then we consider the deblurring problem and the generality of the proposed algorithm allows us to add a energy conservation constraint to the maximum likelihood problem. In order to improve the convergence rate, we devise appropriate scaling strategies and steplength updating rules, especially designed for this application. The effectiveness of the method is evaluated by means of a computational study on astronomical images corrupted by Poisson noise. Comparisons with standard methods for image restoration, such as the expectation maximization algorithm, are also reported.

  5. An Improved Pansharpening Method for Misaligned Panchromatic and Multispectral Data.

    Science.gov (United States)

    Li, Hui; Jing, Linhai; Tang, Yunwei; Ding, Haifeng

    2018-02-11

    Numerous pansharpening methods were proposed in recent decades for fusing low-spatial-resolution multispectral (MS) images with high-spatial-resolution (HSR) panchromatic (PAN) bands to produce fused HSR MS images, which are widely used in various remote sensing tasks. The effect of misregistration between MS and PAN bands on quality of fused products has gained much attention in recent years. An improved method for misaligned MS and PAN imagery is proposed, through two improvements made on a previously published method named RMI (reduce misalignment impact). The performance of the proposed method was assessed by comparing with some outstanding fusion methods, such as adaptive Gram-Schmidt and generalized Laplacian pyramid. Experimental results show that the improved version can reduce spectral distortions of fused dark pixels and sharpen boundaries between different image objects, as well as obtain similar quality indexes with the original RMI method. In addition, the proposed method was evaluated with respect to its sensitivity to misalignments between MS and PAN bands. It is certified that the proposed method is more robust to misalignments between MS and PAN bands than the other methods.

  6. A new method for mobile phone image denoising

    Science.gov (United States)

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

    2015-12-01

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

  7. An improved level set method for brain MR images segmentation and bias correction.

    Science.gov (United States)

    Chen, Yunjie; Zhang, Jianwei; Macione, Jim

    2009-10-01

    Intensity inhomogeneities cause considerable difficulty in the quantitative analysis of magnetic resonance (MR) images. Thus, bias field estimation is a necessary step before quantitative analysis of MR data can be undertaken. This paper presents a variational level set approach to bias correction and segmentation for images with intensity inhomogeneities. Our method is based on an observation that intensities in a relatively small local region are separable, despite of the inseparability of the intensities in the whole image caused by the overall intensity inhomogeneity. We first define a localized K-means-type clustering objective function for image intensities in a neighborhood around each point. The cluster centers in this objective function have a multiplicative factor that estimates the bias within the neighborhood. The objective function is then integrated over the entire domain to define the data term into the level set framework. Our method is able to capture bias of quite general profiles. Moreover, it is robust to initialization, and thereby allows fully automated applications. The proposed method has been used for images of various modalities with promising results.

  8. Improved Stereo Matching With Boosting Method

    Directory of Open Access Journals (Sweden)

    Shiny B

    2015-06-01

    Full Text Available Abstract This paper presents an approach based on classification for improving the accuracy of stereo matching methods. We propose this method for occlusion handling. This work employs classification of pixels for finding the erroneous disparity values. Due to the wide applications of disparity map in 3D television medical imaging etc the accuracy of disparity map has high significance. An initial disparity map is obtained using local or global stereo matching methods from the input stereo image pair. The various features for classification are computed from the input stereo image pair and the obtained disparity map. Then the computed feature vector is used for classification of pixels by using GentleBoost as the classification method. The erroneous disparity values in the disparity map found by classification are corrected through a completion stage or filling stage. A performance evaluation of stereo matching using AdaBoostM1 RUSBoost Neural networks and GentleBoost is performed.

  9. Improved Dynamic Analysis method for quantitative PIXE and SXRF element imaging of complex materials

    International Nuclear Information System (INIS)

    Ryan, C.G.; Laird, J.S.; Fisher, L.A.; Kirkham, R.; Moorhead, G.F.

    2015-01-01

    The Dynamic Analysis (DA) method in the GeoPIXE software provides a rapid tool to project quantitative element images from PIXE and SXRF imaging event data both for off-line analysis and in real-time embedded in a data acquisition system. Initially, it assumes uniform sample composition, background shape and constant model X-ray relative intensities. A number of image correction methods can be applied in GeoPIXE to correct images to account for chemical concentration gradients, differential absorption effects, and to correct images for pileup effects. A new method, applied in a second pass, uses an end-member phase decomposition obtained from the first pass, and DA matrices determined for each end-member, to re-process the event data with each pixel treated as an admixture of end-member terms. This paper describes the new method and demonstrates through examples and Monte-Carlo simulations how it better tracks spatially complex composition and background shape while still benefitting from the speed of DA.

  10. Improved Dynamic Analysis method for quantitative PIXE and SXRF element imaging of complex materials

    Energy Technology Data Exchange (ETDEWEB)

    Ryan, C.G., E-mail: chris.ryan@csiro.au; Laird, J.S.; Fisher, L.A.; Kirkham, R.; Moorhead, G.F.

    2015-11-15

    The Dynamic Analysis (DA) method in the GeoPIXE software provides a rapid tool to project quantitative element images from PIXE and SXRF imaging event data both for off-line analysis and in real-time embedded in a data acquisition system. Initially, it assumes uniform sample composition, background shape and constant model X-ray relative intensities. A number of image correction methods can be applied in GeoPIXE to correct images to account for chemical concentration gradients, differential absorption effects, and to correct images for pileup effects. A new method, applied in a second pass, uses an end-member phase decomposition obtained from the first pass, and DA matrices determined for each end-member, to re-process the event data with each pixel treated as an admixture of end-member terms. This paper describes the new method and demonstrates through examples and Monte-Carlo simulations how it better tracks spatially complex composition and background shape while still benefitting from the speed of DA.

  11. On an image reconstruction method for ECT

    Science.gov (United States)

    Sasamoto, Akira; Suzuki, Takayuki; Nishimura, Yoshihiro

    2007-04-01

    An image by Eddy Current Testing(ECT) is a blurred image to original flaw shape. In order to reconstruct fine flaw image, a new image reconstruction method has been proposed. This method is based on an assumption that a very simple relationship between measured data and source were described by a convolution of response function and flaw shape. This assumption leads to a simple inverse analysis method with deconvolution.In this method, Point Spread Function (PSF) and Line Spread Function(LSF) play a key role in deconvolution processing. This study proposes a simple data processing to determine PSF and LSF from ECT data of machined hole and line flaw. In order to verify its validity, ECT data for SUS316 plate(200x200x10mm) with artificial machined hole and notch flaw had been acquired by differential coil type sensors(produced by ZETEC Inc). Those data were analyzed by the proposed method. The proposed method restored sharp discrete multiple hole image from interfered data by multiple holes. Also the estimated width of line flaw has been much improved compared with original experimental data. Although proposed inverse analysis strategy is simple and easy to implement, its validity to holes and line flaw have been shown by many results that much finer image than original image have been reconstructed.

  12. A Robust Photogrammetric Processing Method of Low-Altitude UAV Images

    Directory of Open Access Journals (Sweden)

    Mingyao Ai

    2015-02-01

    Full Text Available Low-altitude Unmanned Aerial Vehicles (UAV images which include distortion, illumination variance, and large rotation angles are facing multiple challenges of image orientation and image processing. In this paper, a robust and convenient photogrammetric approach is proposed for processing low-altitude UAV images, involving a strip management method to automatically build a standardized regional aerial triangle (AT network, a parallel inner orientation algorithm, a ground control points (GCPs predicting method, and an improved Scale Invariant Feature Transform (SIFT method to produce large number of evenly distributed reliable tie points for bundle adjustment (BA. A multi-view matching approach is improved to produce Digital Surface Models (DSM and Digital Orthophoto Maps (DOM for 3D visualization. Experimental results show that the proposed approach is robust and feasible for photogrammetric processing of low-altitude UAV images and 3D visualization of products.

  13. Visual improvement for bad handwriting based on Monte-Carlo method

    Science.gov (United States)

    Shi, Cao; Xiao, Jianguo; Xu, Canhui; Jia, Wenhua

    2014-03-01

    A visual improvement algorithm based on Monte Carlo simulation is proposed in this paper, in order to enhance visual effects for bad handwriting. The whole improvement process is to use well designed typeface so as to optimize bad handwriting image. In this process, a series of linear operators for image transformation are defined for transforming typeface image to approach handwriting image. And specific parameters of linear operators are estimated by Monte Carlo method. Visual improvement experiments illustrate that the proposed algorithm can effectively enhance visual effect for handwriting image as well as maintain the original handwriting features, such as tilt, stroke order and drawing direction etc. The proposed visual improvement algorithm, in this paper, has a huge potential to be applied in tablet computer and Mobile Internet, in order to improve user experience on handwriting.

  14. Imaging of underground karst water channels using an improved multichannel transient Rayleigh wave detecting method.

    Science.gov (United States)

    Zheng, Xuhui; Liu, Lei; Sun, Jinzhong; Li, Gao; Zhou, Fubiao; Xu, Jiemin

    2018-01-01

    Geological and hydrogeological conditions in karst areas are complicated from the viewpoint of engineering. The construction of underground structures in these areas is often disturbed by the gushing of karst water, which may delay the construction schedule, result in economic losses, and even cause heavy casualties. In this paper, an innovative method of multichannel transient Rayleigh wave detecting is proposed by introducing the concept of arrival time difference phase between channels (TDP). Overcoming the restriction of the space-sampling law, the proposed method can extract the phase velocities of different frequency components from only two channels of transient Rayleigh wave recorded on two adjacent detecting points. This feature greatly improves the work efficiency and lateral resolution of transient Rayleigh wave detecting. The improved multichannel transient Rayleigh wave detecting method is applied to the detection of karst caves and fractures in rock mass of the foundation pit of Yan'an Road Station of Guiyang Metro. The imaging of the detecting results clearly reveals the distribution of karst water inflow channels, which provided significant guidance for water plugging and enabled good control over karst water gushing in the foundation pit.

  15. Improving settlement type classification of aerial images

    CSIR Research Space (South Africa)

    Mdakane, L

    2014-10-01

    Full Text Available , an automated method can be used to help identify human settlements in a fixed, repeatable and timely manner. The main contribution of this work is to improve generalisation on settlement type classification of aerial imagery. Images acquired at different dates...

  16. Improvements in image quality with pseudo-parallel imaging in the phase-scrambling fourier transform technique

    International Nuclear Information System (INIS)

    Ito, Satoshi; Kawawa, Yasuhiro; Yamada, Yoshifumi

    2010-01-01

    The signal obtained in the phase-scrambling Fourier transform (PSFT) imaging technique can be transformed to the signal described by the Fresnel transform of the objects, in which the amplitude of the PSFT presents some kind of blurred image of the objects. Therefore, the signal can be considered to exist in the object domain as well as the Fourier domain of the object. This notable feature makes it possible to assign weights to the reconstructed images by applying a weighting function to the PSFT signal after data acquisition, and as a result, pseudo-parallel image reconstruction using these aliased image data with different weights on the images is feasible. In this study, the improvements in image quality with such pseudo-parallel imaging were examined and demonstrated. The weighting function of the PSFT signal that provides a given weight on the image is estimated using the obtained image data and is iteratively updated after sensitivity encoding (SENSE)-based image reconstruction. Simulation studies showed that reconstruction errors were dramatically reduced and that the spatial resolution was also improved in almost all image spaces. The proposed method was applied to signals synthesized from MR image data with phase variations to verify its effectiveness. It was found that the image quality was improved and that images almost entirely free of aliasing artifacts could be obtained. (author)

  17. Bowtie filter and water calibration in the improvement of cone beam CT image quality

    International Nuclear Information System (INIS)

    Li Minghui; Dai Jianrong; Zhang Ke

    2010-01-01

    Objective: To evaluate the improvement of cone beam CT (CBCT) image quality by using bewtie filter (F 1 ) and water calibration. Methods: First the multi-level gain calibration of the detector panel with the method of Cal 2 calibration was performed, and the CT images of CATPHAN503 with F 0 and bowtie filter were collected, respectively. Then the detector panel using water calibration kit was calibrated, and images were acquired again. Finally, the change of image quality after using F 1 and (or) water calibration method was observed. The observed indexes included low contrast visibility, spatial uniformity, ring artifact, spatial resolution and geometric accuracy. Results: Comparing with the traditional combination of F 0 filter and Cal 2 calibration, the combination of bowtie filter F 1 and water calibration improves low contrast visibility by 13.71%, and spatial uniformity by 54. 42%. Water calibration removes ring artifacts effectively. However, none of them improves spatial resolution and geometric accuracy. Conclusions: The combination of F 1 and water calibration improves CBCT image quality effectively. This improvement is aid to the registration of CBCT images and localization images. (authors)

  18. Novel welding image processing method based on fractal theory

    Institute of Scientific and Technical Information of China (English)

    陈强; 孙振国; 肖勇; 路井荣

    2002-01-01

    Computer vision has come into used in the fields of welding process control and automation. In order to improve precision and rapidity of welding image processing, a novel method based on fractal theory has been put forward in this paper. Compared with traditional methods, the image is preliminarily processed in the macroscopic regions then thoroughly analyzed in the microscopic regions in the new method. With which, an image is divided up to some regions according to the different fractal characters of image edge, and the fuzzy regions including image edges are detected out, then image edges are identified with Sobel operator and curved by LSM (Lease Square Method). Since the data to be processed have been decreased and the noise of image has been reduced, it has been testified through experiments that edges of weld seam or weld pool could be recognized correctly and quickly.

  19. Enhancing the (MSLDIP) image steganographic method (ESLDIP method)

    Science.gov (United States)

    Seddik Saad, Al-hussien

    2011-10-01

    Message transmissions over the Internet still have data security problem. Therefore, secure and secret communication methods are needed for transmitting messages over the Internet. Cryptography scrambles the message so that it cannot be understood. However, it makes the message suspicious enough to attract eavesdropper's attention. Steganography hides the secret message within other innocuous-looking cover files (i.e. images, music and video files) so that it cannot be observed [1].The term steganography originates from the Greek root words "steganos'' and "graphein'' which literally mean "covered writing''. It is defined as the science that involves communicating secret data in an appropriate multimedia carrier, e.g., image, audio text and video files [3].Steganographic techniques allow one party to communicate information to another without a third party even knowing that the communication is occurring. The ways to deliver these "secret messages" vary greatly [3].Our proposed method called Enhanced SLDIP (ESLDIP). In which the maximmum hiding capacity (MHC) of proposed ESLDIP method is higher than the previously proposed MSLDIP methods and the PSNR of the ESLDIP method is higher than the MSLDIP PSNR values', which means that the image quality of the ESLDIP method will be better than MSLDIP method and the maximmum hiding capacity (MHC) also improved. The rest of this paper is organized as follows. In section 2, steganography has been discussed; lingo, carriers and types. In section 3, related works are introduced. In section 4, the proposed method will be discussed in details. In section 5, the simulation results are given and Section 6 concludes the paper.

  20. An improved three-dimensional non-scanning laser imaging system based on digital micromirror device

    Science.gov (United States)

    Xia, Wenze; Han, Shaokun; Lei, Jieyu; Zhai, Yu; Timofeev, Alexander N.

    2018-01-01

    Nowadays, there are two main methods to realize three-dimensional non-scanning laser imaging detection, which are detection method based on APD and detection method based on Streak Tube. However, the detection method based on APD possesses some disadvantages, such as small number of pixels, big pixel interval and complex supporting circuit. The detection method based on Streak Tube possesses some disadvantages, such as big volume, bad reliability and high cost. In order to resolve the above questions, this paper proposes an improved three-dimensional non-scanning laser imaging system based on Digital Micromirror Device. In this imaging system, accurate control of laser beams and compact design of imaging structure are realized by several quarter-wave plates and a polarizing beam splitter. The remapping fiber optics is used to sample the image plane of receiving optical lens, and transform the image into line light resource, which can realize the non-scanning imaging principle. The Digital Micromirror Device is used to convert laser pulses from temporal domain to spatial domain. The CCD with strong sensitivity is used to detect the final reflected laser pulses. In this paper, we also use an algorithm which is used to simulate this improved laser imaging system. In the last, the simulated imaging experiment demonstrates that this improved laser imaging system can realize three-dimensional non-scanning laser imaging detection.

  1. Super-resolution convolutional neural network for the improvement of the image quality of magnified images in chest radiographs

    Science.gov (United States)

    Umehara, Kensuke; Ota, Junko; Ishimaru, Naoki; Ohno, Shunsuke; Okamoto, Kentaro; Suzuki, Takanori; Shirai, Naoki; Ishida, Takayuki

    2017-02-01

    Single image super-resolution (SR) method can generate a high-resolution (HR) image from a low-resolution (LR) image by enhancing image resolution. In medical imaging, HR images are expected to have a potential to provide a more accurate diagnosis with the practical application of HR displays. In recent years, the super-resolution convolutional neural network (SRCNN), which is one of the state-of-the-art deep learning based SR methods, has proposed in computer vision. In this study, we applied and evaluated the SRCNN scheme to improve the image quality of magnified images in chest radiographs. For evaluation, a total of 247 chest X-rays were sampled from the JSRT database. The 247 chest X-rays were divided into 93 training cases with non-nodules and 152 test cases with lung nodules. The SRCNN was trained using the training dataset. With the trained SRCNN, the HR image was reconstructed from the LR one. We compared the image quality of the SRCNN and conventional image interpolation methods, nearest neighbor, bilinear and bicubic interpolations. For quantitative evaluation, we measured two image quality metrics, peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). In the SRCNN scheme, PSNR and SSIM were significantly higher than those of three interpolation methods (pmethods without any obvious artifacts. These preliminary results indicate that the SRCNN scheme significantly outperforms conventional interpolation algorithms for enhancing image resolution and that the use of the SRCNN can yield substantial improvement of the image quality of magnified images in chest radiographs.

  2. Development of flow velocity measurement techniques in visible images. Improvement of particle image velocimetry techniques on image process

    International Nuclear Information System (INIS)

    Kimura, Nobuyuki; Nishimura, Motohiko; Kamide, Hideki; Hishida, Koichi

    1999-10-01

    Noise reduction system was developed to improve applicability of Particle Image Velocimetry (PIV) to complicated configure bounded flows. For fast reactor safety and thermal hydraulic studies, experiments are performed in scale models which usually have rather complicated geometry and structures such as fuel subassemblies, heat exchangers, etc. The structures and stuck dusts on the view window of the models obscure the particle image. Thus the image except the moving particles can be regarded as a noise. In the present study, two noise reduction techniques are proposed. The one is the Time-averaged Light Intensity Subtraction method (TIS) which subtracts the time-averaged light intensity of each pixel in the sequential images from the each corresponding pixel. The other one is the Minimum Light Intensity Subtraction method (MIS) which subtracts the minimum light intensity of each pixel in the sequential images from the each corresponding pixel. Both methods are examined on their capabilities of noise reduction. As for the original 'bench mark' image, the image made from Large Eddy Simulation was used. To the bench mark image, noises are added which are referred as sample images. Both methods reduce the rate of vector with the error of more than one pixel from 90% to less than 5%. Also, more than 50% of the vectors have the error of less than 0.2 pixel. The analysis of uncertainty shows that these methods enhances the accuracy of vector measurement 3 ∼ 12 times if the image with noise were processed, and the MIS method has 1.1 ∼ 2.1 times accuracy compared to the TIS. Thus the present noise reduction methods are quite efficient to enhance the accuracy of flow velocity fields measured with particle images including structures and deposits on the view window. (author)

  3. An imaging method of wavefront coding system based on phase plate rotation

    Science.gov (United States)

    Yi, Rigui; Chen, Xi; Dong, Liquan; Liu, Ming; Zhao, Yuejin; Liu, Xiaohua

    2018-01-01

    Wave-front coding has a great prospect in extending the depth of the optical imaging system and reducing optical aberrations, but the image quality and noise performance are inevitably reduced. According to the theoretical analysis of the wave-front coding system and the phase function expression of the cubic phase plate, this paper analyzed and utilized the feature that the phase function expression would be invariant in the new coordinate system when the phase plate rotates at different angles around the z-axis, and we proposed a method based on the rotation of the phase plate and image fusion. First, let the phase plate rotated at a certain angle around the z-axis, the shape and distribution of the PSF obtained on the image surface remain unchanged, the rotation angle and direction are consistent with the rotation angle of the phase plate. Then, the middle blurred image is filtered by the point spread function of the rotation adjustment. Finally, the reconstruction images were fused by the method of the Laplacian pyramid image fusion and the Fourier transform spectrum fusion method, and the results were evaluated subjectively and objectively. In this paper, we used Matlab to simulate the images. By using the Laplacian pyramid image fusion method, the signal-to-noise ratio of the image is increased by 19% 27%, the clarity is increased by 11% 15% , and the average gradient is increased by 4% 9% . By using the Fourier transform spectrum fusion method, the signal-to-noise ratio of the image is increased by 14% 23%, the clarity is increased by 6% 11% , and the average gradient is improved by 2% 6%. The experimental results show that the image processing by the above method can improve the quality of the restored image, improving the image clarity, and can effectively preserve the image information.

  4. The interpolation method based on endpoint coordinate for CT three-dimensional image

    International Nuclear Information System (INIS)

    Suto, Yasuzo; Ueno, Shigeru.

    1997-01-01

    Image interpolation is frequently used to improve slice resolution to reach spatial resolution. Improved quality of reconstructed three-dimensional images can be attained with this technique as a result. Linear interpolation is a well-known and widely used method. The distance-image method, which is a non-linear interpolation technique, is also used to convert CT value images to distance images. This paper describes a newly developed method that makes use of end-point coordinates: CT-value images are initially converted to binary images by thresholding them and then sequences of pixels with 1-value are arranged in vertical or horizontal directions. A sequence of pixels with 1-value is defined as a line segment which has starting and end points. For each pair of adjacent line segments, another line segment was composed by spatial interpolation of the start and end points. Binary slice images are constructed from the composed line segments. Three-dimensional images were reconstructed from clinical X-ray CT images, using three different interpolation methods and their quality and processing speed were evaluated and compared. (author)

  5. A SAR IMAGE REGISTRATION METHOD BASED ON SIFT ALGORITHM

    Directory of Open Access Journals (Sweden)

    W. Lu

    2017-09-01

    Full Text Available In order to improve the stability and rapidity of synthetic aperture radar (SAR images matching, an effective method was presented. Firstly, the adaptive smoothing filtering was employed for image denoising in image processing based on Wallis filtering to avoid the follow-up noise is amplified. Secondly, feature points were extracted by a simplified SIFT algorithm. Finally, the exact matching of the images was achieved with these points. Compared with the existing methods, it not only maintains the richness of features, but a-lso reduces the noise of the image. The simulation results show that the proposed algorithm can achieve better matching effect.

  6. Research of x-ray automatic image mosaic method

    Science.gov (United States)

    Liu, Bin; Chen, Shunan; Guo, Lianpeng; Xu, Wanpeng

    2013-10-01

    Image mosaic has widely applications value in the fields of medical image analysis, and it is a technology that carries on the spatial matching to a series of image which are overlapped with each other, and finally builds a seamless and high quality image which has high resolution and big eyeshot. In this paper, the method of grayscale cutting pseudo-color enhancement was firstly used to complete the mapping transformation from gray to the pseudo-color, and to extract SIFT features from the images. And then by making use of a similar measure of NCC (normalized cross correlation - Normalized cross-correlation), the method of RANSAC (Random Sample Consensus) was used to exclude the pseudofeature points right in order to complete the exact match of feature points. Finally, seamless mosaic and color fusion were completed by using wavelet multi-decomposition. The experiment shows that the method we used can effectively improve the precision and automation of the medical image mosaic, and provide an effective technical approach for automatic medical image mosaic.

  7. Technical note: Rapid image-based field methods improve the quantification of termite mound structures and greenhouse-gas fluxes

    Directory of Open Access Journals (Sweden)

    P. A. Nauer

    2018-06-01

    Full Text Available Termite mounds (TMs mediate biogeochemical processes with global relevance, such as turnover of the important greenhouse gas methane (CH4. However, the complex internal and external morphology of TMs impede an accurate quantitative description. Here we present two novel field methods, photogrammetry (PG and cross-sectional image analysis, to quantify TM external and internal mound structure of 29 TMs of three termite species. Photogrammetry was used to measure epigeal volume (VE, surface area (AE and mound basal area (AB by reconstructing 3-D models from digital photographs, and compared against a water-displacement method and the conventional approach of approximating TMs by simple geometric shapes. To describe TM internal structure, we introduce TM macro- and micro-porosity (θM and θμ, the volume fractions of macroscopic chambers, and microscopic pores in the wall material, respectively. Macro-porosity was estimated using image analysis of single TM cross sections, and compared against full X-ray computer tomography (CT scans of 17 TMs. For these TMs we present complete pore fractions to assess species-specific differences in internal structure. The PG method yielded VE nearly identical to a water-displacement method, while approximation of TMs by simple geometric shapes led to errors of 4–200 %. Likewise, using PG substantially improved the accuracy of CH4 emission estimates by 10–50 %. Comprehensive CT scanning revealed that investigated TMs have species-specific ranges of θM and θμ, but similar total porosity. Image analysis of single TM cross sections produced good estimates of θM for species with thick walls and evenly distributed chambers. The new image-based methods allow rapid and accurate quantitative characterisation of TMs to answer ecological, physiological and biogeochemical questions. The PG method should be applied when measuring greenhouse-gas emissions from TMs to avoid large errors from inadequate shape

  8. Improved quality of optical coherence tomography imaging of basal cell carcinomas using speckle reduction

    DEFF Research Database (Denmark)

    Mogensen, Mette; Jørgensen, Thomas Martini; Thrane, Lars

    2010-01-01

    suggests a method for improving OCT image quality for skin cancer imaging. EXPERIMENTAL DESIGN: OCT is an optical imaging method analogous to ultrasound. Two basal cell carcinomas (BCC) were imaged using an OCT speckle reduction technique (SR-OCT) based on repeated scanning by altering the distance between...

  9. Improved Wallis Dodging Algorithm for Large-Scale Super-Resolution Reconstruction Remote Sensing Images

    Directory of Open Access Journals (Sweden)

    Chong Fan

    2017-03-01

    Full Text Available A sub-block algorithm is usually applied in the super-resolution (SR reconstruction of images because of limitations in computer memory. However, the sub-block SR images can hardly achieve a seamless image mosaicking because of the uneven distribution of brightness and contrast among these sub-blocks. An effectively improved weighted Wallis dodging algorithm is proposed, aiming at the characteristic that SR reconstructed images are gray images with the same size and overlapping region. This algorithm can achieve consistency of image brightness and contrast. Meanwhile, a weighted adjustment sequence is presented to avoid the spatial propagation and accumulation of errors and the loss of image information caused by excessive computation. A seam line elimination method can share the partial dislocation in the seam line to the entire overlapping region with a smooth transition effect. Subsequently, the improved method is employed to remove the uneven illumination for 900 SR reconstructed images of ZY-3. Then, the overlapping image mosaic method is adopted to accomplish a seamless image mosaic based on the optimal seam line.

  10. Image-Rich Radiology Reports: A Value-Based Model to Improve Clinical Workflow.

    Science.gov (United States)

    Patel, Bhavik N; Lopez, Jose M; Jiang, Brian G; Roth, Christopher J; Nelson, Rendon C

    2017-01-01

    To determine the value of image-rich radiology reports (IRRR) by evaluating the interest and preferences of referring physicians, potential impact on clinical workflow, and the willingness of radiologists to create them. Referring physicians and radiologists were interviewed in this prospective, HIPAA-compliant study. Subject willingness to participate in the study was determined by an e-mail. A single investigator conducted all interviews using a standard questionnaire. All subjects reviewed a video mockup demonstration of IRRR and three methods for viewing embedded images, as follows: (1) clickable hyperlinks to access a scrollable stack of images, (2) scrollable and enlargeable small-image thumbnails, and (3) scrollable but not enlargeable medium-sized images. Questionnaire responses, free comments, and general impressions were captured and analyzed. Seventy-two physicians (36 clinicians, 36 radiologists) were interviewed. Thirty-one clinicians (86%) expressed interest in using IRRR. Seventy-seven percent of subjects believed IRRR would improve communication. Ten clinicians (28%) preferred method 1, 18 (50%) preferred method 2, and 8 (22%) preferred method 3 for embedding images. Thirty clinicians (83%) stated that IRRR would improve efficiency. Twenty-two radiologists (61%) preferred selecting a tool button with a mouse and right-clicking images to embed them, 13 (36%) preferred pressing a function key, and 11 (31%) preferred dictating series and image numbers. The average time radiologists were willing to expend for embedding images was 66.7 seconds. Referring physicians and radiologist both believe IRRR would add value by improving communication with the potential to improve the workflow efficiency of referring physicians. Copyright © 2016 American College of Radiology. Published by Elsevier Inc. All rights reserved.

  11. Iterative methods for dose reduction and image enhancement in tomography

    Science.gov (United States)

    Miao, Jianwei; Fahimian, Benjamin Pooya

    2012-09-18

    A system and method for creating a three dimensional cross sectional image of an object by the reconstruction of its projections that have been iteratively refined through modification in object space and Fourier space is disclosed. The invention provides systems and methods for use with any tomographic imaging system that reconstructs an object from its projections. In one embodiment, the invention presents a method to eliminate interpolations present in conventional tomography. The method has been experimentally shown to provide higher resolution and improved image quality parameters over existing approaches. A primary benefit of the method is radiation dose reduction since the invention can produce an image of a desired quality with a fewer number projections than seen with conventional methods.

  12. Improved Secret Image Sharing Scheme in Embedding Capacity without Underflow and Overflow.

    Science.gov (United States)

    Pang, Liaojun; Miao, Deyu; Li, Huixian; Wang, Qiong

    2015-01-01

    Computational secret image sharing (CSIS) is an effective way to protect a secret image during its transmission and storage, and thus it has attracted lots of attentions since its appearance. Nowadays, it has become a hot topic for researchers to improve the embedding capacity and eliminate the underflow and overflow situations, which is embarrassing and difficult to deal with. The scheme, which has the highest embedding capacity among the existing schemes, has the underflow and overflow problems. Although the underflow and overflow situations have been well dealt with by different methods, the embedding capacities of these methods are reduced more or less. Motivated by these concerns, we propose a novel scheme, in which we take the differential coding, Huffman coding, and data converting to compress the secret image before embedding it to further improve the embedding capacity, and the pixel mapping matrix embedding method with a newly designed matrix is used to embed secret image data into the cover image to avoid the underflow and overflow situations. Experiment results show that our scheme can improve the embedding capacity further and eliminate the underflow and overflow situations at the same time.

  13. A Spectral-Texture Kernel-Based Classification Method for Hyperspectral Images

    Directory of Open Access Journals (Sweden)

    Yi Wang

    2016-11-01

    Full Text Available Classification of hyperspectral images always suffers from high dimensionality and very limited labeled samples. Recently, the spectral-spatial classification has attracted considerable attention and can achieve higher classification accuracy and smoother classification maps. In this paper, a novel spectral-spatial classification method for hyperspectral images by using kernel methods is investigated. For a given hyperspectral image, the principle component analysis (PCA transform is first performed. Then, the first principle component of the input image is segmented into non-overlapping homogeneous regions by using the entropy rate superpixel (ERS algorithm. Next, the local spectral histogram model is applied to each homogeneous region to obtain the corresponding texture features. Because this step is performed within each homogenous region, instead of within a fixed-size image window, the obtained local texture features in the image are more accurate, which can effectively benefit the improvement of classification accuracy. In the following step, a contextual spectral-texture kernel is constructed by combining spectral information in the image and the extracted texture information using the linearity property of the kernel methods. Finally, the classification map is achieved by the support vector machines (SVM classifier using the proposed spectral-texture kernel. Experiments on two benchmark airborne hyperspectral datasets demonstrate that our method can effectively improve classification accuracies, even though only a very limited training sample is available. Specifically, our method can achieve from 8.26% to 15.1% higher in terms of overall accuracy than the traditional SVM classifier. The performance of our method was further compared to several state-of-the-art classification methods of hyperspectral images using objective quantitative measures and a visual qualitative evaluation.

  14. Methods of filtering the graph images of the functions

    Directory of Open Access Journals (Sweden)

    Олександр Григорович Бурса

    2017-06-01

    Full Text Available The theoretical aspects of cleaning raster images of scanned graphs of functions from digital, chromatic and luminance distortions by using computer graphics techniques have been considered. The basic types of distortions characteristic of graph images of functions have been stated. To suppress the distortion several methods, providing for high-quality of the resulting images and saving their topological features, were suggested. The paper describes the techniques developed and improved by the authors: the method of cleaning the image of distortions by means of iterative contrasting, based on the step-by-step increase in image contrast in the graph by 1%; the method of small entities distortion restoring, based on the thinning of the known matrix of contrast increase filter (the allowable dimensions of the nucleus dilution radius convolution matrix, which provide for the retention of the graph lines have been established; integration technique of the noise reduction method by means of contrasting and distortion restoring method of small entities with known σ-filter. Each method in the complex has been theoretically substantiated. The developed methods involve treatment of graph images as the entire image (global processing and its fragments (local processing. The metrics assessing the quality of the resulting image with the global and local processing have been chosen, the substantiation of the choice as well as the formulas have been given. The proposed complex methods of cleaning the graphs images of functions from grayscale image distortions is adaptive to the form of an image carrier, the distortion level in the image and its distribution. The presented results of testing the developed complex of methods for a representative sample of images confirm its effectiveness

  15. Validation of an improved abnormality insertion method for medical image perception investigations

    Science.gov (United States)

    Madsen, Mark T.; Durst, Gregory R.; Caldwell, Robert T.; Schartz, Kevin M.; Thompson, Brad H.; Berbaum, Kevin S.

    2009-02-01

    The ability to insert abnormalities in clinical tomographic images makes image perception studies with medical images practical. We describe a new insertion technique and its experimental validation that uses complementary image masks to select an abnormality from a library and place it at a desired location. The method was validated using a 4-alternative forced-choice experiment. For each case, four quadrants were simultaneously displayed consisting of 5 consecutive frames of a chest CT with a pulmonary nodule. One quadrant was unaltered, while the other 3 had the nodule from the unaltered quadrant artificially inserted. 26 different sets were generated and repeated with order scrambling for a total of 52 cases. The cases were viewed by radiology staff and residents who ranked each quadrant by realistic appearance. On average, the observers were able to correctly identify the unaltered quadrant in 42% of cases, and identify the unaltered quadrant both times it appeared in 25% of cases. Consensus, defined by a majority of readers, correctly identified the unaltered quadrant in only 29% of 52 cases. For repeats, the consensus observer successfully identified the unaltered quadrant only once. We conclude that the insertion method can be used to reliably place abnormalities in perception experiments.

  16. Improvement of viewing-zone angle and image quality of digital holograms

    Energy Technology Data Exchange (ETDEWEB)

    Nomura, Takanori, E-mail: nom@sys.wakayama-u.ac.j [Faculty of Systems Enigneering, Wakayama Univesity, 930 Sakaedani, Wakayama, 640-8510 (Japan)

    2010-02-01

    The method to improve of a viewing-zone angle and an image quality of a digital hologram is presented. A number of digital holograms of a central object are recorded from the position on the circumference. The holograms are used for a hologram synthesis to improve the image quality from whole viewing-zone angle. The synthesis is achieved by a correlation between a hologram and numerically propagated holograms. The large-sized synthesized digital hologram has a wide viewing-zone angle and less speckles. Some experimental results are shown to confirm the proposed method.

  17. Improvement in the independence of relaxation method-based particle tracking velocimetry

    International Nuclear Information System (INIS)

    Jia, P; Wang, Y; Zhang, Y

    2013-01-01

    New techniques are developed to improve the independence of relaxation method-based particle tracking velocimetry (RM-PTV). Firstly, Delaunay tessellation (DT) is employed to form clusters of neighboring particles with similar motion in the same frame; and then a bidirectional calculation concept is adopted to improve the way of particle pairing. These new techniques are tested with both self-defined particle images and the particle image velocimetry standard synthetic particle images. The results indicate that the DT method performs well and efficiently in determining the particle clusters, and the particle pairing process is well optimized by the bidirectional calculation concept. With these methods, three computation parameters are eliminated, which makes RM-PTV more autonomous in applications. (paper)

  18. Single image super-resolution based on compressive sensing and improved TV minimization sparse recovery

    Science.gov (United States)

    Vishnukumar, S.; Wilscy, M.

    2017-12-01

    In this paper, we propose a single image Super-Resolution (SR) method based on Compressive Sensing (CS) and Improved Total Variation (TV) Minimization Sparse Recovery. In the CS framework, low-resolution (LR) image is treated as the compressed version of high-resolution (HR) image. Dictionary Training and Sparse Recovery are the two phases of the method. K-Singular Value Decomposition (K-SVD) method is used for dictionary training and the dictionary represents HR image patches in a sparse manner. Here, only the interpolated version of the LR image is used for training purpose and thereby the structural self similarity inherent in the LR image is exploited. In the sparse recovery phase the sparse representation coefficients with respect to the trained dictionary for LR image patches are derived using Improved TV Minimization method. HR image can be reconstructed by the linear combination of the dictionary and the sparse coefficients. The experimental results show that the proposed method gives better results quantitatively as well as qualitatively on both natural and remote sensing images. The reconstructed images have better visual quality since edges and other sharp details are preserved.

  19. Improvement of sidestream dark field imaging with an image acquisition stabilizer.

    Science.gov (United States)

    Balestra, Gianmarco M; Bezemer, Rick; Boerma, E Christiaan; Yong, Ze-Yie; Sjauw, Krishan D; Engstrom, Annemarie E; Koopmans, Matty; Ince, Can

    2010-07-13

    In the present study we developed, evaluated in volunteers, and clinically validated an image acquisition stabilizer (IAS) for Sidestream Dark Field (SDF) imaging. The IAS is a stainless steel sterilizable ring which fits around the SDF probe tip. The IAS creates adhesion to the imaged tissue by application of negative pressure. The effects of the IAS on the sublingual microcirculatory flow velocities, the force required to induce pressure artifacts (PA), the time to acquire a stable image, and the duration of stable imaging were assessed in healthy volunteers. To demonstrate the clinical applicability of the SDF setup in combination with the IAS, simultaneous bilateral sublingual imaging of the microcirculation were performed during a lung recruitment maneuver (LRM) in mechanically ventilated critically ill patients. One SDF device was operated handheld; the second was fitted with the IAS and held in position by a mechanic arm. Lateral drift, number of losses of image stability and duration of stable imaging of the two methods were compared. Five healthy volunteers were studied. The IAS did not affect microcirculatory flow velocities. A significantly greater force had to applied onto the tissue to induced PA with compared to without IAS (0.25 +/- 0.15 N without vs. 0.62 +/- 0.05 N with the IAS, p IAS ensured an increased duration of a stable image sequence (8 +/- 2 s without vs. 42 +/- 8 s with the IAS, p IAS. In eight mechanically ventilated patients undergoing a LRM the use of the IAS resulted in a significantly reduced image drifting and enabled the acquisition of significantly longer stable image sequences (24 +/- 5 s without vs. 67 +/- 14 s with the IAS, p = 0.006). The present study has validated the use of an IAS for improvement of SDF imaging by demonstrating that the IAS did not affect microcirculatory perfusion in the microscopic field of view. The IAS improved both axial and lateral SDF image stability and thereby increased the critical force required

  20. Image-preprocessing method for near-wall particle image velocimetry (PIV) image interrogation with very large in-plane displacement

    International Nuclear Information System (INIS)

    Zhu, Yiding; Yuan, Huijing; Zhang, Chuanhong; Lee, Cunbiao

    2013-01-01

    Accurate particle image velocimetry (PIV) measurements very near the wall are still a great challenge. The problem is compounded by the very large in-plane displacement on PIV images commonly encountered in measurements in hypersonic boundary layers. An improved image-preprocessing method is presented in this paper which expands the traditional window deformation iterative multigrid scheme to PIV images with very large displacement. Before the interrogation, stationary artificial particles of uniform size are added homogeneously in the wall region. The mean squares of the intensities of signals in the flow and in the wall region are postulated to be equal when half the initial interrogation window overlaps the wall region. The initial estimation near the wall is then smoothed by data from both sides of the shear layer to reduce the large random uncertainties. Interrogations in the following iterative steps then converge to the correct results to provide accurate predictions for particle tracking velocimetries. Significant improvement is seen in Monte Carlo simulations and experimental tests. The algorithm successfully extracted the small flow structures of the second-mode wave in the hypersonic boundary layer from PIV images with low signal-noise-ratios when the traditional method was not successful. (paper)

  1. Reliable clarity automatic-evaluation method for optical remote sensing images

    Science.gov (United States)

    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.

  2. Improving Technology for Vascular Imaging

    Science.gov (United States)

    Rana, Raman

    Neuro-endovascular image guided interventions (Neuro-EIGIs) is a minimally invasive procedure that require micro catheters and endovascular devices be inserted into the vasculature via an incision near the femoral artery and guided under low dose fluoroscopy to the vasculature of the head and neck. However, the endovascular devices used for the purpose are of very small size (stents are of the order of 50mum to 100mum) and the success of these EIGIs depends a lot on the accurate placement of these devices. In order to accurately place these devices inside the patient, the interventionalist should be able to see them clearly. Hence, high resolution capabilities are of immense importance in neuro-EIGIs. The high-resolution detectors, MAF-CCD and MAF-CMOS, at the Toshiba Stroke and Vascular Research Center at the University at Buffalo are capable of presenting improved images for better patient care. Focal spot of an x-ray tube plays an important role in performance of these high resolution detectors. The finite size of the focal spot results into the blurriness around the edges of the image of the object resulting in reduced spatial resolution. Hence, knowledge of accurate size of the focal spot of the x-ray tube is very essential for the evaluation of the total system performance. Importance of magnification and image detector blur deconvolution was demonstrated to carry out the more accurate measurement of x-ray focal spot using a pinhole camera. A 30 micron pinhole was used to obtain the focal spot images using flat panel detector (FPD) and different source to image distances (SIDs) were used to achieve different magnifications (3.16, 2.66 and 2.16). These focal spot images were deconvolved with a 2-D modulation transfer function (MTF), obtained using noise response (NR) method, to remove the detector blur present in the images. Using these corrected images, the accurate size of all the three focal spots were obtained and it was also established that effect of

  3. The use of image morphing to improve the detection of tumors in emission imaging

    International Nuclear Information System (INIS)

    Dykstra, C.; Greer, K.; Jaszczak, R.; Celler, A.

    1999-01-01

    Two of the limitations on the utility of SPECT and planar scintigraphy for the non-invasive detection of carcinoma are the small sizes of many tumors and the possible low contrast between tumor uptake and background. This is particularly true for breast imaging. Use of some form of image processing can improve the visibility of tumors which are at the limit of hardware resolution. Smoothing, by some form of image averaging, either during or post-reconstruction, is widely used to reduce noise and thereby improve the detectability of regions of elevated activity. However, smoothing degrades resolution and, by averaging together closely spaced noise, may make noise look like a valid region of increased uptake. Image morphing by erosion and dilation does not average together image values; it instead selectively removes small features and irregularities from an image without changing the larger features. Application of morphing to emission images has shown that it does not, therefore, degrade resolution and does not always degrade contrast. For these reasons it may be a better method of image processing for noise removal in some images. In this paper the authors present a comparison of the effects of smoothing and morphing using breast and liver studies

  4. Improved quality of intrafraction kilovoltage images by triggered readout of unexposed frames

    DEFF Research Database (Denmark)

    Poulsen, Per Rugaard; Jonassen, Johnny; Schmidt, Mai Lykkegaard

    2015-01-01

    of unexposed kV frames as a means to improve the kV image quality in a series of experiments and a theoretical model of the observed image quality improvements. Methods: A series of fluoroscopic images were acquired of a solid water phantom with an embedded gold marker and an air cavity with and without...... absolute error of 2.0% for the gold marker. Conclusions: A device that triggers readout of unexposed frames during kV fluoroscopy was built and shown to greatly improve the quality of intratreatment kV images. A simple theoretical model successfully described the CNR improvements with the device.......Purpose: The gantry-mounted kilovoltage (kV) imager of modern linear accelerators can be used forreal-time tumor localization during radiation treatment delivery. However, the kV image quality often suffers from cross-scatter from the megavoltage (MV) treatment beam. This study investigates readout...

  5. Improved JEM-X imaging

    DEFF Research Database (Denmark)

    Lund, Niels; Westergaard, Niels Jørgen Stenfeldt; Chenevez, Jérôme

    2010-01-01

    A new imaging method has been developed for JEM-X. The flux from each sky pixel is obtained from a fit to the observed shadowgram rather than from a back projected image. The fitting method is more direct than the standard back projection method used in the public OSA software and allows better...

  6. 3-D image pre-processing algorithms for improved automated tracing of neuronal arbors.

    Science.gov (United States)

    Narayanaswamy, Arunachalam; Wang, Yu; Roysam, Badrinath

    2011-09-01

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

  7. Improving best-phase image quality in cardiac CT by motion correction with MAM optimization

    Energy Technology Data Exchange (ETDEWEB)

    Rohkohl, Christopher; Bruder, Herbert; Stierstorfer, Karl [Siemens AG, Healthcare Sector, Siemensstrasse 1, 91301 Forchheim (Germany); Flohr, Thomas [Siemens AG, Healthcare Sector, Siemensstrasse 1, 91301 Forchheim (Germany); Institute of Diagnostic Radiology, Eberhard Karls University, Hoppe-Seyler-Str. 3, 72076 Tuebingen (Germany)

    2013-03-15

    Purpose: Research in image reconstruction for cardiac CT aims at using motion correction algorithms to improve the image quality of the coronary arteries. The key to those algorithms is motion estimation, which is currently based on 3-D/3-D registration to align the structures of interest in images acquired in multiple heart phases. The need for an extended scan data range covering several heart phases is critical in terms of radiation dose to the patient and limits the clinical potential of the method. Furthermore, literature reports only slight quality improvements of the motion corrected images when compared to the most quiet phase (best-phase) that was actually used for motion estimation. In this paper a motion estimation algorithm is proposed which does not require an extended scan range but works with a short scan data interval, and which markedly improves the best-phase image quality. Methods: Motion estimation is based on the definition of motion artifact metrics (MAM) to quantify motion artifacts in a 3-D reconstructed image volume. The authors use two different MAMs, entropy, and positivity. By adjusting the motion field parameters, the MAM of the resulting motion-compensated reconstruction is optimized using a gradient descent procedure. In this way motion artifacts are minimized. For a fast and practical implementation, only analytical methods are used for motion estimation and compensation. Both the MAM-optimization and a 3-D/3-D registration-based motion estimation algorithm were investigated by means of a computer-simulated vessel with a cardiac motion profile. Image quality was evaluated using normalized cross-correlation (NCC) with the ground truth template and root-mean-square deviation (RMSD). Four coronary CT angiography patient cases were reconstructed to evaluate the clinical performance of the proposed method. Results: For the MAM-approach, the best-phase image quality could be improved for all investigated heart phases, with a maximum

  8. Improving best-phase image quality in cardiac CT by motion correction with MAM optimization

    International Nuclear Information System (INIS)

    Rohkohl, Christopher; Bruder, Herbert; Stierstorfer, Karl; Flohr, Thomas

    2013-01-01

    Purpose: Research in image reconstruction for cardiac CT aims at using motion correction algorithms to improve the image quality of the coronary arteries. The key to those algorithms is motion estimation, which is currently based on 3-D/3-D registration to align the structures of interest in images acquired in multiple heart phases. The need for an extended scan data range covering several heart phases is critical in terms of radiation dose to the patient and limits the clinical potential of the method. Furthermore, literature reports only slight quality improvements of the motion corrected images when compared to the most quiet phase (best-phase) that was actually used for motion estimation. In this paper a motion estimation algorithm is proposed which does not require an extended scan range but works with a short scan data interval, and which markedly improves the best-phase image quality. Methods: Motion estimation is based on the definition of motion artifact metrics (MAM) to quantify motion artifacts in a 3-D reconstructed image volume. The authors use two different MAMs, entropy, and positivity. By adjusting the motion field parameters, the MAM of the resulting motion-compensated reconstruction is optimized using a gradient descent procedure. In this way motion artifacts are minimized. For a fast and practical implementation, only analytical methods are used for motion estimation and compensation. Both the MAM-optimization and a 3-D/3-D registration-based motion estimation algorithm were investigated by means of a computer-simulated vessel with a cardiac motion profile. Image quality was evaluated using normalized cross-correlation (NCC) with the ground truth template and root-mean-square deviation (RMSD). Four coronary CT angiography patient cases were reconstructed to evaluate the clinical performance of the proposed method. Results: For the MAM-approach, the best-phase image quality could be improved for all investigated heart phases, with a maximum

  9. An improved computing method for the image edge detection

    Institute of Scientific and Technical Information of China (English)

    Gang Wang; Liang Xiao; Anzhi He

    2007-01-01

    The framework of detecting the image edge based on the sub-pixel multi-fractal measure (SPMM) is presented. The measure is defined, which gives the sub-pixel local distribution of the image gradient. The more precise singularity exponent of every pixel can be obtained by performing the SPMM analysis on the image. Using the singularity exponents and the multi-fractal spectrum of the image, the image can be segmented into a series of sets with different singularity exponents, thus the image edge can be detected automatically and easily. The simulation results show that the SPMM has higher quality factor in the image edge detection.

  10. Improving the speed of AFM by mechatronic design and modern control methods

    International Nuclear Information System (INIS)

    Schitter, Georg

    2009-01-01

    In Atomic Force Microscopy (AFM) high-performance and high-precision control of the AFM scanner and of the imaging forces is crucial. Particularly at high imaging speeds the dynamic behaviour of the scanner may cause imaging artifacts and limit the maximum imaging rate. This contribution discusses and presents recent improvements in AFM instrumentation for faster imaging by means of mechatronic design and utilizing modern control engineering methods. Combining these improvements enables AFM imaging at more than two orders of magnitudes faster than conventional AFMs. (orig.)

  11. Image Interpolation Scheme based on SVM and Improved PSO

    Science.gov (United States)

    Jia, X. F.; Zhao, B. T.; Liu, X. X.; Song, H. P.

    2018-01-01

    In order to obtain visually pleasing images, a support vector machines (SVM) based interpolation scheme is proposed, in which the improved particle swarm optimization is applied to support vector machine parameters optimization. Training samples are constructed by the pixels around the pixel to be interpolated. Then the support vector machine with optimal parameters is trained using training samples. After the training, we can get the interpolation model, which can be employed to estimate the unknown pixel. Experimental result show that the interpolated images get improvement PNSR compared with traditional interpolation methods, which is agrees with the subjective quality.

  12. Blind compressed sensing image reconstruction based on alternating direction method

    Science.gov (United States)

    Liu, Qinan; Guo, Shuxu

    2018-04-01

    In order to solve the problem of how to reconstruct the original image under the condition of unknown sparse basis, this paper proposes an image reconstruction method based on blind compressed sensing model. In this model, the image signal is regarded as the product of a sparse coefficient matrix and a dictionary matrix. Based on the existing blind compressed sensing theory, the optimal solution is solved by the alternative minimization method. The proposed method solves the problem that the sparse basis in compressed sensing is difficult to represent, which restrains the noise and improves the quality of reconstructed image. This method ensures that the blind compressed sensing theory has a unique solution and can recover the reconstructed original image signal from a complex environment with a stronger self-adaptability. The experimental results show that the image reconstruction algorithm based on blind compressed sensing proposed in this paper can recover high quality image signals under the condition of under-sampling.

  13. Improvement of image velocimetry based on a spatio-temporal correlation method; Jikukan sokan ni motozuku ryushi gazo sokudoba keisokuho no kaiseki seino kaizen

    Energy Technology Data Exchange (ETDEWEB)

    Yamada, H. [Tokuyama College of Technology, Yamaguchi (Japan); Arifuku, T. [Komatsu Ltd., Tokyo (Japan); Koga, K. [Yamaguchi University, Yamaguchi (Japan). Faculty of Engineering

    1998-05-31

    In the image velocimetry, it is generally required to detect the various velocity in each position of the flow field. But the maximum velocity which the usual velocimetry can detect has been limited in about 1 pixel per frame. Then, in order to measure the wide range of velocity vectors from the dynamic image, the improvement of performance in the image velocimetry based on a spatio-temporal correlation method would be attempted by enlarging the analytical region and by interpolating the new frame. The analytical performance of velocimetry was estimated by measuring the velocity from the flow dynamic image made artificially on the personal computer so as to simulate the flow of fluid containing a lot of small particles. As the results, the velocity range of the improved velocimetry became larger than that of the usual velocimetry. 21 refs., 13 figs., 1 tab.

  14. Improved Seam-Line Searching Algorithm for UAV Image Mosaic with Optical Flow.

    Science.gov (United States)

    Zhang, Weilong; Guo, Bingxuan; Li, Ming; Liao, Xuan; Li, Wenzhuo

    2018-04-16

    Ghosting and seams are two major challenges in creating unmanned aerial vehicle (UAV) image mosaic. In response to these problems, this paper proposes an improved method for UAV image seam-line searching. First, an image matching algorithm is used to extract and match the features of adjacent images, so that they can be transformed into the same coordinate system. Then, the gray scale difference, the gradient minimum, and the optical flow value of pixels in adjacent image overlapped area in a neighborhood are calculated, which can be applied to creating an energy function for seam-line searching. Based on that, an improved dynamic programming algorithm is proposed to search the optimal seam-lines to complete the UAV image mosaic. This algorithm adopts a more adaptive energy aggregation and traversal strategy, which can find a more ideal splicing path for adjacent UAV images and avoid the ground objects better. The experimental results show that the proposed method can effectively solve the problems of ghosting and seams in the panoramic UAV images.

  15. Improvement of Sidestream Dark Field Imaging with an Image Acquisition Stabilizer

    International Nuclear Information System (INIS)

    Balestra, Gianmarco M; Bezemer, Rick; Boerma, E Christiaan; Yong, Ze-Yie; Sjauw, Krishan D; Engstrom, Annemarie E; Koopmans, Matty; Ince, Can

    2010-01-01

    In the present study we developed, evaluated in volunteers, and clinically validated an image acquisition stabilizer (IAS) for Sidestream Dark Field (SDF) imaging. The IAS is a stainless steel sterilizable ring which fits around the SDF probe tip. The IAS creates adhesion to the imaged tissue by application of negative pressure. The effects of the IAS on the sublingual microcirculatory flow velocities, the force required to induce pressure artifacts (PA), the time to acquire a stable image, and the duration of stable imaging were assessed in healthy volunteers. To demonstrate the clinical applicability of the SDF setup in combination with the IAS, simultaneous bilateral sublingual imaging of the microcirculation were performed during a lung recruitment maneuver (LRM) in mechanically ventilated critically ill patients. One SDF device was operated handheld; the second was fitted with the IAS and held in position by a mechanic arm. Lateral drift, number of losses of image stability and duration of stable imaging of the two methods were compared. Five healthy volunteers were studied. The IAS did not affect microcirculatory flow velocities. A significantly greater force had to applied onto the tissue to induced PA with compared to without IAS (0.25 ± 0.15 N without vs. 0.62 ± 0.05 N with the IAS, p < 0.001). The IAS ensured an increased duration of a stable image sequence (8 ± 2 s without vs. 42 ± 8 s with the IAS, p < 0.001). The time required to obtain a stable image sequence was similar with and without the IAS. In eight mechanically ventilated patients undergoing a LRM the use of the IAS resulted in a significantly reduced image drifting and enabled the acquisition of significantly longer stable image sequences (24 ± 5 s without vs. 67 ± 14 s with the IAS, p = 0.006). The present study has validated the use of an IAS for improvement of SDF imaging by demonstrating that the IAS did not affect microcirculatory perfusion in the microscopic field of view. The IAS

  16. Multi-crack imaging using nonclassical nonlinear acoustic method

    Science.gov (United States)

    Zhang, Lue; Zhang, Ying; Liu, Xiao-Zhou; Gong, Xiu-Fen

    2014-10-01

    Solid materials with cracks exhibit the nonclassical nonlinear acoustical behavior. The micro-defects in solid materials can be detected by nonlinear elastic wave spectroscopy (NEWS) method with a time-reversal (TR) mirror. While defects lie in viscoelastic solid material with different distances from one another, the nonlinear and hysteretic stress—strain relation is established with Preisach—Mayergoyz (PM) model in crack zone. Pulse inversion (PI) and TR methods are used in numerical simulation and defect locations can be determined from images obtained by the maximum value. Since false-positive defects might appear and degrade the imaging when the defects are located quite closely, the maximum value imaging with a time window is introduced to analyze how defects affect each other and how the fake one occurs. Furthermore, NEWS-TR-NEWS method is put forward to improve NEWS-TR scheme, with another forward propagation (NEWS) added to the existing phases (NEWS and TR). In the added phase, scanner locations are determined by locations of all defects imaged in previous phases, so that whether an imaged defect is real can be deduced. NEWS-TR-NEWS method is proved to be effective to distinguish real defects from the false-positive ones. Moreover, it is also helpful to detect the crack that is weaker than others during imaging procedure.

  17. FFT-enhanced IHS transform method for fusing high-resolution satellite images

    Science.gov (United States)

    Ling, Y.; Ehlers, M.; Usery, E.L.; Madden, M.

    2007-01-01

    Existing image fusion techniques such as the intensity-hue-saturation (IHS) transform and principal components analysis (PCA) methods may not be optimal for fusing the new generation commercial high-resolution satellite images such as Ikonos and QuickBird. One problem is color distortion in the fused image, which causes visual changes as well as spectral differences between the original and fused images. In this paper, a fast Fourier transform (FFT)-enhanced IHS method is developed for fusing new generation high-resolution satellite images. This method combines a standard IHS transform with FFT filtering of both the panchromatic image and the intensity component of the original multispectral image. Ikonos and QuickBird data are used to assess the FFT-enhanced IHS transform method. Experimental results indicate that the FFT-enhanced IHS transform method may improve upon the standard IHS transform and the PCA methods in preserving spectral and spatial information. ?? 2006 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS).

  18. Volumetric CT-images improve testing of radiological image interpretation skills

    Energy Technology Data Exchange (ETDEWEB)

    Ravesloot, Cécile J., E-mail: C.J.Ravesloot@umcutrecht.nl [Radiology Department at University Medical Center Utrecht, Heidelberglaan 100, 3508 GA Utrecht, Room E01.132 (Netherlands); Schaaf, Marieke F. van der, E-mail: M.F.vanderSchaaf@uu.nl [Department of Pedagogical and Educational Sciences at Utrecht University, Heidelberglaan 1, 3584 CS Utrecht (Netherlands); Schaik, Jan P.J. van, E-mail: J.P.J.vanSchaik@umcutrecht.nl [Radiology Department at University Medical Center Utrecht, Heidelberglaan 100, 3508 GA Utrecht, Room E01.132 (Netherlands); Cate, Olle Th.J. ten, E-mail: T.J.tenCate@umcutrecht.nl [Center for Research and Development of Education at University Medical Center Utrecht, Heidelberglaan 100, 3508 GA Utrecht (Netherlands); Gijp, Anouk van der, E-mail: A.vanderGijp-2@umcutrecht.nl [Radiology Department at University Medical Center Utrecht, Heidelberglaan 100, 3508 GA Utrecht, Room E01.132 (Netherlands); Mol, Christian P., E-mail: C.Mol@umcutrecht.nl [Image Sciences Institute at University Medical Center Utrecht, Heidelberglaan 100, 3508 GA Utrecht (Netherlands); Vincken, Koen L., E-mail: K.Vincken@umcutrecht.nl [Image Sciences Institute at University Medical Center Utrecht, Heidelberglaan 100, 3508 GA Utrecht (Netherlands)

    2015-05-15

    Rationale and objectives: Current radiology practice increasingly involves interpretation of volumetric data sets. In contrast, most radiology tests still contain only 2D images. We introduced a new testing tool that allows for stack viewing of volumetric images in our undergraduate radiology program. We hypothesized that tests with volumetric CT-images enhance test quality, in comparison with traditional completely 2D image-based tests, because they might better reflect required skills for clinical practice. Materials and methods: Two groups of medical students (n = 139; n = 143), trained with 2D and volumetric CT-images, took a digital radiology test in two versions (A and B), each containing both 2D and volumetric CT-image questions. In a questionnaire, they were asked to comment on the representativeness for clinical practice, difficulty and user-friendliness of the test questions and testing program. Students’ test scores and reliabilities, measured with Cronbach's alpha, of 2D and volumetric CT-image tests were compared. Results: Estimated reliabilities (Cronbach's alphas) were higher for volumetric CT-image scores (version A: .51 and version B: .54), than for 2D CT-image scores (version A: .24 and version B: .37). Participants found volumetric CT-image tests more representative of clinical practice, and considered them to be less difficult than volumetric CT-image questions. However, in one version (A), volumetric CT-image scores (M 80.9, SD 14.8) were significantly lower than 2D CT-image scores (M 88.4, SD 10.4) (p < .001). The volumetric CT-image testing program was considered user-friendly. Conclusion: This study shows that volumetric image questions can be successfully integrated in students’ radiology testing. Results suggests that the inclusion of volumetric CT-images might improve the quality of radiology tests by positively impacting perceived representativeness for clinical practice and increasing reliability of the test.

  19. Development of motion image prediction method using principal component analysis

    International Nuclear Information System (INIS)

    Chhatkuli, Ritu Bhusal; Demachi, Kazuyuki; Kawai, Masaki; Sakakibara, Hiroshi; Kamiaka, Kazuma

    2012-01-01

    Respiratory motion can induce the limit in the accuracy of area irradiated during lung cancer radiation therapy. Many methods have been introduced to minimize the impact of healthy tissue irradiation due to the lung tumor motion. The purpose of this research is to develop an algorithm for the improvement of image guided radiation therapy by the prediction of motion images. We predict the motion images by using principal component analysis (PCA) and multi-channel singular spectral analysis (MSSA) method. The images/movies were successfully predicted and verified using the developed algorithm. With the proposed prediction method it is possible to forecast the tumor images over the next breathing period. The implementation of this method in real time is believed to be significant for higher level of tumor tracking including the detection of sudden abdominal changes during radiation therapy. (author)

  20. A dual-view digital tomosynthesis imaging technique for improved chest imaging

    Energy Technology Data Exchange (ETDEWEB)

    Zhong, Yuncheng; Lai, Chao-Jen; Wang, Tianpeng; Shaw, Chris C., E-mail: cshaw@mdanderson.org [Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77054 (United States)

    2015-09-15

    Purpose: Digital tomosynthesis (DTS) has been shown to be useful for reducing the overlapping of abnormalities with anatomical structures at various depth levels along the posterior–anterior (PA) direction in chest radiography. However, DTS provides crude three-dimensional (3D) images that have poor resolution in the lateral view and can only be displayed with reasonable quality in the PA view. Furthermore, the spillover of high-contrast objects from off-fulcrum planes generates artifacts that may impede the diagnostic use of the DTS images. In this paper, the authors describe and demonstrate the use of a dual-view DTS technique to improve the accuracy of the reconstructed volume image data for more accurate rendition of the anatomy and slice images with improved resolution and reduced artifacts, thus allowing the 3D image data to be viewed in views other than the PA view. Methods: With the dual-view DTS technique, limited angle scans are performed and projection images are acquired in two orthogonal views: PA and lateral. The dual-view projection data are used together to reconstruct 3D images using the maximum likelihood expectation maximization iterative algorithm. In this study, projection images were simulated or experimentally acquired over 360° using the scanning geometry for cone beam computed tomography (CBCT). While all projections were used to reconstruct CBCT images, selected projections were extracted and used to reconstruct single- and dual-view DTS images for comparison with the CBCT images. For realistic demonstration and comparison, a digital chest phantom derived from clinical CT images was used for the simulation study. An anthropomorphic chest phantom was imaged for the experimental study. The resultant dual-view DTS images were visually compared with the single-view DTS images and CBCT images for the presence of image artifacts and accuracy of CT numbers and anatomy and quantitatively compared with root-mean-square-deviation (RMSD) values

  1. Medical image segmentation using improved FCM

    Institute of Scientific and Technical Information of China (English)

    ZHANG XiaoFeng; ZHANG CaiMing; TANG WenJing; WEI ZhenWen

    2012-01-01

    Image segmentation is one of the most important problems in medical image processing,and the existence of partial volume effect and other phenomena makes the problem much more complex. Fuzzy Cmeans,as an effective tool to deal with PVE,however,is faced with great challenges in efficiency.Aiming at this,this paper proposes one improved FCM algorithm based on the histogram of the given image,which will be denoted as HisFCM and divided into two phases.The first phase will retrieve several intervals on which to compute cluster centroids,and the second one will perform image segmentation based on improved FCM algorithm.Compared with FCM and other improved algorithms,HisFCM is of much higher efficiency with satisfying results.Experiments on medical images show that HisFCM can achieve good segmentation results in less than 0.1 second,and can satisfy real-time requirements of medical image processing.

  2. Improvement on image quality of single photon ECT with converging collimator system

    International Nuclear Information System (INIS)

    Murayama, Hideo; Nohara, Norimasa; Tanaka, Eiichi

    1986-01-01

    Single photon emission computed tomography (SPECT) with converging collimator system was proposed to improve quality of reconstructed images. The collimator system was designed to enhance sensitivity at the center region of field-of-view, where the probability photons escape the attenuating medium is smaller than at the off-center region. In order to evaluate efficiency of the improvement on image quality, the weighting function of projection, which is defined as relative sensitivity to the average on the lateral sampling of projection, was adopted to the image reconstruction algorithm of Radial Post Correction method. Statistical mean square noise in a reconstructed image was formulated in this method. Simulation studies using typical weighting function showed that center-enhanced weighting function brings effective improvement on image quality, especially, at the center region of cold area surrounded by annularly distributed activity. A new SPECT system was proposed as one example of the converging collimator systems. The system is composed of four gamma cameras with four fan-beam collimators, which have different focal distances one another. Simple simulation studies showed that the proposed system has reasonable center-enhanced weighting function, and the image quality based on the proposed system was fairly improved as compared with one based on uniform weighting function at the center region of the field-of-view. (author)

  3. Rice pads. Devices to improve the effect of fat suppression of CHESS images

    International Nuclear Information System (INIS)

    Moriya, Susumu; Yokobayashi, Tsuneo; Miki, Yukio

    2013-01-01

    The chemical shift selective (CHESS) method is often used for fat suppression in magnetic resonance imaging. CHESS has several advantages, including versatility, quick imaging, and applicability to contrast examinations. One disadvantage of CHESS is the lingering fat signal generated as a result of nonuniformity of the static magnetic field. To overcome this drawback, some researchers have used pads made with polished rice (rice pads), a simple method in which rice pads are placed outside the area to be imaged. We describe ways to improve CHESS images, characteristics of the rice pad, its application to imaging, and methods of placing the pad. (author)

  4. Double Minimum Variance Beamforming Method to Enhance Photoacoustic Imaging

    OpenAIRE

    Paridar, Roya; Mozaffarzadeh, Moein; Nasiriavanaki, Mohammadreza; Orooji, Mahdi

    2018-01-01

    One of the common algorithms used to reconstruct photoacoustic (PA) images is the non-adaptive Delay-and-Sum (DAS) beamformer. However, the quality of the reconstructed PA images obtained by DAS is not satisfying due to its high level of sidelobes and wide mainlobe. In contrast, adaptive beamformers, such as minimum variance (MV), result in an improved image compared to DAS. In this paper, a novel beamforming method, called Double MV (D-MV) is proposed to enhance the image quality compared to...

  5. Medical Imaging Image Quality Assessment with Monte Carlo Methods

    International Nuclear Information System (INIS)

    Michail, C M; Fountos, G P; Kalyvas, N I; Valais, I G; Kandarakis, I S; Karpetas, G E; Martini, Niki; Koukou, Vaia

    2015-01-01

    The aim of the present study was to assess image quality of PET scanners through a thin layer chromatography (TLC) plane source. The source was simulated using a previously validated Monte Carlo model. The model was developed by using the GATE MC package and reconstructed images obtained with the STIR software for tomographic image reconstruction, with cluster computing. The PET scanner simulated in this study was the GE DiscoveryST. A plane source consisted of a TLC plate, was simulated by a layer of silica gel on aluminum (Al) foil substrates, immersed in 18F-FDG bath solution (1MBq). Image quality was assessed in terms of the Modulation Transfer Function (MTF). MTF curves were estimated from transverse reconstructed images of the plane source. Images were reconstructed by the maximum likelihood estimation (MLE)-OSMAPOSL algorithm. OSMAPOSL reconstruction was assessed by using various subsets (3 to 21) and iterations (1 to 20), as well as by using various beta (hyper) parameter values. MTF values were found to increase up to the 12th iteration whereas remain almost constant thereafter. MTF improves by using lower beta values. The simulated PET evaluation method based on the TLC plane source can be also useful in research for the further development of PET and SPECT scanners though GATE simulations. (paper)

  6. Domain decomposition methods for solving an image problem

    Energy Technology Data Exchange (ETDEWEB)

    Tsui, W.K.; Tong, C.S. [Hong Kong Baptist College (Hong Kong)

    1994-12-31

    The domain decomposition method is a technique to break up a problem so that ensuing sub-problems can be solved on a parallel computer. In order to improve the convergence rate of the capacitance systems, pre-conditioned conjugate gradient methods are commonly used. In the last decade, most of the efficient preconditioners are based on elliptic partial differential equations which are particularly useful for solving elliptic partial differential equations. In this paper, the authors apply the so called covering preconditioner, which is based on the information of the operator under investigation. Therefore, it is good for various kinds of applications, specifically, they shall apply the preconditioned domain decomposition method for solving an image restoration problem. The image restoration problem is to extract an original image which has been degraded by a known convolution process and additive Gaussian noise.

  7. Application of Improved Wavelet Thresholding Function in Image Denoising Processing

    Directory of Open Access Journals (Sweden)

    Hong Qi Zhang

    2014-07-01

    Full Text Available Wavelet analysis is a time – frequency analysis method, time-frequency localization problems are well solved, this paper analyzes the basic principles of the wavelet transform and the relationship between the signal singularity Lipschitz exponent and the local maxima of the wavelet transform coefficients mold, the principles of wavelet transform in image denoising are analyzed, the disadvantages of traditional wavelet thresholding function are studied, wavelet threshold function, the discontinuity of hard threshold and constant deviation of soft threshold are improved, image is denoised through using the improved threshold function.

  8. Selecting optimal monochromatic level with spectral CT imaging for improving imaging quality in hepatic venography

    International Nuclear Information System (INIS)

    Sun Jun; Luo Xianfu; Wang Shou'an; Wang Jun; Sun Jiquan; Wang Zhijun; Wu Jingtao

    2013-01-01

    Objective: To investigate the effect of spectral CT monochromatic images for improving imaging quality in hepatic venography. Methods: Thirty patients underwent spectral CT examination on a GE Discovery CT 750 HD scanner. During portal phase, 1.25 mm slice thickness polychromatic images and optimal monochromatic images were obtained, and volume rendering and maximum intensity projection were created to show the hepatic veins respectively. The overall imaging quality was evaluated on a five-point scale by two radiologists. Inter-observer agreement in subjective image quality grading was assessed by Kappa statistics. Paired-sample t test were used to compare hepatic vein attenuation, hepatic parenchyma attenuation, CT value difference between the hepatic vein and the liver parenchyma, image noise, vein-to-liver contrast-to-noise ratio (CNR), the image quality score of hepatic venography between the two image data sets. Results: The monochromatic images at 50 keV were found to demonstrate the best CNR for hepatic vein.The hepatic vein attenuation [(329 ± 47) HU], hepatic parenchyma attenuation [(178 ± 33) HU], CT value difference between the hepatic vein and the liver parenchyma [(151 ± 33) HU], image noise (17.33 ± 4.18), CNR (9.13 ± 2.65), the image quality score (4.2 ± 0.6) of optimal monochromatic images were significantly higher than those of polychromatic images [(149 ± 18) HU], [(107 ± 14) HU], [(43 ±11) HU], 12.55 ± 3.02, 3.53 ± 1.03, 3.1 ± 0.8 (t values were 24.79, 13.95, 18.85, 9.07, 13.25 and 12.04, respectively, P < 0.01). In the comparison of image quality, Kappa value was 0.81 with optimal monochromatic images and 0.69 with polychromatic images. Conclusion: Monochromatic images of spectral CT could improve CNR for displaying hepatic vein and improve the image quality compared to the conventional polychromatic images. (authors)

  9. A Local Region of Interest Imaging Method for Electrical Impedance Tomography with Internal Electrodes

    Directory of Open Access Journals (Sweden)

    Hyeuknam Kwon

    2013-01-01

    Full Text Available Electrical Impedance Tomography (EIT is a very attractive functional imaging method despite the low sensitivity and resolution. The use of internal electrodes with the conventional reconstruction algorithms was not enough to enhance image resolution and accuracy in the region of interest (ROI. We propose a local ROI imaging method with internal electrodes developed from careful analysis of the sensitivity matrix that is designed to reduce the sensitivity of the voxels outside the local region and optimize the sensitivity of the voxel inside the local region. We perform numerical simulations and physical measurements to demonstrate the localized EIT imaging method. In preliminary results with multiple objects we show the benefits of using an internal electrode and the improved resolution due to the local ROI image reconstruction method. The sensitivity is further increased by allowing the surface electrodes to be unevenly spaced with a higher density of surface electrodes near the ROI. Also, we analyse how much the image quality is improved using several performance parameters for comparison. While these have not yet been studied in depth, it convincingly shows an improvement in local sensitivity in images obtained with an internal electrode in comparison to a standard reconstruction method.

  10. An Improved Unmixing-Based Fusion Method: Potential Application to Remote Monitoring of Inland Waters

    Directory of Open Access Journals (Sweden)

    Yulong Guo

    2015-02-01

    Full Text Available Although remote sensing technology has been widely used to monitor inland water bodies; the lack of suitable data with high spatial and spectral resolution has severely obstructed its practical development. The objective of this study is to improve the unmixing-based fusion (UBF method to produce fused images that maintain both spectral and spatial information from the original images. Images from Environmental Satellite 1 (HJ1 and Medium Resolution Imaging Spectrometer (MERIS were used in this study to validate the method. An improved UBF (IUBF algorithm is established by selecting a proper HJ1-CCD image band for each MERIS band and thereafter applying an unsupervised classification method in each sliding window. Viewing in the visual sense—the radiance and the spectrum—the results show that the improved method effectively yields images with the spatial resolution of the HJ1-CCD image and the spectrum resolution of the MERIS image. When validated using two datasets; the ERGAS index (Relative Dimensionless Global Error indicates that IUBF is more robust than UBF. Finally, the fused data were applied to evaluate the chlorophyll a concentrations (Cchla in Taihu Lake. The result shows that the Cchla map obtained by IUBF fusion captures more detailed information than that of MERIS.

  11. A proposed assessment method for image of regional educational institutions

    Directory of Open Access Journals (Sweden)

    Kataeva Natalya

    2017-01-01

    Full Text Available Market of educational services in the current Russian economic conditions is a complex of a huge variety of educational institutions. Market of educational services is already experiencing a significant influence of the demographic situation in Russia. This means that higher education institutions are forced to fight in a tough competition for high school students. Increased competition in the educational market forces universities to find new methods of non-price competition in attraction of potential students and throughout own educational and economic activities. Commercialization of education places universities in a single plane with commercial companies who study a positive perception of the image and reputation as a competitive advantage, which is quite acceptable for use in strategic and current activities of higher education institutions to ensure the competitiveness of educational services and educational institution in whole. Nevertheless, due to lack of evidence-based proposals in this area there is a need for scientific research in terms of justification of organizational and methodological aspects of image use as a factor in the competitiveness of the higher education institution. Theoretically and practically there are different methods and ways of evaluating the company’s image. The article provides a comparative assessment of the existing valuation methods of corporate image and the author’s method of estimating the image of higher education institutions based on the key influencing factors. The method has been tested on the Vyatka State Agricultural Academy (Russia. The results also indicate the strengths and weaknesses of the institution, highlights ways of improving, and adjusts the efforts for image improvement.

  12. On the pinned field image binarization for signature generation in image ownership verification method

    Directory of Open Access Journals (Sweden)

    Chang Hsuan

    2011-01-01

    Full Text Available Abstract The issue of pinned field image binarization for signature generation in the ownership verification of the protected image is investigated. The pinned field explores the texture information of the protected image and can be employed to enhance the watermark robustness. In the proposed method, four optimization schemes are utilized to determine the threshold values for transforming the pinned field into a binary feature image, which is then utilized to generate an effective signature image. Experimental results show that the utilization of optimization schemes can significantly improve the signature robustness from the previous method (Lee and Chang, Opt. Eng. 49 (9, 097005, 2010. While considering both the watermark retrieval rate and the computation speed, the genetic algorithm is strongly recommended. In addition, compared with Chang and Lin's scheme (J. Syst. Softw. 81 (7, 1118-1129, 2008, the proposed scheme also has better performance.

  13. Research on interpolation methods in medical image processing.

    Science.gov (United States)

    Pan, Mei-Sen; Yang, Xiao-Li; Tang, Jing-Tian

    2012-04-01

    Image interpolation is widely used for the field of medical image processing. In this paper, interpolation methods are divided into three groups: filter interpolation, ordinary interpolation and general partial volume interpolation. Some commonly-used filter methods for image interpolation are pioneered, but the interpolation effects need to be further improved. When analyzing and discussing ordinary interpolation, many asymmetrical kernel interpolation methods are proposed. Compared with symmetrical kernel ones, the former are have some advantages. After analyzing the partial volume and generalized partial volume estimation interpolations, the new concept and constraint conditions of the general partial volume interpolation are defined, and several new partial volume interpolation functions are derived. By performing the experiments of image scaling, rotation and self-registration, the interpolation methods mentioned in this paper are compared in the entropy, peak signal-to-noise ratio, cross entropy, normalized cross-correlation coefficient and running time. Among the filter interpolation methods, the median and B-spline filter interpolations have a relatively better interpolating performance. Among the ordinary interpolation methods, on the whole, the symmetrical cubic kernel interpolations demonstrate a strong advantage, especially the symmetrical cubic B-spline interpolation. However, we have to mention that they are very time-consuming and have lower time efficiency. As for the general partial volume interpolation methods, from the total error of image self-registration, the symmetrical interpolations provide certain superiority; but considering the processing efficiency, the asymmetrical interpolations are better.

  14. Review methods for image segmentation from computed tomography images

    International Nuclear Information System (INIS)

    Mamat, Nurwahidah; Rahman, Wan Eny Zarina Wan Abdul; Soh, Shaharuddin Cik; Mahmud, Rozi

    2014-01-01

    Image segmentation is a challenging process in order to get the accuracy of segmentation, automation and robustness especially in medical images. There exist many segmentation methods that can be implemented to medical images but not all methods are suitable. For the medical purposes, the aims of image segmentation are to study the anatomical structure, identify the region of interest, measure tissue volume to measure growth of tumor and help in treatment planning prior to radiation therapy. In this paper, we present a review method for segmentation purposes using Computed Tomography (CT) images. CT images has their own characteristics that affect the ability to visualize anatomic structures and pathologic features such as blurring of the image and visual noise. The details about the methods, the goodness and the problem incurred in the methods will be defined and explained. It is necessary to know the suitable segmentation method in order to get accurate segmentation. This paper can be a guide to researcher to choose the suitable segmentation method especially in segmenting the images from CT scan

  15. Multi-crack imaging using nonclassical nonlinear acoustic method

    International Nuclear Information System (INIS)

    Zhang Lue; Zhang Ying; Liu Xiao-Zhou; Gong Xiu-Fen

    2014-01-01

    Solid materials with cracks exhibit the nonclassical nonlinear acoustical behavior. The micro-defects in solid materials can be detected by nonlinear elastic wave spectroscopy (NEWS) method with a time-reversal (TR) mirror. While defects lie in viscoelastic solid material with different distances from one another, the nonlinear and hysteretic stress—strain relation is established with Preisach—Mayergoyz (PM) model in crack zone. Pulse inversion (PI) and TR methods are used in numerical simulation and defect locations can be determined from images obtained by the maximum value. Since false-positive defects might appear and degrade the imaging when the defects are located quite closely, the maximum value imaging with a time window is introduced to analyze how defects affect each other and how the fake one occurs. Furthermore, NEWS-TR-NEWS method is put forward to improve NEWS-TR scheme, with another forward propagation (NEWS) added to the existing phases (NEWS and TR). In the added phase, scanner locations are determined by locations of all defects imaged in previous phases, so that whether an imaged defect is real can be deduced. NEWS-TR-NEWS method is proved to be effective to distinguish real defects from the false-positive ones. Moreover, it is also helpful to detect the crack that is weaker than others during imaging procedure. (electromagnetism, optics, acoustics, heat transfer, classical mechanics, and fluid dynamics)

  16. Studying depression using imaging and machine learning methods.

    Science.gov (United States)

    Patel, Meenal J; Khalaf, Alexander; Aizenstein, Howard J

    2016-01-01

    Depression is a complex clinical entity that can pose challenges for clinicians regarding both accurate diagnosis and effective timely treatment. These challenges have prompted the development of multiple machine learning methods to help improve the management of this disease. These methods utilize anatomical and physiological data acquired from neuroimaging to create models that can identify depressed patients vs. non-depressed patients and predict treatment outcomes. This article (1) presents a background on depression, imaging, and machine learning methodologies; (2) reviews methodologies of past studies that have used imaging and machine learning to study depression; and (3) suggests directions for future depression-related studies.

  17. Improving performance of wavelet-based image denoising algorithm using complex diffusion process

    DEFF Research Database (Denmark)

    Nadernejad, Ehsan; Sharifzadeh, Sara; Korhonen, Jari

    2012-01-01

    using a variety of standard images and its performance has been compared against several de-noising algorithms known from the prior art. Experimental results show that the proposed algorithm preserves the edges better and in most cases, improves the measured visual quality of the denoised images......Image enhancement and de-noising is an essential pre-processing step in many image processing algorithms. In any image de-noising algorithm, the main concern is to keep the interesting structures of the image. Such interesting structures often correspond to the discontinuities (edges...... in comparison to the existing methods known from the literature. The improvement is obtained without excessive computational cost, and the algorithm works well on a wide range of different types of noise....

  18. Sonar Image Enhancements for Improved Detection of Sea Mines

    DEFF Research Database (Denmark)

    Jespersen, Karl; Sørensen, Helge Bjarup Dissing; Zerr, Benoit

    1999-01-01

    In this paper, five methods for enhancing sonar images prior to automatic detection of sea mines are investigated. Two of the methods have previously been published in connection with detection systems and serve as reference. The three new enhancement approaches are variance stabilizing log...... transform, nonlinear filtering, and pixel averaging for speckle reduction. The effect of the enhancement step is tested by using the full prcessing chain i.e. enhancement, detection and thresholding to determine the number of detections and false alarms. Substituting different enhancement algorithms...... in the processing chain gives a precise measure of the performance of the enhancement stage. The test is performed using a sonar image database with images ranging from very simple to very complex. The result of the comparison indicates that the new enhancement approaches improve the detection performance....

  19. Medical Image Visual Appearance Improvement Using Bihistogram Bezier Curve Contrast Enhancement: Data from the Osteoarthritis Initiative

    Science.gov (United States)

    Gan, Hong-Seng; Swee, Tan Tian; Abdul Karim, Ahmad Helmy; Sayuti, Khairil Amir; Abdul Kadir, Mohammed Rafiq; Tham, Weng-Kit; Wong, Liang-Xuan; Chaudhary, Kashif T.; Yupapin, Preecha P.

    2014-01-01

    Well-defined image can assist user to identify region of interest during segmentation. However, complex medical image is usually characterized by poor tissue contrast and low background luminance. The contrast improvement can lift image visual quality, but the fundamental contrast enhancement methods often overlook the sudden jump problem. In this work, the proposed bihistogram Bezier curve contrast enhancement introduces the concept of “adequate contrast enhancement” to overcome sudden jump problem in knee magnetic resonance image. Since every image produces its own intensity distribution, the adequate contrast enhancement checks on the image's maximum intensity distortion and uses intensity discrepancy reduction to generate Bezier transform curve. The proposed method improves tissue contrast and preserves pertinent knee features without compromising natural image appearance. Besides, statistical results from Fisher's Least Significant Difference test and the Duncan test have consistently indicated that the proposed method outperforms fundamental contrast enhancement methods to exalt image visual quality. As the study is limited to relatively small image database, future works will include a larger dataset with osteoarthritic images to assess the clinical effectiveness of the proposed method to facilitate the image inspection. PMID:24977191

  20. SAR Data Fusion Imaging Method Oriented to Target Feature Extraction

    Directory of Open Access Journals (Sweden)

    Yang Wei

    2015-02-01

    Full Text Available To deal with the difficulty for target outlines extracting precisely due to neglect of target scattering characteristic variation during the processing of high-resolution space-borne SAR data, a novel fusion imaging method is proposed oriented to target feature extraction. Firstly, several important aspects that affect target feature extraction and SAR image quality are analyzed, including curved orbit, stop-and-go approximation, atmospheric delay, and high-order residual phase error. Furthermore, the corresponding compensation methods are addressed as well. Based on the analysis, the mathematical model of SAR echo combined with target space-time spectrum is established for explaining the space-time-frequency change rule of target scattering characteristic. Moreover, a fusion imaging strategy and method under high-resolution and ultra-large observation angle range conditions are put forward to improve SAR quality by fusion processing in range-doppler and image domain. Finally, simulations based on typical military targets are used to verify the effectiveness of the fusion imaging method.

  1. Improvements in SPECT technology for cerebral imaging

    International Nuclear Information System (INIS)

    Esser, P.D.

    1985-01-01

    Advancement in three major areas of SPECT (single photon emission computed tomography) technology have resulted in improved image quality for cerebral studies. In the first area, single-crystal camera electronics, extensive use of microprocessors, custom digital circuitry, an data bus architecture have allowed precise external control of all gantry motions and improved signal processing. The new digital circuitry permits energy, uniformity, and linearity corrections to be an integral part of the processing electronics. Calibration of these correlations is controlled by algorithms stored in the camera's memory. The second area of improved SPECT technology is camera collimation and related imaging techniques. In this area, system resolution has been improved without loss of sensitivity by decreasing the air gap between patient and collimator surface. Since cerebral studies characteristically image high-contrast regions less than 1 cm in size, image quality has been improved by increasing collimator resolution even at the expense of sensitivity. Increased resolution also improved image contrast for studies using 123 I-labeled pharmaceuticals with 3% to 4% 124 I contamination. 65 references

  2. IMPROVED ESTIMATION OF FIBER LENGTH FROM 3-DIMENSIONAL IMAGES

    Directory of Open Access Journals (Sweden)

    Joachim Ohser

    2013-03-01

    Full Text Available A new method is presented for estimating the specific fiber length from 3D images of macroscopically homogeneous fiber systems. The method is based on a discrete version of the Crofton formula, where local knowledge from 3x3x3-pixel configurations of the image data is exploited. It is shown that the relative error resulting from the discretization of the outer integral of the Crofton formula amonts at most 1.2%. An algorithmic implementation of the method is simple and the runtime as well as the amount of memory space are low. The estimation is significantly improved by considering 3x3x3-pixel configurations instead of 2x2x2, as already studied in literature.

  3. A method of fast mosaic for massive UAV images

    Science.gov (United States)

    Xiang, Ren; Sun, Min; Jiang, Cheng; Liu, Lei; Zheng, Hui; Li, Xiaodong

    2014-11-01

    With the development of UAV technology, UAVs are used widely in multiple fields such as agriculture, forest protection, mineral exploration, natural disaster management and surveillances of public security events. In contrast of traditional manned aerial remote sensing platforms, UAVs are cheaper and more flexible to use. So users can obtain massive image data with UAVs, but this requires a lot of time to process the image data, for example, Pix4UAV need approximately 10 hours to process 1000 images in a high performance PC. But disaster management and many other fields require quick respond which is hard to realize with massive image data. Aiming at improving the disadvantage of high time consumption and manual interaction, in this article a solution of fast UAV image stitching is raised. GPS and POS data are used to pre-process the original images from UAV, belts and relation between belts and images are recognized automatically by the program, in the same time useless images are picked out. This can boost the progress of finding match points between images. Levenberg-Marquard algorithm is improved so that parallel computing can be applied to shorten the time of global optimization notably. Besides traditional mosaic result, it can also generate superoverlay result for Google Earth, which can provide a fast and easy way to show the result data. In order to verify the feasibility of this method, a fast mosaic system of massive UAV images is developed, which is fully automated and no manual interaction is needed after original images and GPS data are provided. A test using 800 images of Kelan River in Xinjiang Province shows that this system can reduce 35%-50% time consumption in contrast of traditional methods, and increases respond speed of UAV image processing rapidly.

  4. Medical Image Visual Appearance Improvement Using Bihistogram Bezier Curve Contrast Enhancement: Data from the Osteoarthritis Initiative

    Directory of Open Access Journals (Sweden)

    Hong-Seng Gan

    2014-01-01

    Full Text Available Well-defined image can assist user to identify region of interest during segmentation. However, complex medical image is usually characterized by poor tissue contrast and low background luminance. The contrast improvement can lift image visual quality, but the fundamental contrast enhancement methods often overlook the sudden jump problem. In this work, the proposed bihistogram Bezier curve contrast enhancement introduces the concept of “adequate contrast enhancement” to overcome sudden jump problem in knee magnetic resonance image. Since every image produces its own intensity distribution, the adequate contrast enhancement checks on the image’s maximum intensity distortion and uses intensity discrepancy reduction to generate Bezier transform curve. The proposed method improves tissue contrast and preserves pertinent knee features without compromising natural image appearance. Besides, statistical results from Fisher’s Least Significant Difference test and the Duncan test have consistently indicated that the proposed method outperforms fundamental contrast enhancement methods to exalt image visual quality. As the study is limited to relatively small image database, future works will include a larger dataset with osteoarthritic images to assess the clinical effectiveness of the proposed method to facilitate the image inspection.

  5. An object-oriented classification method of high resolution imagery based on improved AdaTree

    International Nuclear Information System (INIS)

    Xiaohe, Zhang; Liang, Zhai; Jixian, Zhang; Huiyong, Sang

    2014-01-01

    With the popularity of the application using high spatial resolution remote sensing image, more and more studies paid attention to object-oriented classification on image segmentation as well as automatic classification after image segmentation. This paper proposed a fast method of object-oriented automatic classification. First, edge-based or FNEA-based segmentation was used to identify image objects and the values of most suitable attributes of image objects for classification were calculated. Then a certain number of samples from the image objects were selected as training data for improved AdaTree algorithm to get classification rules. Finally, the image objects could be classified easily using these rules. In the AdaTree, we mainly modified the final hypothesis to get classification rules. In the experiment with WorldView2 image, the result of the method based on AdaTree showed obvious accuracy and efficient improvement compared with the method based on SVM with the kappa coefficient achieving 0.9242

  6. COMPARISON OF IMAGE ENHANCEMENT METHODS FOR CHROMOSOME KARYOTYPE IMAGE ENHANCEMENT

    Directory of Open Access Journals (Sweden)

    Dewa Made Sri Arsa

    2017-02-01

    Full Text Available The chromosome is a set of DNA structure that carry information about our life. The information can be obtained through Karyotyping. The process requires a clear image so the chromosome can be evaluate well. Preprocessing have to be done on chromosome images that is image enhancement. The process starts with image background removing. The image will be cleaned background color. The next step is image enhancement. This paper compares several methods for image enhancement. We evaluate some method in image enhancement like Histogram Equalization (HE, Contrast-limiting Adaptive Histogram Equalization (CLAHE, Histogram Equalization with 3D Block Matching (HE+BM3D, and basic image enhancement, unsharp masking. We examine and discuss the best method for enhancing chromosome image. Therefore, to evaluate the methods, the original image was manipulated by the addition of some noise and blur. Peak Signal-to-noise Ratio (PSNR and Structural Similarity Index (SSIM are used to examine method performance. The output of enhancement method will be compared with result of Professional software for karyotyping analysis named Ikaros MetasystemT M . Based on experimental results, HE+BM3D method gets a stable result on both scenario noised and blur image.

  7. Improving treatment planning accuracy through multimodality imaging

    International Nuclear Information System (INIS)

    Sailer, Scott L.; Rosenman, Julian G.; Soltys, Mitchel; Cullip, Tim J.; Chen, Jun

    1996-01-01

    Purpose: In clinical practice, physicians are constantly comparing multiple images taken at various times during the patient's treatment course. One goal of such a comparison is to accurately define the gross tumor volume (GTV). The introduction of three-dimensional treatment planning has greatly enhanced the ability to define the GTV, but there are times when the GTV is not visible on the treatment-planning computed tomography (CT) scan. We have modified our treatment-planning software to allow for interactive display of multiple, registered images that enhance the physician's ability to accurately determine the GTV. Methods and Materials: Images are registered using interactive tools developed at the University of North Carolina at Chapel Hill (UNC). Automated methods are also available. Images registered with the treatment-planning CT scan are digitized from film. After a physician has approved the registration, the registered images are made available to the treatment-planning software. Structures and volumes of interest are contoured on all images. In the beam's eye view, wire loop representations of these structures can be visualized from all image types simultaneously. Each registered image can be seamlessly viewed during the treatment-planning process, and all contours from all image types can be seen on any registered image. A beam may, therefore, be designed based on any contour. Results: Nineteen patients have been planned and treated using multimodality imaging from November 1993 through August 1994. All registered images were digitized from film, and many were from outside institutions. Brain has been the most common site (12), but the techniques of registration and image display have also been used for the thorax (4), abdomen (2), and extremity (1). The registered image has been an magnetic resonance (MR) scan in 15 cases and a diagnostic CT scan in 5 cases. In one case, sequential MRs, one before treatment and another after 30 Gy, were used to plan

  8. Snake Model Based on Improved Genetic Algorithm in Fingerprint Image Segmentation

    Directory of Open Access Journals (Sweden)

    Mingying Zhang

    2016-12-01

    Full Text Available Automatic fingerprint identification technology is a quite mature research field in biometric identification technology. As the preprocessing step in fingerprint identification, fingerprint segmentation can improve the accuracy of fingerprint feature extraction, and also reduce the time of fingerprint preprocessing, which has a great significance in improving the performance of the whole system. Based on the analysis of the commonly used methods of fingerprint segmentation, the existing segmentation algorithm is improved in this paper. The snake model is used to segment the fingerprint image. Additionally, it is improved by using the global optimization of the improved genetic algorithm. Experimental results show that the algorithm has obvious advantages both in the speed of image segmentation and in the segmentation effect.

  9. Systems and methods for imaging using radiation from laser produced plasmas

    Science.gov (United States)

    Renard-Le Galloudec, Nathalie; Cowan, Thomas E.; Sentoku, Yasuhiko; Rassuchine, Jennifer

    2009-06-30

    In particular embodiments, the present disclosure provides systems and methods for imaging a subject using radiation emitted from a laser produced plasma generating by irradiating a target with a laser. In particular examples, the target includes at least one radiation enhancing component, such as a fluor, cap, or wire. In further examples, the target has a metal layer and an internal surface defining an internal apex, the internal apex of less than about 15 .mu.m, such as less than about 1 .mu.m. The targets may take a variety of shapes, including cones, pyramids, and hemispheres. Certain aspects of the present disclosure provide improved imaging of a subject, such as improved medical images of a radiation dose than typical conventional methods and systems.

  10. Moving object detection in top-view aerial videos improved by image stacking

    Science.gov (United States)

    Teutsch, Michael; Krüger, Wolfgang; Beyerer, Jürgen

    2017-08-01

    Image stacking is a well-known method that is used to improve the quality of images in video data. A set of consecutive images is aligned by applying image registration and warping. In the resulting image stack, each pixel has redundant information about its intensity value. This redundant information can be used to suppress image noise, resharpen blurry images, or even enhance the spatial image resolution as done in super-resolution. Small moving objects in the videos usually get blurred or distorted by image stacking and thus need to be handled explicitly. We use image stacking in an innovative way: image registration is applied to small moving objects only, and image warping blurs the stationary background that surrounds the moving objects. Our video data are coming from a small fixed-wing unmanned aerial vehicle (UAV) that acquires top-view gray-value images of urban scenes. Moving objects are mainly cars but also other vehicles such as motorcycles. The resulting images, after applying our proposed image stacking approach, are used to improve baseline algorithms for vehicle detection and segmentation. We improve precision and recall by up to 0.011, which corresponds to a reduction of the number of false positive and false negative detections by more than 3 per second. Furthermore, we show how our proposed image stacking approach can be implemented efficiently.

  11. Multi-example feature-constrained back-projection method for image super-resolution

    Institute of Scientific and Technical Information of China (English)

    Junlei Zhang; Dianguang Gai; Xin Zhang; Xuemei Li

    2017-01-01

    Example-based super-resolution algorithms,which predict unknown high-resolution image information using a relationship model learnt from known high- and low-resolution image pairs, have attracted considerable interest in the field of image processing. In this paper, we propose a multi-example feature-constrained back-projection method for image super-resolution. Firstly, we take advantage of a feature-constrained polynomial interpolation method to enlarge the low-resolution image. Next, we consider low-frequency images of different resolutions to provide an example pair. Then, we use adaptive k NN search to find similar patches in the low-resolution image for every image patch in the high-resolution low-frequency image, leading to a regression model between similar patches to be learnt. The learnt model is applied to the low-resolution high-frequency image to produce high-resolution high-frequency information. An iterative back-projection algorithm is used as the final step to determine the final high-resolution image.Experimental results demonstrate that our method improves the visual quality of the high-resolution image.

  12. Optoelectronic imaging of speckle using image processing method

    Science.gov (United States)

    Wang, Jinjiang; Wang, Pengfei

    2018-01-01

    A detailed image processing of laser speckle interferometry is proposed as an example for the course of postgraduate student. Several image processing methods were used together for dealing with optoelectronic imaging system, such as the partial differential equations (PDEs) are used to reduce the effect of noise, the thresholding segmentation also based on heat equation with PDEs, the central line is extracted based on image skeleton, and the branch is removed automatically, the phase level is calculated by spline interpolation method, and the fringe phase can be unwrapped. Finally, the imaging processing method was used to automatically measure the bubble in rubber with negative pressure which could be used in the tire detection.

  13. Soft tissue tumors - imaging methods

    International Nuclear Information System (INIS)

    Arlart, I.P.

    1985-01-01

    Soft Tissue Tumors - Imaging Methods: Imaging methods play an important diagnostic role in soft tissue tumors concerning a preoperative evaluation of localization, size, topographic relationship, dignity, and metastatic disease. The present paper gives an overview about diagnostic methods available today such as ultrasound, thermography, roentgenographic plain films and xeroradiography, radionuclide methods, computed tomography, lymphography, angiography, and magnetic resonance imaging. Besides sonography particularly computed tomography has the most important diagnostic value in soft tissue tumors. The application of a recently developed method, the magnetic resonance imaging, cannot yet be assessed in its significance. (orig.) [de

  14. Target recognition of ladar range images using slice image: comparison of four improved algorithms

    Science.gov (United States)

    Xia, Wenze; Han, Shaokun; Cao, Jingya; Wang, Liang; Zhai, Yu; Cheng, Yang

    2017-07-01

    Compared with traditional 3-D shape data, ladar range images possess properties of strong noise, shape degeneracy, and sparsity, which make feature extraction and representation difficult. The slice image is an effective feature descriptor to resolve this problem. We propose four improved algorithms on target recognition of ladar range images using slice image. In order to improve resolution invariance of the slice image, mean value detection instead of maximum value detection is applied in these four improved algorithms. In order to improve rotation invariance of the slice image, three new improved feature descriptors-which are feature slice image, slice-Zernike moments, and slice-Fourier moments-are applied to the last three improved algorithms, respectively. Backpropagation neural networks are used as feature classifiers in the last two improved algorithms. The performance of these four improved recognition systems is analyzed comprehensively in the aspects of the three invariances, recognition rate, and execution time. The final experiment results show that the improvements for these four algorithms reach the desired effect, the three invariances of feature descriptors are not directly related to the final recognition performance of recognition systems, and these four improved recognition systems have different performances under different conditions.

  15. Deep kernel learning method for SAR image target recognition

    Science.gov (United States)

    Chen, Xiuyuan; Peng, Xiyuan; Duan, Ran; Li, Junbao

    2017-10-01

    With the development of deep learning, research on image target recognition has made great progress in recent years. Remote sensing detection urgently requires target recognition for military, geographic, and other scientific research. This paper aims to solve the synthetic aperture radar image target recognition problem by combining deep and kernel learning. The model, which has a multilayer multiple kernel structure, is optimized layer by layer with the parameters of Support Vector Machine and a gradient descent algorithm. This new deep kernel learning method improves accuracy and achieves competitive recognition results compared with other learning methods.

  16. Multilevel Image Segmentation Based on an Improved Firefly Algorithm

    Directory of Open Access Journals (Sweden)

    Kai Chen

    2016-01-01

    Full Text Available Multilevel image segmentation is time-consuming and involves large computation. The firefly algorithm has been applied to enhancing the efficiency of multilevel image segmentation. However, in some cases, firefly algorithm is easily trapped into local optima. In this paper, an improved firefly algorithm (IFA is proposed to search multilevel thresholds. In IFA, in order to help fireflies escape from local optima and accelerate the convergence, two strategies (i.e., diversity enhancing strategy with Cauchy mutation and neighborhood strategy are proposed and adaptively chosen according to different stagnation stations. The proposed IFA is compared with three benchmark optimal algorithms, that is, Darwinian particle swarm optimization, hybrid differential evolution optimization, and firefly algorithm. The experimental results show that the proposed method can efficiently segment multilevel images and obtain better performance than the other three methods.

  17. Studying depression using imaging and machine learning methods

    Directory of Open Access Journals (Sweden)

    Meenal J. Patel

    2016-01-01

    Full Text Available Depression is a complex clinical entity that can pose challenges for clinicians regarding both accurate diagnosis and effective timely treatment. These challenges have prompted the development of multiple machine learning methods to help improve the management of this disease. These methods utilize anatomical and physiological data acquired from neuroimaging to create models that can identify depressed patients vs. non-depressed patients and predict treatment outcomes. This article (1 presents a background on depression, imaging, and machine learning methodologies; (2 reviews methodologies of past studies that have used imaging and machine learning to study depression; and (3 suggests directions for future depression-related studies.

  18. Rapid flow imaging method

    International Nuclear Information System (INIS)

    Pelc, N.J.; Spritzer, C.E.; Lee, J.N.

    1988-01-01

    A rapid, phase-contrast, MR imaging method of imaging flow has been implemented. The method, called VIGRE (velocity imaging with gradient recalled echoes), consists of two interleaved, narrow flip angle, gradient-recalled acquisitions. One is flow compensated while the second has a specified flow encoding (both peak velocity and direction) that causes signals to contain additional phase in proportion to velocity in the specified direction. Complex image data from the first acquisition are used as a phase reference for the second, yielding immunity from phase accumulation due to causes other than motion. Images with pixel values equal to MΔΘ where M is the magnitude of the flow compensated image and ΔΘ is the phase difference at the pixel, are produced. The magnitude weighting provides additional vessel contrast, suppresses background noise, maintains the flow direction information, and still allows quantitative data to be retrieved. The method has been validated with phantoms and is undergoing initial clinical evaluation. Early results are extremely encouraging

  19. Statistical iterative reconstruction to improve image quality for digital breast tomosynthesis

    International Nuclear Information System (INIS)

    Xu, Shiyu; Chen, Ying; Lu, Jianping; Zhou, Otto

    2015-01-01

    Purpose: Digital breast tomosynthesis (DBT) is a novel modality with the potential to improve early detection of breast cancer by providing three-dimensional (3D) imaging with a low radiation dose. 3D image reconstruction presents some challenges: cone-beam and flat-panel geometry, and highly incomplete sampling. A promising means to overcome these challenges is statistical iterative reconstruction (IR), since it provides the flexibility of accurate physics modeling and a general description of system geometry. The authors’ goal was to develop techniques for applying statistical IR to tomosynthesis imaging data. Methods: These techniques include the following: a physics model with a local voxel-pair based prior with flexible parameters to fine-tune image quality; a precomputed parameter λ in the prior, to remove data dependence and to achieve a uniform resolution property; an effective ray-driven technique to compute the forward and backprojection; and an oversampled, ray-driven method to perform high resolution reconstruction with a practical region-of-interest technique. To assess the performance of these techniques, the authors acquired phantom data on the stationary DBT prototype system. To solve the estimation problem, the authors proposed an optimization-transfer based algorithm framework that potentially allows fewer iterations to achieve an acceptably converged reconstruction. Results: IR improved the detectability of low-contrast and small microcalcifications, reduced cross-plane artifacts, improved spatial resolution, and lowered noise in reconstructed images. Conclusions: Although the computational load remains a significant challenge for practical development, the superior image quality provided by statistical IR, combined with advancing computational techniques, may bring benefits to screening, diagnostics, and intraoperative imaging in clinical applications

  20. Statistical iterative reconstruction to improve image quality for digital breast tomosynthesis

    Energy Technology Data Exchange (ETDEWEB)

    Xu, Shiyu, E-mail: shiyu.xu@gmail.com; Chen, Ying, E-mail: adachen@siu.edu [Department of Electrical and Computer Engineering, Southern Illinois University Carbondale, Carbondale, Illinois 62901 (United States); Lu, Jianping; Zhou, Otto [Department of Physics and Astronomy and Curriculum in Applied Sciences and Engineering, University of North Carolina Chapel Hill, Chapel Hill, North Carolina 27599 (United States)

    2015-09-15

    Purpose: Digital breast tomosynthesis (DBT) is a novel modality with the potential to improve early detection of breast cancer by providing three-dimensional (3D) imaging with a low radiation dose. 3D image reconstruction presents some challenges: cone-beam and flat-panel geometry, and highly incomplete sampling. A promising means to overcome these challenges is statistical iterative reconstruction (IR), since it provides the flexibility of accurate physics modeling and a general description of system geometry. The authors’ goal was to develop techniques for applying statistical IR to tomosynthesis imaging data. Methods: These techniques include the following: a physics model with a local voxel-pair based prior with flexible parameters to fine-tune image quality; a precomputed parameter λ in the prior, to remove data dependence and to achieve a uniform resolution property; an effective ray-driven technique to compute the forward and backprojection; and an oversampled, ray-driven method to perform high resolution reconstruction with a practical region-of-interest technique. To assess the performance of these techniques, the authors acquired phantom data on the stationary DBT prototype system. To solve the estimation problem, the authors proposed an optimization-transfer based algorithm framework that potentially allows fewer iterations to achieve an acceptably converged reconstruction. Results: IR improved the detectability of low-contrast and small microcalcifications, reduced cross-plane artifacts, improved spatial resolution, and lowered noise in reconstructed images. Conclusions: Although the computational load remains a significant challenge for practical development, the superior image quality provided by statistical IR, combined with advancing computational techniques, may bring benefits to screening, diagnostics, and intraoperative imaging in clinical applications.

  1. An improved ghost-cell immersed boundary method for compressible flow simulations

    KAUST Repository

    Chi, Cheng

    2016-05-20

    This study presents an improved ghost-cell immersed boundary approach to represent a solid body in compressible flow simulations. In contrast to the commonly used approaches, in the present work ghost cells are mirrored through the boundary described using a level-set method to farther image points, incorporating a higher-order extra/interpolation scheme for the ghost cell values. A sensor is introduced to deal with image points near the discontinuities in the flow field. Adaptive mesh refinement (AMR) is used to improve the representation of the geometry efficiently in the Cartesian grid system. The improved ghost-cell method is validated against four test cases: (a) double Mach reflections on a ramp, (b) smooth Prandtl-Meyer expansion flows, (c) supersonic flows in a wind tunnel with a forward-facing step, and (d) supersonic flows over a circular cylinder. It is demonstrated that the improved ghost-cell method can reach the accuracy of second order in L1 norm and higher than first order in L∞ norm. Direct comparisons against the cut-cell method demonstrate that the improved ghost-cell method is almost equally accurate with better efficiency for boundary representation in high-fidelity compressible flow simulations. Copyright © 2016 John Wiley & Sons, Ltd.

  2. Improvement of nonlinear diffusion equation using relaxed geometric mean filter for low PSNR images

    DEFF Research Database (Denmark)

    Nadernejad, Ehsan

    2013-01-01

    A new method to improve the performance of low PSNR image denoising is presented. The proposed scheme estimates edge gradient from an image that is regularised with a relaxed geometric mean filter. The proposed method consists of two stages; the first stage consists of a second order nonlinear an...

  3. Improvement of range spatial resolution of medical ultrasound imaging by element-domain signal processing

    Science.gov (United States)

    Hasegawa, Hideyuki

    2017-07-01

    The range spatial resolution is an important factor determining the image quality in ultrasonic imaging. The range spatial resolution in ultrasonic imaging depends on the ultrasonic pulse length, which is determined by the mechanical response of the piezoelectric element in an ultrasonic probe. To improve the range spatial resolution without replacing the transducer element, in the present study, methods based on maximum likelihood (ML) estimation and multiple signal classification (MUSIC) were proposed. The proposed methods were applied to echo signals received by individual transducer elements in an ultrasonic probe. The basic experimental results showed that the axial half maximum of the echo from a string phantom was improved from 0.21 mm (conventional method) to 0.086 mm (ML) and 0.094 mm (MUSIC).

  4. Statistical image reconstruction methods for simultaneous emission/transmission PET scans

    International Nuclear Information System (INIS)

    Erdogan, H.; Fessler, J.A.

    1996-01-01

    Transmission scans are necessary for estimating the attenuation correction factors (ACFs) to yield quantitatively accurate PET emission images. To reduce the total scan time, post-injection transmission scans have been proposed in which one can simultaneously acquire emission and transmission data using rod sources and sinogram windowing. However, since the post-injection transmission scans are corrupted by emission coincidences, accurate correction for attenuation becomes more challenging. Conventional methods (emission subtraction) for ACF computation from post-injection scans are suboptimal and require relatively long scan times. We introduce statistical methods based on penalized-likelihood objectives to compute ACFs and then use them to reconstruct lower noise PET emission images from simultaneous transmission/emission scans. Simulations show the efficacy of the proposed methods. These methods improve image quality and SNR of the estimates as compared to conventional methods

  5. Improved Interactive Medical-Imaging System

    Science.gov (United States)

    Ross, Muriel D.; Twombly, Ian A.; Senger, Steven

    2003-01-01

    An improved computational-simulation system for interactive medical imaging has been invented. The system displays high-resolution, three-dimensional-appearing images of anatomical objects based on data acquired by such techniques as computed tomography (CT) and magnetic-resonance imaging (MRI). The system enables users to manipulate the data to obtain a variety of views for example, to display cross sections in specified planes or to rotate images about specified axes. Relative to prior such systems, this system offers enhanced capabilities for synthesizing images of surgical cuts and for collaboration by users at multiple, remote computing sites.

  6. Improved methods for dewarping images in convex mirrors in fine art: applications to van Eyck and Parmigianino

    Science.gov (United States)

    Usami, Yumi; Stork, David G.; Fujiki, Jun; Hino, Hideitsu; Akaho, Shotaro; Murata, Noboru

    2011-03-01

    We derive and demonstrate new methods for dewarping images depicted in convex mirrors in artwork and for estimating the three-dimensional shapes of the mirrors themselves. Previous methods were based on the assumption that mirrors were spherical or paraboloidal, an assumption unlikely to hold for hand-blown glass spheres used in early Renaissance art, such as Johannes van Eyck's Portrait of Giovanni (?) Arnolfini and his wife (1434) and Robert Campin's Portrait of St. John the Baptist and Heinrich von Werl (1438). Our methods are more general than such previous methods in that we assume merely that the mirror is radially symmetric and that there are straight lines (or colinear points) in the actual source scene. We express the mirror's shape as a mathematical series and pose the image dewarping task as that of estimating the coefficients in the series expansion. Central to our method is the plumbline principle: that the optimal coefficients are those that dewarp the mirror image so as to straighten lines that correspond to straight lines in the source scene. We solve for these coefficients algebraically through principal component analysis, PCA. Our method relies on a global figure of merit to balance warping errors throughout the image and it thereby reduces a reliance on the somewhat subjective criterion used in earlier methods. Our estimation can be applied to separate image annuli, which is appropriate if the mirror shape is irregular. Once we have found the optimal image dewarping, we compute the mirror shape by solving a differential equation based on the estimated dewarping function. We demonstrate our methods on the Arnolfini mirror and reveal a dewarped image superior to those found in prior work|an image noticeably more rectilinear throughout and having a more coherent geometrical perspective and vanishing points. Moreover, we find the mirror deviated from spherical and paraboloidal shape; this implies that it would have been useless as a concave

  7. Improving the quality of brain CT image from Wavelet filters

    International Nuclear Information System (INIS)

    Pita Machado, Reinaldo; Perez Diaz, Marlen; Bravo Pino, Rolando

    2012-01-01

    An algorithm to reduce Poisson noise is described using Wavelet filters. Five tomographic images of patients and a head anthropomorphic phantom were used. They were acquired with two different CT machines. Due to the original images contain the acquisition noise; some simulated free noise lesions were added to the images and after that the whole images were contaminated with noise. Contaminated images were filtered with 9 Wavelet filters at different decomposition levels and thresholds. Image quality of filtered and unfiltered images was graded using the Signal to Noise ratio, Normalized Mean Square Error and the Structural Similarity Index, as well as, by the subjective JAFROC methods with 5 observers. Some filters as Bior 3.7 and dB45 improved in a significant way head CT image quality (p<0.05) producing an increment in SNR without visible structural distortions

  8. Improve Image Quality of Transversal Relaxation Time PROPELLER and FLAIR on Magnetic Resonance Imaging

    Science.gov (United States)

    Rauf, N.; Alam, D. Y.; Jamaluddin, M.; Samad, B. A.

    2018-03-01

    The Magnetic Resonance Imaging (MRI) is a medical imaging technique that uses the interaction between the magnetic field and the nuclear spins. MRI can be used to show disparity of pathology by transversal relaxation time (T2) weighted images. Some techniques for producing T2-weighted images are Periodically Rotated Overlapping Parallel Lines with Enhanced Reconstruction (PROPELLER) and Fluid Attenuated Inversion Recovery (FLAIR). A comparison of T2 PROPELLER and T2 FLAIR parameters in MRI image has been conducted. And improve Image Quality the image by using RadiAnt DICOM Viewer and ENVI software with method of image segmentation and Region of Interest (ROI). Brain images were randomly selected. The result of research showed that Time Repetition (TR) and Time Echo (TE) values in all types of images were not influenced by age. T2 FLAIR images had longer TR value (9000 ms), meanwhile T2 PROPELLER images had longer TE value (100.75 - 102.1 ms). Furthermore, areas with low and medium signal intensity appeared clearer by using T2 PROPELLER images (average coefficients of variation for low and medium signal intensity were 0.0431 and 0.0705, respectively). As for areas with high signal intensity appeared clearer by using T2 FLAIR images (average coefficient of variation was 0.0637).

  9. Bayesian image reconstruction for improving detection performance of muon tomography.

    Science.gov (United States)

    Wang, Guobao; Schultz, Larry J; Qi, Jinyi

    2009-05-01

    Muon tomography is a novel technology that is being developed for detecting high-Z materials in vehicles or cargo containers. Maximum likelihood methods have been developed for reconstructing the scattering density image from muon measurements. However, the instability of maximum likelihood estimation often results in noisy images and low detectability of high-Z targets. In this paper, we propose using regularization to improve the image quality of muon tomography. We formulate the muon reconstruction problem in a Bayesian framework by introducing a prior distribution on scattering density images. An iterative shrinkage algorithm is derived to maximize the log posterior distribution. At each iteration, the algorithm obtains the maximum a posteriori update by shrinking an unregularized maximum likelihood update. Inverse quadratic shrinkage functions are derived for generalized Laplacian priors and inverse cubic shrinkage functions are derived for generalized Gaussian priors. Receiver operating characteristic studies using simulated data demonstrate that the Bayesian reconstruction can greatly improve the detection performance of muon tomography.

  10. Attenuation correction with region growing method used in the positron emission mammography imaging system

    Science.gov (United States)

    Gu, Xiao-Yue; Li, Lin; Yin, Peng-Fei; Yun, Ming-Kai; Chai, Pei; Huang, Xian-Chao; Sun, Xiao-Li; Wei, Long

    2015-10-01

    The Positron Emission Mammography imaging system (PEMi) provides a novel nuclear diagnosis method dedicated for breast imaging. With a better resolution than whole body PET, PEMi can detect millimeter-sized breast tumors. To address the requirement of semi-quantitative analysis with a radiotracer concentration map of the breast, a new attenuation correction method based on a three-dimensional seeded region growing image segmentation (3DSRG-AC) method has been developed. The method gives a 3D connected region as the segmentation result instead of image slices. The continuity property of the segmentation result makes this new method free of activity variation of breast tissues. The threshold value chosen is the key process for the segmentation method. The first valley in the grey level histogram of the reconstruction image is set as the lower threshold, which works well in clinical application. Results show that attenuation correction for PEMi improves the image quality and the quantitative accuracy of radioactivity distribution determination. Attenuation correction also improves the probability of detecting small and early breast tumors. Supported by Knowledge Innovation Project of The Chinese Academy of Sciences (KJCX2-EW-N06)

  11. Conjugate-gradient preconditioning methods for shift-variant PET image reconstruction.

    Science.gov (United States)

    Fessler, J A; Booth, S D

    1999-01-01

    Gradient-based iterative methods often converge slowly for tomographic image reconstruction and image restoration problems, but can be accelerated by suitable preconditioners. Diagonal preconditioners offer some improvement in convergence rate, but do not incorporate the structure of the Hessian matrices in imaging problems. Circulant preconditioners can provide remarkable acceleration for inverse problems that are approximately shift-invariant, i.e., for those with approximately block-Toeplitz or block-circulant Hessians. However, in applications with nonuniform noise variance, such as arises from Poisson statistics in emission tomography and in quantum-limited optical imaging, the Hessian of the weighted least-squares objective function is quite shift-variant, and circulant preconditioners perform poorly. Additional shift-variance is caused by edge-preserving regularization methods based on nonquadratic penalty functions. This paper describes new preconditioners that approximate more accurately the Hessian matrices of shift-variant imaging problems. Compared to diagonal or circulant preconditioning, the new preconditioners lead to significantly faster convergence rates for the unconstrained conjugate-gradient (CG) iteration. We also propose a new efficient method for the line-search step required by CG methods. Applications to positron emission tomography (PET) illustrate the method.

  12. Multi-clues image retrieval based on improved color invariants

    Science.gov (United States)

    Liu, Liu; Li, Jian-Xun

    2012-05-01

    At present, image retrieval has a great progress in indexing efficiency and memory usage, which mainly benefits from the utilization of the text retrieval technology, such as the bag-of-features (BOF) model and the inverted-file structure. Meanwhile, because the robust local feature invariants are selected to establish BOF, the retrieval precision of BOF is enhanced, especially when it is applied to a large-scale database. However, these local feature invariants mainly consider the geometric variance of the objects in the images, and thus the color information of the objects fails to be made use of. Because of the development of the information technology and Internet, the majority of our retrieval objects is color images. Therefore, retrieval performance can be further improved through proper utilization of the color information. We propose an improved method through analyzing the flaw of shadow-shading quasi-invariant. The response and performance of shadow-shading quasi-invariant for the object edge with the variance of lighting are enhanced. The color descriptors of the invariant regions are extracted and integrated into BOF based on the local feature. The robustness of the algorithm and the improvement of the performance are verified in the final experiments.

  13. Image combination enhancement method for X-ray compton back-scattering security inspection body scanner

    International Nuclear Information System (INIS)

    Wang Huaiying; Zhang Yujin; Yang Lirui; Li Dong

    2011-01-01

    As for X-ray Compton Back-Scattering (CBS) body scanner, image clearness is very important for the performance of detecting the contraband hidden on the body. A new image combination enhancement method is provided based on characteristics of CBS body images and points of human vision. After processed by this method, the CBS image will be obviously improved with clear levels, distinct outline and uniform background. (authors)

  14. A Remote Sensing Image Fusion Method based on adaptive dictionary learning

    Science.gov (United States)

    He, Tongdi; Che, Zongxi

    2018-01-01

    This paper discusses using a remote sensing fusion method, based on' adaptive sparse representation (ASP)', to provide improved spectral information, reduce data redundancy and decrease system complexity. First, the training sample set is formed by taking random blocks from the images to be fused, the dictionary is then constructed using the training samples, and the remaining terms are clustered to obtain the complete dictionary by iterated processing at each step. Second, the self-adaptive weighted coefficient rule of regional energy is used to select the feature fusion coefficients and complete the reconstruction of the image blocks. Finally, the reconstructed image blocks are rearranged and an average is taken to obtain the final fused images. Experimental results show that the proposed method is superior to other traditional remote sensing image fusion methods in both spectral information preservation and spatial resolution.

  15. A novel optical gating method for laser gated imaging

    Science.gov (United States)

    Ginat, Ran; Schneider, Ron; Zohar, Eyal; Nesher, Ofer

    2013-06-01

    For the past 15 years, Elbit Systems is developing time-resolved active laser-gated imaging (LGI) systems for various applications. Traditional LGI systems are based on high sensitive gated sensors, synchronized to pulsed laser sources. Elbit propriety multi-pulse per frame method, which is being implemented in LGI systems, improves significantly the imaging quality. A significant characteristic of the LGI is its ability to penetrate a disturbing media, such as rain, haze and some fog types. Current LGI systems are based on image intensifier (II) sensors, limiting the system in spectral response, image quality, reliability and cost. A novel propriety optical gating module was developed in Elbit, untying the dependency of LGI system on II. The optical gating module is not bounded to the radiance wavelength and positioned between the system optics and the sensor. This optical gating method supports the use of conventional solid state sensors. By selecting the appropriate solid state sensor, the new LGI systems can operate at any desired wavelength. In this paper we present the new gating method characteristics, performance and its advantages over the II gating method. The use of the gated imaging systems is described in a variety of applications, including results from latest field experiments.

  16. A High-Dynamic-Range Optical Remote Sensing Imaging Method for Digital TDI CMOS

    Directory of Open Access Journals (Sweden)

    Taiji Lan

    2017-10-01

    Full Text Available The digital time delay integration (digital TDI technology of the complementary metal-oxide-semiconductor (CMOS image sensor has been widely adopted and developed in the optical remote sensing field. However, the details of targets that have low illumination or low contrast in scenarios of high contrast are often drowned out because of the superposition of multi-stage images in digital domain multiplies the read noise and the dark noise, thus limiting the imaging dynamic range. Through an in-depth analysis of the information transfer model of digital TDI, this paper attempts to explore effective ways to overcome this issue. Based on the evaluation and analysis of multi-stage images, the entropy-maximized adaptive histogram equalization (EMAHE algorithm is proposed to improve the ability of images to express the details of dark or low-contrast targets. Furthermore, in this paper, an image fusion method is utilized based on gradient pyramid decomposition and entropy weighting of different TDI stage images, which can improve the detection ability of the digital TDI CMOS for complex scenes with high contrast, and obtain images that are suitable for recognition by the human eye. The experimental results show that the proposed methods can effectively improve the high-dynamic-range imaging (HDRI capability of the digital TDI CMOS. The obtained images have greater entropy and average gradients.

  17. Methods of Hematoxylin and Erosin Image Information Acquisition and Optimization in Confocal Microscopy.

    Science.gov (United States)

    Yoon, Woong Bae; Kim, Hyunjin; Kim, Kwang Gi; Choi, Yongdoo; Chang, Hee Jin; Sohn, Dae Kyung

    2016-07-01

    We produced hematoxylin and eosin (H&E) staining-like color images by using confocal laser scanning microscopy (CLSM), which can obtain the same or more information in comparison to conventional tissue staining. We improved images by using several image converting techniques, including morphological methods, color space conversion methods, and segmentation methods. An image obtained after image processing showed coloring very similar to that in images produced by H&E staining, and it is advantageous to conduct analysis through fluorescent dye imaging and microscopy rather than analysis based on single microscopic imaging. The colors used in CLSM are different from those seen in H&E staining, which is the method most widely used for pathologic diagnosis and is familiar to pathologists. Computer technology can facilitate the conversion of images by CLSM to be very similar to H&E staining images. We believe that the technique used in this study has great potential for application in clinical tissue analysis.

  18. A Novel Unsupervised Segmentation Quality Evaluation Method for Remote Sensing Images.

    Science.gov (United States)

    Gao, Han; Tang, Yunwei; Jing, Linhai; Li, Hui; Ding, Haifeng

    2017-10-24

    The segmentation of a high spatial resolution remote sensing image is a critical step in geographic object-based image analysis (GEOBIA). Evaluating the performance of segmentation without ground truth data, i.e., unsupervised evaluation, is important for the comparison of segmentation algorithms and the automatic selection of optimal parameters. This unsupervised strategy currently faces several challenges in practice, such as difficulties in designing effective indicators and limitations of the spectral values in the feature representation. This study proposes a novel unsupervised evaluation method to quantitatively measure the quality of segmentation results to overcome these problems. In this method, multiple spectral and spatial features of images are first extracted simultaneously and then integrated into a feature set to improve the quality of the feature representation of ground objects. The indicators designed for spatial stratified heterogeneity and spatial autocorrelation are included to estimate the properties of the segments in this integrated feature set. These two indicators are then combined into a global assessment metric as the final quality score. The trade-offs of the combined indicators are accounted for using a strategy based on the Mahalanobis distance, which can be exhibited geometrically. The method is tested on two segmentation algorithms and three testing images. The proposed method is compared with two existing unsupervised methods and a supervised method to confirm its capabilities. Through comparison and visual analysis, the results verified the effectiveness of the proposed method and demonstrated the reliability and improvements of this method with respect to other methods.

  19. A Novel Unsupervised Segmentation Quality Evaluation Method for Remote Sensing Images

    Directory of Open Access Journals (Sweden)

    Han Gao

    2017-10-01

    Full Text Available The segmentation of a high spatial resolution remote sensing image is a critical step in geographic object-based image analysis (GEOBIA. Evaluating the performance of segmentation without ground truth data, i.e., unsupervised evaluation, is important for the comparison of segmentation algorithms and the automatic selection of optimal parameters. This unsupervised strategy currently faces several challenges in practice, such as difficulties in designing effective indicators and limitations of the spectral values in the feature representation. This study proposes a novel unsupervised evaluation method to quantitatively measure the quality of segmentation results to overcome these problems. In this method, multiple spectral and spatial features of images are first extracted simultaneously and then integrated into a feature set to improve the quality of the feature representation of ground objects. The indicators designed for spatial stratified heterogeneity and spatial autocorrelation are included to estimate the properties of the segments in this integrated feature set. These two indicators are then combined into a global assessment metric as the final quality score. The trade-offs of the combined indicators are accounted for using a strategy based on the Mahalanobis distance, which can be exhibited geometrically. The method is tested on two segmentation algorithms and three testing images. The proposed method is compared with two existing unsupervised methods and a supervised method to confirm its capabilities. Through comparison and visual analysis, the results verified the effectiveness of the proposed method and demonstrated the reliability and improvements of this method with respect to other methods.

  20. An Improved Ghost-cell Immersed Boundary Method for Compressible Inviscid Flow Simulations

    KAUST Repository

    Chi, Cheng

    2015-05-01

    This study presents an improved ghost-cell immersed boundary approach to represent a solid body in compressible flow simulations. In contrast to the commonly used approaches, in the present work ghost cells are mirrored through the boundary described using a level-set method to farther image points, incorporating a higher-order extra/interpolation scheme for the ghost cell values. In addition, a shock sensor is in- troduced to deal with image points near the discontinuities in the flow field. Adaptive mesh refinement (AMR) is used to improve the representation of the geometry efficiently. The improved ghost-cell method is validated against five test cases: (a) double Mach reflections on a ramp, (b) supersonic flows in a wind tunnel with a forward- facing step, (c) supersonic flows over a circular cylinder, (d) smooth Prandtl-Meyer expansion flows, and (e) steady shock-induced combustion over a wedge. It is demonstrated that the improved ghost-cell method can reach the accuracy of second order in L1 norm and higher than first order in L∞ norm. Direct comparisons against the cut-cell method demonstrate that the improved ghost-cell method is almost equally accurate with better efficiency for boundary representation in high-fidelity compressible flow simulations. Implementation of the improved ghost-cell method in reacting Euler flows further validates its general applicability for compressible flow simulations.

  1. Improving Accuracy for Image Fusion in Abdominal Ultrasonography

    Directory of Open Access Journals (Sweden)

    Caroline Ewertsen

    2012-08-01

    Full Text Available Image fusion involving real-time ultrasound (US is a technique where previously recorded computed tomography (CT or magnetic resonance images (MRI are reformatted in a projection to fit the real-time US images after an initial co-registration. The co-registration aligns the images by means of common planes or points. We evaluated the accuracy of the alignment when varying parameters as patient position, respiratory phase and distance from the co-registration points/planes. We performed a total of 80 co-registrations and obtained the highest accuracy when the respiratory phase for the co-registration procedure was the same as when the CT or MRI was obtained. Furthermore, choosing co-registration points/planes close to the area of interest also improved the accuracy. With all settings optimized a mean error of 3.2 mm was obtained. We conclude that image fusion involving real-time US is an accurate method for abdominal examinations and that the accuracy is influenced by various adjustable factors that should be kept in mind.

  2. CT image segmentation methods for bone used in medical additive manufacturing.

    Science.gov (United States)

    van Eijnatten, Maureen; van Dijk, Roelof; Dobbe, Johannes; Streekstra, Geert; Koivisto, Juha; Wolff, Jan

    2018-01-01

    The accuracy of additive manufactured medical constructs is limited by errors introduced during image segmentation. The aim of this study was to review the existing literature on different image segmentation methods used in medical additive manufacturing. Thirty-two publications that reported on the accuracy of bone segmentation based on computed tomography images were identified using PubMed, ScienceDirect, Scopus, and Google Scholar. The advantages and disadvantages of the different segmentation methods used in these studies were evaluated and reported accuracies were compared. The spread between the reported accuracies was large (0.04 mm - 1.9 mm). Global thresholding was the most commonly used segmentation method with accuracies under 0.6 mm. The disadvantage of this method is the extensive manual post-processing required. Advanced thresholding methods could improve the accuracy to under 0.38 mm. However, such methods are currently not included in commercial software packages. Statistical shape model methods resulted in accuracies from 0.25 mm to 1.9 mm but are only suitable for anatomical structures with moderate anatomical variations. Thresholding remains the most widely used segmentation method in medical additive manufacturing. To improve the accuracy and reduce the costs of patient-specific additive manufactured constructs, more advanced segmentation methods are required. Copyright © 2017 IPEM. Published by Elsevier Ltd. All rights reserved.

  3. A flexible new method for 3D measurement based on multi-view image sequences

    Science.gov (United States)

    Cui, Haihua; Zhao, Zhimin; Cheng, Xiaosheng; Guo, Changye; Jia, Huayu

    2016-11-01

    Three-dimensional measurement is the base part for reverse engineering. The paper developed a new flexible and fast optical measurement method based on multi-view geometry theory. At first, feature points are detected and matched with improved SIFT algorithm. The Hellinger Kernel is used to estimate the histogram distance instead of traditional Euclidean distance, which is immunity to the weak texture image; then a new filter three-principle for filtering the calculation of essential matrix is designed, the essential matrix is calculated using the improved a Contrario Ransac filter method. One view point cloud is constructed accurately with two view images; after this, the overlapped features are used to eliminate the accumulated errors caused by added view images, which improved the camera's position precision. At last, the method is verified with the application of dental restoration CAD/CAM, experiment results show that the proposed method is fast, accurate and flexible for tooth 3D measurement.

  4. Image Improvement Techniques

    Science.gov (United States)

    Shine, R. A.

    1997-05-01

    Over the last decade, a repertoire of techniques have been developed and/or refined to improve the quality of high spatial resolution solar movies taken from ground based observatories. These include real time image motion corrections, frame selection, phase diversity measurements of the wavefront, and extensive post processing to partially remove atmospheric distortion. Their practical application has been made possible by the increasing availability and decreasing cost of large CCD's with fast digital readouts and high speed computer workstations with large memories. Most successful have been broad band (0.3 to 10 nm) filtergram movies which can use exposure times of 10 to 30 ms, short enough to ``freeze'' atmospheric motions. Even so, only a handful of movies with excellent image quality for more than a hour have been obtained to date. Narrowband filtergrams (about 0.01 nm), such as those required for constructing magnetograms and Dopplergrams, have been more challenging although some single images approach the quality of the best continuum images. Some promising new techniques and instruments, together with persistence and good luck, should continue the progress made in the last several years.

  5. Methods in quantitative image analysis.

    Science.gov (United States)

    Oberholzer, M; Ostreicher, M; Christen, H; Brühlmann, M

    1996-05-01

    histogram of an existing image (input image) into a new grey value histogram (output image) are most quickly handled by a look-up table (LUT). The histogram of an image can be influenced by gain, offset and gamma of the camera. Gain defines the voltage range, offset defines the reference voltage and gamma the slope of the regression line between the light intensity and the voltage of the camera. A very important descriptor of neighbourhood relations in an image is the co-occurrence matrix. The distance between the pixels (original pixel and its neighbouring pixel) can influence the various parameters calculated from the co-occurrence matrix. The main goals of image enhancement are elimination of surface roughness in an image (smoothing), correction of defects (e.g. noise), extraction of edges, identification of points, strengthening texture elements and improving contrast. In enhancement, two types of operations can be distinguished: pixel-based (point operations) and neighbourhood-based (matrix operations). The most important pixel-based operations are linear stretching of grey values, application of pre-stored LUTs and histogram equalisation. The neighbourhood-based operations work with so-called filters. These are organising elements with an original or initial point in their centre. Filters can be used to accentuate or to suppress specific structures within the image. Filters can work either in the spatial or in the frequency domain. The method used for analysing alterations of grey value intensities in the frequency domain is the Hartley transform. Filter operations in the spatial domain can be based on averaging or ranking the grey values occurring in the organising element. The most important filters, which are usually applied, are the Gaussian filter and the Laplace filter (both averaging filters), and the median filter, the top hat filter and the range operator (all ranking filters). Segmentation of objects is traditionally based on threshold grey values. (AB

  6. Improved contrast deep optoacoustic imaging using displacement-compensated averaging: breast tumour phantom studies

    Energy Technology Data Exchange (ETDEWEB)

    Jaeger, M; Preisser, S; Kitz, M; Frenz, M [Institute of Applied Physics, University of Bern, Sidlerstrasse 5, CH-3012 Bern (Switzerland); Ferrara, D; Senegas, S; Schweizer, D, E-mail: frenz@iap.unibe.ch [Fukuda Denshi Switzerland AG, Reinacherstrasse 131, CH-4002 Basel (Switzerland)

    2011-09-21

    For real-time optoacoustic (OA) imaging of the human body, a linear array transducer and reflection mode optical irradiation is usually preferred. Such a setup, however, results in significant image background, which prevents imaging structures at the ultimate depth determined by the light distribution and the signal noise level. Therefore, we previously proposed a method for image background reduction, based on displacement-compensated averaging (DCA) of image series obtained when the tissue sample under investigation is gradually deformed. OA signals and background signals are differently affected by the deformation and can thus be distinguished. The proposed method is now experimentally applied to image artificial tumours embedded inside breast phantoms. OA images are acquired alternately with pulse-echo images using a combined OA/echo-ultrasound device. Tissue deformation is accessed via speckle tracking in pulse echo images, and used to compensate in the OA images for the local tissue displacement. In that way, OA sources are highly correlated between subsequent images, while background is decorrelated and can therefore be reduced by averaging. We show that image contrast in breast phantoms is strongly improved and detectability of embedded tumours significantly increased, using the DCA method.

  7. Imaging of 1.0-mm-diameter radiopaque markers with megavoltage X-rays: an improved online imaging system

    International Nuclear Information System (INIS)

    Pang, G.; Beachey, D.J.; O'Brien, P.F.; Rowlands, J.A.

    2002-01-01

    Purpose: To improve an online portal imaging system such that implanted cylindrical gold markers of small diameter (no more than 1.0 mm) can be visualized. These small markers would make the implantation procedure much less traumatic for the patient than the large markers (1.6 mm in diameter), which are usually used today to monitor prostate interfraction motion during radiation therapy. Methods and Materials: Several changes have been made to a mirror-video based online imaging system to improve image quality. First, the conventional camera tube was replaced by an avalanche-multiplication-based video tube. This new camera tube has very high gain at the target such that the camera noise, which is one of the main causes of image degradation of online portal imaging systems, was overcome and effectively eliminated. Second, the conventional linear-accelerator (linac) target was replaced with a low atomic number (low-Z) target such that more diagnostic X-rays are present in the megavoltage X-ray beam. Third, the copper plate buildup layer for the phosphor screen was replaced by a thin plastic layer for detection of the diagnostic X-ray components in the beam generated by the low-Z target. Results: Radiopaque fiducial gold markers of different sizes, i.e., 1.0 mm (diameter) x 5 mm (length) and 0.8 mm (diameter) x 3 mm (length), embedded in an Alderson Rando phantom, can be clearly seen on the images acquired with our improved system. These markers could not be seen on images obtained with any commercial system available in our clinic. Conclusion: This work demonstrates the visibility of small-diameter radiopaque markers with an improved online portal imaging system. These markers can be easily implanted into the prostate and used to monitor the interfraction motion of the prostate

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

    Science.gov (United States)

    Zhang, Jiachao; Hirakawa, Keigo

    2017-04-01

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

  9. Methods for evaluating imaging methods of limited reproducibility

    International Nuclear Information System (INIS)

    Krummenauer, F.

    2005-01-01

    Just like new drugs, new or modified imaging methods must be subjected to objective clinical tests, including tests on humans. In this, it must be ensured that the principle of Good Clinical Practice (GCP) are followed with regard to medical, administrative and methodical quality. Innovative methods fo clinical epidemiology and medical biometry should be applied from the planning stage to the final statistical evaluation. The author presents established and new methods for planning, evaluation and reporting of clinical tests of diagnostic methods, and especially imaging methods, in clinical medicine and illustrates these by means of current research projects in the various medical disciplines. The strategies presented are summarized in a recommendation based on the concept of phases I - IV of clinical drug testing in order to enable standardisation of the clinical evaluation of imaging methods. (orig.)

  10. An Interactive Method Based on the Live Wire for Segmentation of the Breast in Mammography Images

    Directory of Open Access Journals (Sweden)

    Zhang Zewei

    2014-01-01

    Full Text Available In order to improve accuracy of computer-aided diagnosis of breast lumps, the authors introduce an improved interactive segmentation method based on Live Wire. This paper presents the Gabor filters and FCM clustering algorithm is introduced to the Live Wire cost function definition. According to the image FCM analysis for image edge enhancement, we eliminate the interference of weak edge and access external features clear segmentation results of breast lumps through improving Live Wire on two cases of breast segmentation data. Compared with the traditional method of image segmentation, experimental results show that the method achieves more accurate segmentation of breast lumps and provides more accurate objective basis on quantitative and qualitative analysis of breast lumps.

  11. An interactive method based on the live wire for segmentation of the breast in mammography images.

    Science.gov (United States)

    Zewei, Zhang; Tianyue, Wang; Li, Guo; Tingting, Wang; Lu, Xu

    2014-01-01

    In order to improve accuracy of computer-aided diagnosis of breast lumps, the authors introduce an improved interactive segmentation method based on Live Wire. This paper presents the Gabor filters and FCM clustering algorithm is introduced to the Live Wire cost function definition. According to the image FCM analysis for image edge enhancement, we eliminate the interference of weak edge and access external features clear segmentation results of breast lumps through improving Live Wire on two cases of breast segmentation data. Compared with the traditional method of image segmentation, experimental results show that the method achieves more accurate segmentation of breast lumps and provides more accurate objective basis on quantitative and qualitative analysis of breast lumps.

  12. SU-E-I-82: Improving CT Image Quality for Radiation Therapy Using Iterative Reconstruction Algorithms and Slightly Increasing Imaging Doses

    International Nuclear Information System (INIS)

    Noid, G; Chen, G; Tai, A; Li, X

    2014-01-01

    Purpose: Iterative reconstruction (IR) algorithms are developed to improve CT image quality (IQ) by reducing noise without diminishing spatial resolution or contrast. For CT in radiation therapy (RT), slightly increasing imaging dose to improve IQ may be justified if it can substantially enhance structure delineation. The purpose of this study is to investigate and to quantify the IQ enhancement as a result of increasing imaging doses and using IR algorithms. Methods: CT images were acquired for phantoms, built to evaluate IQ metrics including spatial resolution, contrast and noise, with a variety of imaging protocols using a CT scanner (Definition AS Open, Siemens) installed inside a Linac room. Representative patients were scanned once the protocols were optimized. Both phantom and patient scans were reconstructed using the Sinogram Affirmed Iterative Reconstruction (SAFIRE) and the Filtered Back Projection (FBP) methods. IQ metrics of the obtained CTs were compared. Results: IR techniques are demonstrated to preserve spatial resolution as measured by the point spread function and reduce noise in comparison to traditional FBP. Driven by the reduction in noise, the contrast to noise ratio is doubled by adopting the highest SAFIRE strength. As expected, increasing imaging dose reduces noise for both SAFIRE and FBP reconstructions. The contrast to noise increases from 3 to 5 by increasing the dose by a factor of 4. Similar IQ improvement was observed on the CTs for selected patients with pancreas and prostrate cancers. Conclusion: The IR techniques produce a measurable enhancement to CT IQ by reducing the noise. Increasing imaging dose further reduces noise independent of the IR techniques. The improved CT enables more accurate delineation of tumors and/or organs at risk during RT planning and delivery guidance

  13. Scan time reduction in {sup 23}Na-Magnetic Resonance Imaging using the chemical shift imaging sequence. Evaluation of an iterative reconstruction method

    Energy Technology Data Exchange (ETDEWEB)

    Weingaertner, Sebastian; Konstandin, Simon; Schad, Lothar R. [Heidelberg Univ., Mannheim (Germany). Computer Assisted Clinical Medicine; Wetterling, Friedrich [Heidelberg Univ., Mannheim (Germany). Computer Assisted Clinical Medicine; Dublin Univ. (Ireland) Trinity Inst. of Neuroscience; Fatar, Marc [Heidelberg Univ., Mannheim (Germany). Dept. of Neurology; Neumaier-Probst, Eva [Heidelberg Univ., Mannheim (Germany). Dept. of Neuroradiology

    2015-07-01

    To evaluate potential scan time reduction in {sup 23}Na-Magnetic Resonance Imaging with the chemical shift imaging sequence (CSI) using undersampled data of high-quality datasets, reconstructed with an iterative constrained reconstruction, compared to reduced resolution or reduced signal-to-noise ratio. CSI {sup 23}Na-images were retrospectively undersampled and reconstructed with a constrained reconstruction scheme. The results were compared to conventional methods of scan time reduction. The constrained reconstruction scheme used a phase constraint and a finite object support, which was extracted from a spatially registered {sup 1}H-image acquired with a double-tuned coil. The methods were evaluated using numerical simulations, phantom images and in-vivo images of a healthy volunteer and a patient who suffered from cerebral ischemic stroke. The constrained reconstruction scheme showed improved image quality compared to a decreased number of averages, images with decreased resolution or circular undersampling with weighted averaging for any undersampling factor. Brain images of a stroke patient, which were reconstructed from three-fold undersampled k-space data, resulted in only minor differences from the original image (normalized root means square error < 12%) and an almost identical delineation of the stroke region (mismatch < 6%). The acquisition of undersampled {sup 23}Na-CSI images enables up to three-fold scan time reduction with improved image quality compared to conventional methods of scan time saving.

  14. X-ray scatter correction method for dedicated breast computed tomography: improvements and initial patient testing

    International Nuclear Information System (INIS)

    Ramamurthy, Senthil; D’Orsi, Carl J; Sechopoulos, Ioannis

    2016-01-01

    A previously proposed x-ray scatter correction method for dedicated breast computed tomography was further developed and implemented so as to allow for initial patient testing. The method involves the acquisition of a complete second set of breast CT projections covering 360° with a perforated tungsten plate in the path of the x-ray beam. To make patient testing feasible, a wirelessly controlled electronic positioner for the tungsten plate was designed and added to a breast CT system. Other improvements to the algorithm were implemented, including automated exclusion of non-valid primary estimate points and the use of a different approximation method to estimate the full scatter signal. To evaluate the effectiveness of the algorithm, evaluation of the resulting image quality was performed with a breast phantom and with nine patient images. The improvements in the algorithm resulted in the avoidance of introduction of artifacts, especially at the object borders, which was an issue in the previous implementation in some cases. Both contrast, in terms of signal difference and signal difference-to-noise ratio were improved with the proposed method, as opposed to with the correction algorithm incorporated in the system, which does not recover contrast. Patient image evaluation also showed enhanced contrast, better cupping correction, and more consistent voxel values for the different tissues. The algorithm also reduces artifacts present in reconstructions of non-regularly shaped breasts. With the implemented hardware and software improvements, the proposed method can be reliably used during patient breast CT imaging, resulting in improvement of image quality, no introduction of artifacts, and in some cases reduction of artifacts already present. The impact of the algorithm on actual clinical performance for detection, diagnosis and other clinical tasks in breast imaging remains to be evaluated. (paper)

  15. Dynamic CT perfusion imaging of the myocardium: a technical note on improvement of image quality.

    Directory of Open Access Journals (Sweden)

    Daniela Muenzel

    Full Text Available OBJECTIVE: To improve image and diagnostic quality in dynamic CT myocardial perfusion imaging (MPI by using motion compensation and a spatio-temporal filter. METHODS: Dynamic CT MPI was performed using a 256-slice multidetector computed tomography scanner (MDCT. Data from two different patients-with and without myocardial perfusion defects-were evaluated to illustrate potential improvements for MPI (institutional review board approved. Three datasets for each patient were generated: (i original data (ii motion compensated data and (iii motion compensated data with spatio-temporal filtering performed. In addition to the visual assessment of the tomographic slices, noise and contrast-to-noise-ratio (CNR were measured for all data. Perfusion analysis was performed using time-density curves with regions-of-interest (ROI placed in normal and hypoperfused myocardium. Precision in definition of normal and hypoperfused areas was determined in corresponding coloured perfusion maps. RESULTS: The use of motion compensation followed by spatio-temporal filtering resulted in better alignment of the cardiac volumes over time leading to a more consistent perfusion quantification and improved detection of the extend of perfusion defects. Additionally image noise was reduced by 78.5%, with CNR improvements by a factor of 4.7. The average effective radiation dose estimate was 7.1±1.1 mSv. CONCLUSION: The use of motion compensation and spatio-temporal smoothing will result in improved quantification of dynamic CT MPI using a latest generation CT scanner.

  16. 3D/3D registration of coronary CTA and biplane XA reconstructions for improved image guidance

    Energy Technology Data Exchange (ETDEWEB)

    Dibildox, Gerardo, E-mail: g.dibildox@erasmusmc.nl; Baka, Nora; Walsum, Theo van [Biomedical Imaging Group Rotterdam, Departments of Radiology and Medical Informatics, Erasmus Medical Center, 3015 GE Rotterdam (Netherlands); Punt, Mark; Aben, Jean-Paul [Pie Medical Imaging, 6227 AJ Maastricht (Netherlands); Schultz, Carl [Department of Cardiology, Erasmus Medical Center, 3015 GE Rotterdam (Netherlands); Niessen, Wiro [Quantitative Imaging Group, Faculty of Applied Sciences, Delft University of Technology, 2628 CJ Delft, The Netherlands and Biomedical Imaging Group Rotterdam, Departments of Radiology and Medical Informatics, Erasmus Medical Center, 3015 GE Rotterdam (Netherlands)

    2014-09-15

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

  17. A novel method for enhancing the lateral resolution and image SNR in confocal microscopy

    Science.gov (United States)

    Chen, Youhua; Zhu, Dazhao; Fang, Yue; Kuang, Cuifang; Liu, Xu

    2017-12-01

    There is always a tradeoff between the resolution and the signal-to-noise ratio (SNR) in confocal microscopy. In particular, the pinhole size is very important for maintaining a balance between them. In this paper, we propose a method for improving the lateral resolution and image SNR in confocal microscopy without making any changes to the hardware. By using the fluorescence emission difference (FED) approach, we divide the images acquired by different pinhole sizes into one image acquired by the central pinhole and several images acquired by ring-shaped pinholes. Then, they are added together with the deconvolution method. Simulation and experimental results for fluorescent particles and cells show that our method can achieve a far better resolution than a large pinhole and a higher SNR than a small pinhole. Moreover, our method can improve the performance of classic confocal laser scanning microscopy (CLSM) to a certain extent, especially CLSM with a continuously variable pinhole.

  18. Bone surface enhancement in ultrasound images using a new Doppler-based acquisition/processing method

    Science.gov (United States)

    Yang, Xu; Tang, Songyuan; Tasciotti, Ennio; Righetti, Raffaella

    2018-01-01

    Ultrasound (US) imaging has long been considered as a potential aid in orthopedic surgeries. US technologies are safe, portable and do not use radiations. This would make them a desirable tool for real-time assessment of fractures and to monitor fracture healing. However, image quality of US imaging methods in bone applications is limited by speckle, attenuation, shadow, multiple reflections and other imaging artifacts. While bone surfaces typically appear in US images as somewhat ‘brighter’ than soft tissue, they are often not easily distinguishable from the surrounding tissue. Therefore, US imaging methods aimed at segmenting bone surfaces need enhancement in image contrast prior to segmentation to improve the quality of the detected bone surface. In this paper, we present a novel acquisition/processing technique for bone surface enhancement in US images. Inspired by elastography and Doppler imaging methods, this technique takes advantage of the difference between the mechanical and acoustic properties of bones and those of soft tissues to make the bone surface more easily distinguishable in US images. The objective of this technique is to facilitate US-based bone segmentation methods and improve the accuracy of their outcomes. The newly proposed technique is tested both in in vitro and in vivo experiments. The results of these preliminary experiments suggest that the use of the proposed technique has the potential to significantly enhance the detectability of bone surfaces in noisy ultrasound images.

  19. Bone surface enhancement in ultrasound images using a new Doppler-based acquisition/processing method.

    Science.gov (United States)

    Yang, Xu; Tang, Songyuan; Tasciotti, Ennio; Righetti, Raffaella

    2018-01-17

    Ultrasound (US) imaging has long been considered as a potential aid in orthopedic surgeries. US technologies are safe, portable and do not use radiations. This would make them a desirable tool for real-time assessment of fractures and to monitor fracture healing. However, image quality of US imaging methods in bone applications is limited by speckle, attenuation, shadow, multiple reflections and other imaging artifacts. While bone surfaces typically appear in US images as somewhat 'brighter' than soft tissue, they are often not easily distinguishable from the surrounding tissue. Therefore, US imaging methods aimed at segmenting bone surfaces need enhancement in image contrast prior to segmentation to improve the quality of the detected bone surface. In this paper, we present a novel acquisition/processing technique for bone surface enhancement in US images. Inspired by elastography and Doppler imaging methods, this technique takes advantage of the difference between the mechanical and acoustic properties of bones and those of soft tissues to make the bone surface more easily distinguishable in US images. The objective of this technique is to facilitate US-based bone segmentation methods and improve the accuracy of their outcomes. The newly proposed technique is tested both in in vitro and in vivo experiments. The results of these preliminary experiments suggest that the use of the proposed technique has the potential to significantly enhance the detectability of bone surfaces in noisy ultrasound images.

  20. A New Pixels Flipping Method for Huge Watermarking Capacity of the Invoice Font Image

    Directory of Open Access Journals (Sweden)

    Li Li

    2014-01-01

    Full Text Available Invoice printing just has two-color printing, so invoice font image can be seen as binary image. To embed watermarks into invoice image, the pixels need to be flipped. The more huge the watermark is, the more the pixels need to be flipped. We proposed a new pixels flipping method in invoice image for huge watermarking capacity. The pixels flipping method includes one novel interpolation method for binary image, one flippable pixels evaluation mechanism, and one denoising method based on gravity center and chaos degree. The proposed interpolation method ensures that the invoice image keeps features well after scaling. The flippable pixels evaluation mechanism ensures that the pixels keep better connectivity and smoothness and the pattern has highest structural similarity after flipping. The proposed denoising method makes invoice font image smoother and fiter for human vision. Experiments show that the proposed flipping method not only keeps the invoice font structure well but also improves watermarking capacity.

  1. A new pixels flipping method for huge watermarking capacity of the invoice font image.

    Science.gov (United States)

    Li, Li; Hou, Qingzheng; Lu, Jianfeng; Xu, Qishuai; Dai, Junping; Mao, Xiaoyang; Chang, Chin-Chen

    2014-01-01

    Invoice printing just has two-color printing, so invoice font image can be seen as binary image. To embed watermarks into invoice image, the pixels need to be flipped. The more huge the watermark is, the more the pixels need to be flipped. We proposed a new pixels flipping method in invoice image for huge watermarking capacity. The pixels flipping method includes one novel interpolation method for binary image, one flippable pixels evaluation mechanism, and one denoising method based on gravity center and chaos degree. The proposed interpolation method ensures that the invoice image keeps features well after scaling. The flippable pixels evaluation mechanism ensures that the pixels keep better connectivity and smoothness and the pattern has highest structural similarity after flipping. The proposed denoising method makes invoice font image smoother and fiter for human vision. Experiments show that the proposed flipping method not only keeps the invoice font structure well but also improves watermarking capacity.

  2. Place of modern imaging methods and their influence on the diagnostic process

    International Nuclear Information System (INIS)

    Petkov, D.; Lazarova, I.

    1991-01-01

    The main trends in development of the modern imaging diagnostic methods are presented: increasing the specificity of CT, nuclear-magnetic resonance imaging, positron-emission tomography, digital substractional angiography, echography etc. based on modern technical improvements; objective representation of the physiological and biochemical divergencies in particular diseases; interventional radiology; integral application of different methods; improving the sensitivity and specificity of the methods based on developments in pharmacology (new contrast media, parmaceuticals influencing the function of examinated organs, etc.); the possibilities for data compilation and further computerized processing of primary data. Personal experience is reported with the exploitation of these methods in Bulgaria. Attention is also called to the unfavourable impact connected with the too strong technicization of the diagnostic and therapeutic process in a health, deontologic, economical and social respect. 15 refs

  3. Bispectral methods of signal processing applications in radar, telecommunications and digital image restoration

    CERN Document Server

    Totsky, Alexander V; Kravchenko, Victor F

    2015-01-01

    By studying applications in radar, telecommunications and digital image restoration, this monograph discusses signal processing techniques based on bispectral methods. Improved robustness against different forms of noise as well as preservation of phase information render this method a valuable alternative to common power-spectrum analysis used in radar object recognition, digital wireless communications, and jitter removal in images.

  4. Anatomical image-guided fluorescence molecular tomography reconstruction using kernel method

    Science.gov (United States)

    Baikejiang, Reheman; Zhao, Yue; Fite, Brett Z.; Ferrara, Katherine W.; Li, Changqing

    2017-01-01

    Abstract. Fluorescence molecular tomography (FMT) is an important in vivo imaging modality to visualize physiological and pathological processes in small animals. However, FMT reconstruction is ill-posed and ill-conditioned due to strong optical scattering in deep tissues, which results in poor spatial resolution. It is well known that FMT image quality can be improved substantially by applying the structural guidance in the FMT reconstruction. An approach to introducing anatomical information into the FMT reconstruction is presented using the kernel method. In contrast to conventional methods that incorporate anatomical information with a Laplacian-type regularization matrix, the proposed method introduces the anatomical guidance into the projection model of FMT. The primary advantage of the proposed method is that it does not require segmentation of targets in the anatomical images. Numerical simulations and phantom experiments have been performed to demonstrate the proposed approach’s feasibility. Numerical simulation results indicate that the proposed kernel method can separate two FMT targets with an edge-to-edge distance of 1 mm and is robust to false-positive guidance and inhomogeneity in the anatomical image. For the phantom experiments with two FMT targets, the kernel method has reconstructed both targets successfully, which further validates the proposed kernel method. PMID:28464120

  5. Improving high resolution retinal image quality using speckle illumination HiLo imaging.

    Science.gov (United States)

    Zhou, Xiaolin; Bedggood, Phillip; Metha, Andrew

    2014-08-01

    Retinal image quality from flood illumination adaptive optics (AO) ophthalmoscopes is adversely affected by out-of-focus light scatter due to the lack of confocality. This effect is more pronounced in small eyes, such as that of rodents, because the requisite high optical power confers a large dioptric thickness to the retina. A recently-developed structured illumination microscopy (SIM) technique called HiLo imaging has been shown to reduce the effect of out-of-focus light scatter in flood illumination microscopes and produce pseudo-confocal images with significantly improved image quality. In this work, we adopted the HiLo technique to a flood AO ophthalmoscope and performed AO imaging in both (physical) model and live rat eyes. The improvement in image quality from HiLo imaging is shown both qualitatively and quantitatively by using spatial spectral analysis.

  6. Image Reconstruction Based on Homotopy Perturbation Inversion Method for Electrical Impedance Tomography

    Directory of Open Access Journals (Sweden)

    Jing Wang

    2013-01-01

    Full Text Available The image reconstruction for electrical impedance tomography (EIT mathematically is a typed nonlinear ill-posed inverse problem. In this paper, a novel iteration regularization scheme based on the homotopy perturbation technique, namely, homotopy perturbation inversion method, is applied to investigate the EIT image reconstruction problem. To verify the feasibility and effectiveness, simulations of image reconstruction have been performed in terms of considering different locations, sizes, and numbers of the inclusions, as well as robustness to data noise. Numerical results indicate that this method can overcome the numerical instability and is robust to data noise in the EIT image reconstruction. Moreover, compared with the classical Landweber iteration method, our approach improves the convergence rate. The results are promising.

  7. Improved sampling and analysis of images in corneal confocal microscopy.

    Science.gov (United States)

    Schaldemose, E L; Fontain, F I; Karlsson, P; Nyengaard, J R

    2017-10-01

    Corneal confocal microscopy (CCM) is a noninvasive clinical method to analyse and quantify corneal nerve fibres in vivo. Although the CCM technique is in constant progress, there are methodological limitations in terms of sampling of images and objectivity of the nerve quantification. The aim of this study was to present a randomized sampling method of the CCM images and to develop an adjusted area-dependent image analysis. Furthermore, a manual nerve fibre analysis method was compared to a fully automated method. 23 idiopathic small-fibre neuropathy patients were investigated using CCM. Corneal nerve fibre length density (CNFL) and corneal nerve fibre branch density (CNBD) were determined in both a manual and automatic manner. Differences in CNFL and CNBD between (1) the randomized and the most common sampling method, (2) the adjusted and the unadjusted area and (3) the manual and automated quantification method were investigated. The CNFL values were significantly lower when using the randomized sampling method compared to the most common method (p = 0.01). There was not a statistical significant difference in the CNBD values between the randomized and the most common sampling method (p = 0.85). CNFL and CNBD values were increased when using the adjusted area compared to the standard area. Additionally, the study found a significant increase in the CNFL and CNBD values when using the manual method compared to the automatic method (p ≤ 0.001). The study demonstrated a significant difference in the CNFL values between the randomized and common sampling method indicating the importance of clear guidelines for the image sampling. The increase in CNFL and CNBD values when using the adjusted cornea area is not surprising. The observed increases in both CNFL and CNBD values when using the manual method of nerve quantification compared to the automatic method are consistent with earlier findings. This study underlines the importance of improving the analysis of the

  8. a Hyperspectral Image Classification Method Using Isomap and Rvm

    Science.gov (United States)

    Chang, H.; Wang, T.; Fang, H.; Su, Y.

    2018-04-01

    Classification is one of the most significant applications of hyperspectral image processing and even remote sensing. Though various algorithms have been proposed to implement and improve this application, there are still drawbacks in traditional classification methods. Thus further investigations on some aspects, such as dimension reduction, data mining, and rational use of spatial information, should be developed. In this paper, we used a widely utilized global manifold learning approach, isometric feature mapping (ISOMAP), to address the intrinsic nonlinearities of hyperspectral image for dimension reduction. Considering the impropriety of Euclidean distance in spectral measurement, we applied spectral angle (SA) for substitute when constructed the neighbourhood graph. Then, relevance vector machines (RVM) was introduced to implement classification instead of support vector machines (SVM) for simplicity, generalization and sparsity. Therefore, a probability result could be obtained rather than a less convincing binary result. Moreover, taking into account the spatial information of the hyperspectral image, we employ a spatial vector formed by different classes' ratios around the pixel. At last, we combined the probability results and spatial factors with a criterion to decide the final classification result. To verify the proposed method, we have implemented multiple experiments with standard hyperspectral images compared with some other methods. The results and different evaluation indexes illustrated the effectiveness of our method.

  9. Stokes vector based interpolation method to improve the efficiency of bio-inspired polarization-difference imaging in turbid media

    Science.gov (United States)

    Guan, Jinge; Ren, Wei; Cheng, Yaoyu

    2018-04-01

    We demonstrate an efficient polarization-difference imaging system in turbid conditions by using the Stokes vector of light. The interaction of scattered light with the polarizer is analyzed by the Stokes-Mueller formalism. An interpolation method is proposed to replace the mechanical rotation of the polarization axis of the analyzer theoretically, and its performance is verified by the experiment at different turbidity levels. We show that compared with direct imaging, the Stokes vector based imaging method can effectively reduce the effect of light scattering and enhance the image contrast.

  10. Improving Conductivity Image Quality Using Block Matrix-based Multiple Regularization (BMMR Technique in EIT: A Simulation Study

    Directory of Open Access Journals (Sweden)

    Tushar Kanti Bera

    2011-06-01

    Full Text Available A Block Matrix based Multiple Regularization (BMMR technique is proposed for improving conductivity image quality in EIT. The response matrix (JTJ has been partitioned into several sub-block matrices and the highest eigenvalue of each sub-block matrices has been chosen as regularization parameter for the nodes contained by that sub-block. Simulated boundary data are generated for circular domain with circular inhomogeneity and the conductivity images are reconstructed in a Model Based Iterative Image Reconstruction (MoBIIR algorithm. Conductivity images are reconstructed with BMMR technique and the results are compared with the Single-step Tikhonov Regularization (STR and modified Levenberg-Marquardt Regularization (LMR methods. It is observed that the BMMR technique reduces the projection error and solution error and improves the conductivity reconstruction in EIT. Result show that the BMMR method also improves the image contrast and inhomogeneity conductivity profile and hence the reconstructed image quality is enhanced. ;doi:10.5617/jeb.170 J Electr Bioimp, vol. 2, pp. 33-47, 2011

  11. Improvement of Secret Image Invisibility in Circulation Image with Dyadic Wavelet Based Data Hiding with Run-Length Coded Secret Images of Which Location of Codes are Determined with Random Number

    OpenAIRE

    Kohei Arai; Yuji Yamada

    2011-01-01

    An attempt is made for improvement of secret image invisibility in circulation images with dyadic wavelet based data hiding with run-length coded secret images of which location of codes are determined by random number. Through experiments, it is confirmed that secret images are almost invisible in circulation images. Also robustness of the proposed data hiding method against data compression of circulation images is discussed. Data hiding performance in terms of invisibility of secret images...

  12. Image splitting and remapping method for radiological image compression

    Science.gov (United States)

    Lo, Shih-Chung B.; Shen, Ellen L.; Mun, Seong K.

    1990-07-01

    A new decomposition method using image splitting and gray-level remapping has been proposed for image compression, particularly for images with high contrast resolution. The effects of this method are especially evident in our radiological image compression study. In our experiments, we tested the impact of this decomposition method on image compression by employing it with two coding techniques on a set of clinically used CT images and several laser film digitized chest radiographs. One of the compression techniques used was full-frame bit-allocation in the discrete cosine transform domain, which has been proven to be an effective technique for radiological image compression. The other compression technique used was vector quantization with pruned tree-structured encoding, which through recent research has also been found to produce a low mean-square-error and a high compression ratio. The parameters we used in this study were mean-square-error and the bit rate required for the compressed file. In addition to these parameters, the difference between the original and reconstructed images will be presented so that the specific artifacts generated by both techniques can be discerned by visual perception.

  13. Improving Signal-to-Noise Ratio in Susceptibility Weighted Imaging: A Novel Multicomponent Non-Local Approach.

    Directory of Open Access Journals (Sweden)

    Pasquale Borrelli

    Full Text Available In susceptibility-weighted imaging (SWI, the high resolution required to obtain a proper contrast generation leads to a reduced signal-to-noise ratio (SNR. The application of a denoising filter to produce images with higher SNR and still preserve small structures from excessive blurring is therefore extremely desirable. However, as the distributions of magnitude and phase noise may introduce biases during image restoration, the application of a denoising filter is non-trivial. Taking advantage of the potential multispectral nature of MR images, a multicomponent approach using a Non-Local Means (MNLM denoising filter may perform better than a component-by-component image restoration method. Here we present a new MNLM-based method (Multicomponent-Imaginary-Real-SWI, hereafter MIR-SWI to produce SWI images with high SNR and improved conspicuity. Both qualitative and quantitative comparisons of MIR-SWI with the original SWI scheme and previously proposed SWI restoring pipelines showed that MIR-SWI fared consistently better than the other approaches. Noise removal with MIR-SWI also provided improvement in contrast-to-noise ratio (CNR and vessel conspicuity at higher factors of phase mask multiplications than the one suggested in the literature for SWI vessel imaging. We conclude that a proper handling of noise in the complex MR dataset may lead to improved image quality for SWI data.

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

    Science.gov (United States)

    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.

  15. Optimized lighting method of applying shaped-function signal for increasing the dynamic range of LED-multispectral imaging system

    Science.gov (United States)

    Yang, Xue; Hu, Yajia; Li, Gang; Lin, Ling

    2018-02-01

    This paper proposes an optimized lighting method of applying a shaped-function signal for increasing the dynamic range of light emitting diode (LED)-multispectral imaging system. The optimized lighting method is based on the linear response zone of the analog-to-digital conversion (ADC) and the spectral response of the camera. The auxiliary light at a higher sensitivity-camera area is introduced to increase the A/D quantization levels that are within the linear response zone of ADC and improve the signal-to-noise ratio. The active light is modulated by the shaped-function signal to improve the gray-scale resolution of the image. And the auxiliary light is modulated by the constant intensity signal, which is easy to acquire the images under the active light irradiation. The least square method is employed to precisely extract the desired images. One wavelength in multispectral imaging based on LED illumination was taken as an example. It has been proven by experiments that the gray-scale resolution and the accuracy of information of the images acquired by the proposed method were both significantly improved. The optimum method opens up avenues for the hyperspectral imaging of biological tissue.

  16. Panorama parking assistant system with improved particle swarm optimization method

    Science.gov (United States)

    Cheng, Ruzhong; Zhao, Yong; Li, Zhichao; Jiang, Weigang; Wang, Xin'an; Xu, Yong

    2013-10-01

    A panorama parking assistant system (PPAS) for the automotive aftermarket together with a practical improved particle swarm optimization method (IPSO) are proposed in this paper. In the PPAS system, four fisheye cameras are installed in the vehicle with different views, and four channels of video frames captured by the cameras are processed as a 360-deg top-view image around the vehicle. Besides the embedded design of PPAS, the key problem for image distortion correction and mosaicking is the efficiency of parameter optimization in the process of camera calibration. In order to address this problem, an IPSO method is proposed. Compared with other parameter optimization methods, the proposed method allows a certain range of dynamic change for the intrinsic and extrinsic parameters, and can exploit only one reference image to complete all of the optimization; therefore, the efficiency of the whole camera calibration is increased. The PPAS is commercially available, and the IPSO method is a highly practical way to increase the efficiency of the installation and the calibration of PPAS in automobile 4S shops.

  17. Advances and Perspectives in Chemical Imaging in Cellular Environments Using Electrochemical Methods

    Directory of Open Access Journals (Sweden)

    Robert A. Lazenby

    2018-05-01

    Full Text Available This review discusses a broad range of recent advances (2013–2017 in chemical imaging using electrochemical methods, with a particular focus on techniques that have been applied to study cellular processes, or techniques that show promise for use in this field in the future. Non-scanning techniques such as microelectrode arrays (MEAs offer high time-resolution (<10 ms imaging; however, at reduced spatial resolution. In contrast, scanning electrochemical probe microscopies (SEPMs offer higher spatial resolution (as low as a few nm per pixel imaging, with images collected typically over many minutes. Recent significant research efforts to improve the spatial resolution of SEPMs using nanoscale probes and to improve the temporal resolution using fast scanning have resulted in movie (multiple frame imaging with frame rates as low as a few seconds per image. Many SEPM techniques lack chemical specificity or have poor selectivity (defined by the choice of applied potential for redox-active species. This can be improved using multifunctional probes, ion-selective electrodes and tip-integrated biosensors, although additional effort may be required to preserve sensor performance after miniaturization of these probes. We discuss advances to the field of electrochemical imaging, and technological developments which are anticipated to extend the range of processes that can be studied. This includes imaging cellular processes with increased sensor selectivity and at much improved spatiotemporal resolution than has been previously customary.

  18. Improved proton computed tomography by dual modality image reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    Hansen, David C., E-mail: dch@ki.au.dk; Bassler, Niels [Experimental Clinical Oncology, Aarhus University, 8000 Aarhus C (Denmark); Petersen, Jørgen Breede Baltzer [Medical Physics, Aarhus University Hospital, 8000 Aarhus C (Denmark); Sørensen, Thomas Sangild [Computer Science, Aarhus University, 8000 Aarhus C, Denmark and Clinical Medicine, Aarhus University, 8200 Aarhus N (Denmark)

    2014-03-15

    Purpose: Proton computed tomography (CT) is a promising image modality for improving the stopping power estimates and dose calculations for particle therapy. However, the finite range of about 33 cm of water of most commercial proton therapy systems limits the sites that can be scanned from a full 360° rotation. In this paper the authors propose a method to overcome the problem using a dual modality reconstruction (DMR) combining the proton data with a cone-beam x-ray prior. Methods: A Catphan 600 phantom was scanned using a cone beam x-ray CT scanner. A digital replica of the phantom was created in the Monte Carlo code Geant4 and a 360° proton CT scan was simulated, storing the entrance and exit position and momentum vector of every proton. Proton CT images were reconstructed using a varying number of angles from the scan. The proton CT images were reconstructed using a constrained nonlinear conjugate gradient algorithm, minimizing total variation and the x-ray CT prior while remaining consistent with the proton projection data. The proton histories were reconstructed along curved cubic-spline paths. Results: The spatial resolution of the cone beam CT prior was retained for the fully sampled case and the 90° interval case, with the MTF = 0.5 (modulation transfer function) ranging from 5.22 to 5.65 linepairs/cm. In the 45° interval case, the MTF = 0.5 dropped to 3.91 linepairs/cm For the fully sampled DMR, the maximal root mean square (RMS) error was 0.006 in units of relative stopping power. For the limited angle cases the maximal RMS error was 0.18, an almost five-fold improvement over the cone beam CT estimate. Conclusions: Dual modality reconstruction yields the high spatial resolution of cone beam x-ray CT while maintaining the improved stopping power estimation of proton CT. In the case of limited angles, the use of prior image proton CT greatly improves the resolution and stopping power estimate, but does not fully achieve the quality of a 360

  19. Improved proton computed tomography by dual modality image reconstruction

    International Nuclear Information System (INIS)

    Hansen, David C.; Bassler, Niels; Petersen, Jørgen Breede Baltzer; Sørensen, Thomas Sangild

    2014-01-01

    Purpose: Proton computed tomography (CT) is a promising image modality for improving the stopping power estimates and dose calculations for particle therapy. However, the finite range of about 33 cm of water of most commercial proton therapy systems limits the sites that can be scanned from a full 360° rotation. In this paper the authors propose a method to overcome the problem using a dual modality reconstruction (DMR) combining the proton data with a cone-beam x-ray prior. Methods: A Catphan 600 phantom was scanned using a cone beam x-ray CT scanner. A digital replica of the phantom was created in the Monte Carlo code Geant4 and a 360° proton CT scan was simulated, storing the entrance and exit position and momentum vector of every proton. Proton CT images were reconstructed using a varying number of angles from the scan. The proton CT images were reconstructed using a constrained nonlinear conjugate gradient algorithm, minimizing total variation and the x-ray CT prior while remaining consistent with the proton projection data. The proton histories were reconstructed along curved cubic-spline paths. Results: The spatial resolution of the cone beam CT prior was retained for the fully sampled case and the 90° interval case, with the MTF = 0.5 (modulation transfer function) ranging from 5.22 to 5.65 linepairs/cm. In the 45° interval case, the MTF = 0.5 dropped to 3.91 linepairs/cm For the fully sampled DMR, the maximal root mean square (RMS) error was 0.006 in units of relative stopping power. For the limited angle cases the maximal RMS error was 0.18, an almost five-fold improvement over the cone beam CT estimate. Conclusions: Dual modality reconstruction yields the high spatial resolution of cone beam x-ray CT while maintaining the improved stopping power estimation of proton CT. In the case of limited angles, the use of prior image proton CT greatly improves the resolution and stopping power estimate, but does not fully achieve the quality of a 360

  20. Development and evaluation of a novel lossless image compression method (AIC: artificial intelligence compression method) using neural networks as artificial intelligence

    International Nuclear Information System (INIS)

    Fukatsu, Hiroshi; Naganawa, Shinji; Yumura, Shinnichiro

    2008-01-01

    This study was aimed to validate the performance of a novel image compression method using a neural network to achieve a lossless compression. The encoding consists of the following blocks: a prediction block; a residual data calculation block; a transformation and quantization block; an organization and modification block; and an entropy encoding block. The predicted image is divided into four macro-blocks using the original image for teaching; and then redivided into sixteen sub-blocks. The predicted image is compared to the original image to create the residual image. The spatial and frequency data of the residual image are compared and transformed. Chest radiography, computed tomography (CT), magnetic resonance imaging, positron emission tomography, radioisotope mammography, ultrasonography, and digital subtraction angiography images were compressed using the AIC lossless compression method; and the compression rates were calculated. The compression rates were around 15:1 for chest radiography and mammography, 12:1 for CT, and around 6:1 for other images. This method thus enables greater lossless compression than the conventional methods. This novel method should improve the efficiency of handling of the increasing volume of medical imaging data. (author)

  1. Image registration method for medical image sequences

    Science.gov (United States)

    Gee, Timothy F.; Goddard, James S.

    2013-03-26

    Image registration of low contrast image sequences is provided. In one aspect, a desired region of an image is automatically segmented and only the desired region is registered. Active contours and adaptive thresholding of intensity or edge information may be used to segment the desired regions. A transform function is defined to register the segmented region, and sub-pixel information may be determined using one or more interpolation methods.

  2. An Improved Method to Watermark Images Sensitive to Blocking Artifacts

    OpenAIRE

    Afzel Noore

    2007-01-01

    A new digital watermarking technique for images that are sensitive to blocking artifacts is presented. Experimental results show that the proposed MDCT based approach produces highly imperceptible watermarked images and is robust to attacks such as compression, noise, filtering and geometric transformations. The proposed MDCT watermarking technique is applied to fingerprints for ensuring security. The face image and demographic text data of an individual are used as multi...

  3. REVIEW OF MATHEMATICAL METHODS AND ALGORITHMS OF MEDICAL IMAGE PROCESSING ON THE EXAMPLE OF TECHNOLOGY OF MEDICAL IMAGE PROCESSING FROM WOLFRAM MATHEMATICA

    Directory of Open Access Journals (Sweden)

    О. E. Prokopchenko

    2015-09-01

    Full Text Available The article analyzes the basic methods and algorithms of mathematical processing of medical images as objects of computer mathematics. The presented methods and computer algorithms of mathematics relevant and may find application in the field of medical imaging - automated processing of images; as a tool for measurement and determination the optical parameters; identification and formation of medical images database. Methods and computer algorithms presented in the article & based on Wolfram Mathematica are also relevant to the problem of modern medical education. As an example of Wolfram Mathematica may be considered appropriate demonstration, such as recognition of special radiographs and morphological imaging. These methods are used to improve the diagnostic significance and value of medical (clinical research and can serve as an educational interactive demonstration. Implementation submitted individual methods and algorithms of computer Wolfram Mathematics contributes, in general, the optimization process of practical processing and presentation of medical images.

  4. Classification Method in Integrated Information Network Using Vector Image Comparison

    Directory of Open Access Journals (Sweden)

    Zhou Yuan

    2014-05-01

    Full Text Available Wireless Integrated Information Network (WMN consists of integrated information that can get data from its surrounding, such as image, voice. To transmit information, large resource is required which decreases the service time of the network. In this paper we present a Classification Approach based on Vector Image Comparison (VIC for WMN that improve the service time of the network. The available methods for sub-region selection and conversion are also proposed.

  5. Improving the image quality of contrast-enhanced MR angiography by automated image registration: A prospective study in peripheral arterial disease of the lower extremities

    International Nuclear Information System (INIS)

    Menke, Jan

    2010-01-01

    Objective: If a patient has moved during digital subtraction angiography (DSA), manual pixel shift can improve the image quality. This study investigated whether such image registration can also improve the quality of contrast-enhanced magnetic resonance angiography (MRA) in patients with peripheral arterial disease of the lower extremities. Materials and methods: 404 leg MRAs of patients likely to have peripheral artery disease were included in this prospective study. The standard non-registered MRAs were compared to automatically linear, affine and warp registered MRAs by four image quality parameters, including the vessel detection probability (VDP) in maximum intensity projection (MIP) images and contrast-to-noise ratios (CNR). The different registration types were compared by analysis of variance. Results: All studied image quality parameters showed similar trends. Generally, registration improved the leg MRA quality significantly (P < 0.05). The 12% of lower legs with a body shift of 1 mm or more showed the highest gain in image quality when using linear registration instead of no registration, with an average VDP gain of 20-49%. Warp registration improved the image quality slightly further. Conclusion: Automated image registration can improve the MRA image quality especially in the lower legs, which is comparable to the effect of pixel shift in DSA.

  6. Improved cancer diagnostics by different image processing techniques on OCT images

    Science.gov (United States)

    Kanawade, Rajesh; Lengenfelder, Benjamin; Marini Menezes, Tassiana; Hohmann, Martin; Kopfinger, Stefan; Hohmann, Tim; Grabiec, Urszula; Klämpfl, Florian; Gonzales Menezes, Jean; Waldner, Maximilian; Schmidt, Michael

    2015-07-01

    Optical-coherence tomography (OCT) is a promising non-invasive, high-resolution imaging modality which can be used for cancer diagnosis and its therapeutic assessment. However, speckle noise makes detection of cancer boundaries and image segmentation problematic and unreliable. Therefore, to improve the image analysis for a precise cancer border detection, the performance of different image processing algorithms such as mean, median, hybrid median filter and rotational kernel transformation (RKT) for this task is investigated. This is done on OCT images acquired from an ex-vivo human cancerous mucosa and in vitro by using cultivated tumour applied on organotypical hippocampal slice cultures. The preliminary results confirm that the border between the healthy and the cancer lesions can be identified precisely. The obtained results are verified with fluorescence microscopy. This research can improve cancer diagnosis and the detection of borders between healthy and cancerous tissue. Thus, it could also reduce the number of biopsies required during screening endoscopy by providing better guidance to the physician.

  7. Improving image quality for digital breast tomosynthesis: an automated detection and diffusion-based method for metal artifact reduction

    Science.gov (United States)

    Lu, Yao; Chan, Heang-Ping; Wei, Jun; Hadjiiski, Lubomir M.; Samala, Ravi K.

    2017-10-01

    In digital breast tomosynthesis (DBT), the high-attenuation metallic clips marking a previous biopsy site in the breast cause errors in the estimation of attenuation along the ray paths intersecting the markers during reconstruction, which result in interplane and inplane artifacts obscuring the visibility of subtle lesions. We proposed a new metal artifact reduction (MAR) method to improve image quality. Our method uses automatic detection and segmentation to generate a marker location map for each projection (PV). A voting technique based on the geometric correlation among different PVs is designed to reduce false positives (FPs) and to label the pixels on the PVs and the voxels in the imaged volume that represent the location and shape of the markers. An iterative diffusion method replaces the labeled pixels on the PVs with estimated tissue intensity from the neighboring regions while preserving the original pixel values in the neighboring regions. The inpainted PVs are then used for DBT reconstruction. The markers are repainted on the reconstructed DBT slices for radiologists’ information. The MAR method is independent of reconstruction techniques or acquisition geometry. For the training set, the method achieved 100% success rate with one FP in 19 views. For the test set, the success rate by view was 97.2% for core biopsy microclips and 66.7% for clusters of large post-lumpectomy markers with a total of 10 FPs in 58 views. All FPs were large dense benign calcifications that also generated artifacts if they were not corrected by MAR. For the views with successful detection, the metal artifacts were reduced to a level that was not visually apparent in the reconstructed slices. The visibility of breast lesions obscured by the reconstruction artifacts from the metallic markers was restored.

  8. Full-direct method for imaging pharmacokinetic parameters in dynamic fluorescence molecular tomography

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Guanglei, E-mail: guangleizhang@bjtu.edu.cn [Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084 (China); Department of Biomedical Engineering, School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044 (China); Pu, Huangsheng; Liu, Fei; Bai, Jing [Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084 (China); He, Wei [China Institute of Sport Science, Beijing 100061 (China); Luo, Jianwen, E-mail: luo-jianwen@tsinghua.edu.cn [Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084 (China); Center for Biomedical Imaging Research, School of Medicine, Tsinghua University, Beijing 100084 (China)

    2015-02-23

    Images of pharmacokinetic parameters (also known as parametric images) in dynamic fluorescence molecular tomography (FMT) can provide three-dimensional metabolic information for biological studies and drug development. However, the ill-posed nature of FMT and the high temporal variation of fluorophore concentration together make it difficult to obtain accurate parametric images in small animals in vivo. In this letter, we present a method to directly reconstruct the parametric images from the boundary measurements based on hybrid FMT/X-ray computed tomography (XCT) system. This method can not only utilize structural priors obtained from the XCT system to mitigate the ill-posedness of FMT but also make full use of the temporal correlations of boundary measurements to model the high temporal variation of fluorophore concentration. The results of numerical simulation and mouse experiment demonstrate that the proposed method leads to significant improvements in the reconstruction quality of parametric images.

  9. Twin-Foucault imaging method

    Science.gov (United States)

    Harada, Ken

    2012-02-01

    A method of Lorentz electron microscopy, which enables observation two Foucault images simultaneously by using an electron biprism instead of an objective aperture, was developed. The electron biprism is installed between two electron beams deflected by 180° magnetic domains. Potential applied to the biprism deflects the two electron beams further, and two Foucault images with reversed contrast are then obtained in one visual field. The twin Foucault images are able to extract the magnetic domain structures and to reconstruct an ordinary electron micrograph. The developed Foucault method was demonstrated with a 180° domain structure of manganite La0.825Sr0.175MnO3.

  10. Structured sparse canonical correlation analysis for brain imaging genetics: an improved GraphNet method.

    Science.gov (United States)

    Du, Lei; Huang, Heng; Yan, Jingwen; Kim, Sungeun; Risacher, Shannon L; Inlow, Mark; Moore, Jason H; Saykin, Andrew J; Shen, Li

    2016-05-15

    Structured sparse canonical correlation analysis (SCCA) models have been used to identify imaging genetic associations. These models either use group lasso or graph-guided fused lasso to conduct feature selection and feature grouping simultaneously. The group lasso based methods require prior knowledge to define the groups, which limits the capability when prior knowledge is incomplete or unavailable. The graph-guided methods overcome this drawback by using the sample correlation to define the constraint. However, they are sensitive to the sign of the sample correlation, which could introduce undesirable bias if the sign is wrongly estimated. We introduce a novel SCCA model with a new penalty, and develop an efficient optimization algorithm. Our method has a strong upper bound for the grouping effect for both positively and negatively correlated features. We show that our method performs better than or equally to three competing SCCA models on both synthetic and real data. In particular, our method identifies stronger canonical correlations and better canonical loading patterns, showing its promise for revealing interesting imaging genetic associations. The Matlab code and sample data are freely available at http://www.iu.edu/∼shenlab/tools/angscca/ shenli@iu.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  11. An evaluation on CT image acquisition method for medical VR applications

    Science.gov (United States)

    Jang, Seong-wook; Ko, Junho; Yoo, Yon-sik; Kim, Yoonsang

    2017-02-01

    Recent medical virtual reality (VR) applications to minimize re-operations are being studied for improvements in surgical efficiency and reduction of operation error. The CT image acquisition method considering three-dimensional (3D) modeling for medical VR applications is important, because the realistic model is required for the actual human organ. However, the research for medical VR applications has focused on 3D modeling techniques and utilized 3D models. In addition, research on a CT image acquisition method considering 3D modeling has never been reported. The conventional CT image acquisition method involves scanning a limited area of the lesion for the diagnosis of doctors once or twice. However, the medical VR application is required to acquire the CT image considering patients' various postures and a wider area than the lesion. A wider area than the lesion is required because of the necessary process of comparing bilateral sides for dyskinesia diagnosis of the shoulder, pelvis, and leg. Moreover, patients' various postures are required due to the different effects on the musculoskeletal system. Therefore, in this paper, we perform a comparative experiment on the acquired CT images considering image area (unilateral/bilateral) and patients' postures (neutral/abducted). CT images are acquired from 10 patients for the experiments, and the acquired CT images are evaluated based on the length per pixel and the morphological deviation. Finally, by comparing the experiment results, we evaluate the CT image acquisition method for medical VR applications.

  12. An age estimation method using brain local features for T1-weighted images.

    Science.gov (United States)

    Kondo, Chihiro; Ito, Koichi; Kai Wu; Sato, Kazunori; Taki, Yasuyuki; Fukuda, Hiroshi; Aoki, Takafumi

    2015-08-01

    Previous statistical analysis studies using large-scale brain magnetic resonance (MR) image databases have examined that brain tissues have age-related morphological changes. This fact indicates that one can estimate the age of a subject from his/her brain MR image by evaluating morphological changes with healthy aging. This paper proposes an age estimation method using local features extracted from T1-weighted MR images. The brain local features are defined by volumes of brain tissues parcellated into local regions defined by the automated anatomical labeling atlas. The proposed method selects optimal local regions to improve the performance of age estimation. We evaluate performance of the proposed method using 1,146 T1-weighted images from a Japanese MR image database. We also discuss the medical implication of selected optimal local regions.

  13. Improvements in the image quality of ventilatory tomograms by electrical impedance tomography

    International Nuclear Information System (INIS)

    Hahn, G; Dittmar, J; Just, A; Hellige, G

    2008-01-01

    We present an improved approach to image ventilation in functional electrical impedance tomography (f-EIT). It combines the advantages of the two established procedures of calculating standard deviation as a functional parameter of ventilation (SD method) and the so-called filling capacity (FC method). The SD method quantifies the local impedance variation over a series of tomograms for each pixel; the FC method is based on the slope of a linear fit of regional versus the global impedance change. Tidal volume V T is displayed linearly by the SD method in f-EIT; it is, however, sensitive to noisy data. The FC method is much more robust with respect to noise but does not display the tidal volume V T . We combined the advantages of both techniques in a new VT method which is based on raw data. It saves computing time and is suitable for both f-EIT and absolute EIT (a-EIT). We separated the raw data into two representative sets: end expiratory and end inspiratory. This was accomplished by calculating the global time course of the relative impedance changes from the raw data. In this time course, we determined all frame numbers (indices) of end expiration and end inspiration. These frame numbers were used to calculate one mean expiratory and one mean inspiratory raw data frame. Reconstruction by difference imaging directly reflects the mean tidal volume V T during the acquired frame series. The effect of the improvement by the VT method was investigated at different noise levels by adding artificial noise from 0 to 100 µV rms to a real raw dataset. The robustness with regard to noise of the VT method was similar to that of the FC method. The practical value of suppression of non-ventilatory impedance changes, artefacts and noise was tested by studying ten healthy subjects (four females, six males) during normal breathing. We found a highly significant improvement in the image quality (p < 0.001) of ventilation for this group of volunteers

  14. The method for detecting small lesions in medical image based on sliding window

    Science.gov (United States)

    Han, Guilai; Jiao, Yuan

    2016-10-01

    At present, the research on computer-aided diagnosis includes the sample image segmentation, extracting visual features, generating the classification model by learning, and according to the model generated to classify and judge the inspected images. However, this method has a large scale of calculation and speed is slow. And because medical images are usually low contrast, when the traditional image segmentation method is applied to the medical image, there is a complete failure. As soon as possible to find the region of interest, improve detection speed, this topic attempts to introduce the current popular visual attention model into small lesions detection. However, Itti model is mainly for natural images. But the effect is not ideal when it is used to medical images which usually are gray images. Especially in the early stages of some cancers, the focus of a disease in the whole image is not the most significant region and sometimes is very difficult to be found. But these lesions are prominent in the local areas. This paper proposes a visual attention mechanism based on sliding window, and use sliding window to calculate the significance of a local area. Combined with the characteristics of the lesion, select the features of gray, entropy, corner and edge to generate a saliency map. Then the significant region is segmented and distinguished. This method reduces the difficulty of image segmentation, and improves the detection accuracy of small lesions, and it has great significance to early discovery, early diagnosis and treatment of cancers.

  15. Superiority Of Graph-Based Visual Saliency GVS Over Other Image Segmentation Methods

    Directory of Open Access Journals (Sweden)

    Umu Lamboi

    2017-02-01

    Full Text Available Although inherently tedious the segmentation of images and the evaluation of segmented images are critical in computer vision processes. One of the main challenges in image segmentation evaluation arises from the basic conflict between generality and objectivity. For general segmentation purposes the lack of well-defined ground-truth and segmentation accuracy limits the evaluation of specific applications. Subjectivity is the most common method of evaluation of segmentation quality where segmented images are visually compared. This is daunting task however limits the scope of segmentation evaluation to a few predetermined sets of images. As an alternative supervised evaluation compares segmented images against manually-segmented or pre-processed benchmark images. Not only good evaluation methods allow for different comparisons but also for integration with target recognition systems for adaptive selection of appropriate segmentation granularity with improved recognition accuracy. Most of the current segmentation methods still lack satisfactory measures of effectiveness. Thus this study proposed a supervised framework which uses visual saliency detection to quantitatively evaluate image segmentation quality. The new benchmark evaluator uses Graph-based Visual Saliency GVS to compare boundary outputs for manually segmented images. Using the Berkeley Segmentation Database the proposed algorithm was tested against 4 other quantitative evaluation methods Probabilistic Rand Index PRI Variation of Information VOI Global Consistency Error GSE and Boundary Detection Error BDE. Based on the results the GVS approach outperformed any of the other 4 independent standard methods in terms of visual saliency detection of images.

  16. Recommendations to improve imaging and analysis of brain lesion load and atrophy in longitudinal studies of multiple sclerosis

    DEFF Research Database (Denmark)

    Vrenken, H; Jenkinson, M; Horsfield, M A

    2013-01-01

    resonance image analysis methods for assessing brain lesion load and atrophy, this paper makes recommendations to improve these measures for longitudinal studies of MS. Briefly, they are (1) images should be acquired using 3D pulse sequences, with near-isotropic spatial resolution and multiple image......Focal lesions and brain atrophy are the most extensively studied aspects of multiple sclerosis (MS), but the image acquisition and analysis techniques used can be further improved, especially those for studying within-patient changes of lesion load and atrophy longitudinally. Improved accuracy...

  17. REVIEW OF MATHEMATICAL METHODS AND ALGORITHMS OF MEDICAL IMAGE PROCESSING ON THE EXAMPLE OF TECHNOLOGY OF MEDICAL IMAGE PROCESSING FROM WOLFRAM MATHEMATICS

    Directory of Open Access Journals (Sweden)

    O. Ye. Prokopchenko

    2015-10-01

    Full Text Available The article analyzes the basic methods and algorithms of mathematical processing of medical images as objects of computer mathematics. The presented methods and computer algorithms of mathematics relevant and may find application in the field of medical imaging - automated processing of images; as a tool for measurement and determination the optical parameters; identification and formation of medical images database. Methods and computer algorithms presented in the article and based on Wolfram Mathematica are also relevant to the problem of modern medical education. As an example of Wolfram Mathematics may be considered appropriate demonstration, such as recognition of special radiographs and morphological imaging. These methods are used to improve  the diagnostic significance and value of medical (clinical research and can serve as an educational interactive demonstration. Implementation submitted individual methods and algorithms of computer Wolfram Mathematics contributes, in general, the optimization process of practical processing and presentation of medical images.

  18. A three-frame digital image correlation (DIC) method for the measurement of small displacements and strains

    International Nuclear Information System (INIS)

    Cofaru, C; Philips, W; Van Paepegem, W

    2012-01-01

    Digital image correlation (DIC) has become a well-established approach for the calculation of full-field displacement and strains within the field of experimental mechanics. Since their introduction, DIC methods have been relying on only two images to measure the displacements and strains that materials undergo under load. It can be foreseen that the use of additional image information for the calculus of displacements and strains, although computationally more expensive, can positively impact DIC method accuracy under both ideal and challenging experimental conditions. Such accuracy improvements are especially important when measuring very small deformations, which still constitutes a great challenge: small displacements and strains translate into equally small digital image intensity changes on the material’s surface, which are affected by the digitization processes of the imaging hardware and by other image acquisition effects such as image noise. This paper proposes a new three-frame Newton–Raphson DIC method and evaluates it from the standpoints of accuracy and speed. The method models the deformations that are to be measured under the assumption that the deformation occurs at approximately the same rate between each two consecutive images in the three image sequences that are employed. The aim is to investigate how the use of image data from more than two images impacts accuracy and what is the effect on the computational speed. The proposed method is compared with the classic two-frame Newton–Raphson method in three experiments. Two experiments rely on numerically deformed images that simulate heterogeneous deformations. The third experiment uses images from a real deformation experiment. Results indicate that although it is computationally more demanding, the three-frame method significantly improves displacement and strain accuracy and is less sensitive to image noise. (paper)

  19. Methods in Astronomical Image Processing

    Science.gov (United States)

    Jörsäter, S.

    A Brief Introductory Note History of Astronomical Imaging Astronomical Image Data Images in Various Formats Digitized Image Data Digital Image Data Philosophy of Astronomical Image Processing Properties of Digital Astronomical Images Human Image Processing Astronomical vs. Computer Science Image Processing Basic Tools of Astronomical Image Processing Display Applications Calibration of Intensity Scales Calibration of Length Scales Image Re-shaping Feature Enhancement Noise Suppression Noise and Error Analysis Image Processing Packages: Design of AIPS and MIDAS AIPS MIDAS Reduction of CCD Data Bias Subtraction Clipping Preflash Subtraction Dark Subtraction Flat Fielding Sky Subtraction Extinction Correction Deconvolution Methods Rebinning/Combining Summary and Prospects for the Future

  20. An improved method for estimating capillary pressure from 3D microtomography images and its application to the study of disconnected nonwetting phase

    Science.gov (United States)

    Li, Tianyi; Schlüter, Steffen; Dragila, Maria Ines; Wildenschild, Dorthe

    2018-04-01

    We present an improved method for estimating interfacial curvatures from x-ray computed microtomography (CMT) data that significantly advances the potential for this tool to unravel the mechanisms and phenomena associated with multi-phase fluid motion in porous media. CMT data, used to analyze the spatial distribution and capillary pressure-saturation (Pc-S) relationships of liquid phases, requires accurate estimates of interfacial curvature. Our improved method for curvature estimation combines selective interface modification and distance weighting approaches. It was verified against synthetic (analytical computer-generated) and real image data sets, demonstrating a vast improvement over previous methods. Using this new tool on a previously published data set (multiphase flow) yielded important new insights regarding the pressure state of the disconnected nonwetting phase during drainage and imbibition. The trapped and disconnected non-wetting phase delimits its own hysteretic Pc-S curve that inhabits the space within the main hysteretic Pc-S loop of the connected wetting phase. Data suggests that the pressure of the disconnected, non-wetting phase is strongly modified by the pore geometry rather than solely by the bulk liquid phase that surrounds it.

  1. An improved ASIFT algorithm for indoor panorama image matching

    Science.gov (United States)

    Fu, Han; Xie, Donghai; Zhong, Ruofei; Wu, Yu; Wu, Qiong

    2017-07-01

    The generation of 3D models for indoor objects and scenes is an attractive tool for digital city, virtual reality and SLAM purposes. Panoramic images are becoming increasingly more common in such applications due to their advantages to capture the complete environment in one single image with large field of view. The extraction and matching of image feature points are important and difficult steps in three-dimensional reconstruction, and ASIFT is a state-of-the-art algorithm to implement these functions. Compared with the SIFT algorithm, more feature points can be generated and the matching accuracy of ASIFT algorithm is higher, even for the panoramic images with obvious distortions. However, the algorithm is really time-consuming because of complex operations and performs not very well for some indoor scenes under poor light or without rich textures. To solve this problem, this paper proposes an improved ASIFT algorithm for indoor panoramic images: firstly, the panoramic images are projected into multiple normal perspective images. Secondly, the original ASIFT algorithm is simplified from the affine transformation of tilt and rotation with the images to the only tilt affine transformation. Finally, the results are re-projected to the panoramic image space. Experiments in different environments show that this method can not only ensure the precision of feature points extraction and matching, but also greatly reduce the computing time.

  2. Digital image processing mathematical and computational methods

    CERN Document Server

    Blackledge, J M

    2005-01-01

    This authoritative text (the second part of a complete MSc course) provides mathematical methods required to describe images, image formation and different imaging systems, coupled with the principle techniques used for processing digital images. It is based on a course for postgraduates reading physics, electronic engineering, telecommunications engineering, information technology and computer science. This book relates the methods of processing and interpreting digital images to the 'physics' of imaging systems. Case studies reinforce the methods discussed, with examples of current research

  3. [Plaque segmentation of intracoronary optical coherence tomography images based on K-means and improved random walk algorithm].

    Science.gov (United States)

    Wang, Guanglei; Wang, Pengyu; Han, Yechen; Liu, Xiuling; Li, Yan; Lu, Qian

    2017-06-01

    In recent years, optical coherence tomography (OCT) has developed into a popular coronary imaging technology at home and abroad. The segmentation of plaque regions in coronary OCT images has great significance for vulnerable plaque recognition and research. In this paper, a new algorithm based on K -means clustering and improved random walk is proposed and Semi-automated segmentation of calcified plaque, fibrotic plaque and lipid pool was achieved. And the weight function of random walk is improved. The distance between the edges of pixels in the image and the seed points is added to the definition of the weight function. It increases the weak edge weights and prevent over-segmentation. Based on the above methods, the OCT images of 9 coronary atherosclerotic patients were selected for plaque segmentation. By contrasting the doctor's manual segmentation results with this method, it was proved that this method had good robustness and accuracy. It is hoped that this method can be helpful for the clinical diagnosis of coronary heart disease.

  4. Novel edge treatment method for improving the transmission reconstruction quality in Tomographic Gamma Scanning.

    Science.gov (United States)

    Han, Miaomiao; Guo, Zhirong; Liu, Haifeng; Li, Qinghua

    2018-05-01

    Tomographic Gamma Scanning (TGS) is a method used for the nondestructive assay of radioactive wastes. In TGS, the actual irregular edge voxels are regarded as regular cubic voxels in the traditional treatment method. In this study, in order to improve the performance of TGS, a novel edge treatment method is proposed that considers the actual shapes of these voxels. The two different edge voxel treatment methods were compared by computing the pixel-level relative errors and normalized mean square errors (NMSEs) between the reconstructed transmission images and the ideal images. Both methods were coupled with two different interative algorithms comprising Algebraic Reconstruction Technique (ART) with a non-negativity constraint and Maximum Likelihood Expectation Maximization (MLEM). The results demonstrated that the traditional method for edge voxel treatment can introduce significant error and that the real irregular edge voxel treatment method can improve the performance of TGS by obtaining better transmission reconstruction images. With the real irregular edge voxel treatment method, MLEM algorithm and ART algorithm can be comparable when assaying homogenous matrices, but MLEM algorithm is superior to ART algorithm when assaying heterogeneous matrices. Copyright © 2018 Elsevier Ltd. All rights reserved.

  5. Robust and efficient method for matching features in omnidirectional images

    Science.gov (United States)

    Zhu, Qinyi; Zhang, Zhijiang; Zeng, Dan

    2018-04-01

    Binary descriptors have been widely used in many real-time applications due to their efficiency. These descriptors are commonly designed for perspective images but perform poorly on omnidirectional images, which are severely distorted. To address this issue, this paper proposes tangent plane BRIEF (TPBRIEF) and adapted log polar grid-based motion statistics (ALPGMS). TPBRIEF projects keypoints to a unit sphere and applies the fixed test set in BRIEF descriptor on the tangent plane of the unit sphere. The fixed test set is then backprojected onto the original distorted images to construct the distortion invariant descriptor. TPBRIEF directly enables keypoint detecting and feature describing on original distorted images, whereas other approaches correct the distortion through image resampling, which introduces artifacts and adds time cost. With ALPGMS, omnidirectional images are divided into circular arches named adapted log polar grids. Whether a match is true or false is then determined by simply thresholding the match numbers in a grid pair where the two matched points located. Experiments show that TPBRIEF greatly improves the feature matching accuracy and ALPGMS robustly removes wrong matches. Our proposed method outperforms the state-of-the-art methods.

  6. Improving abdomen tumor low-dose CT images using a fast dictionary learning based processing

    International Nuclear Information System (INIS)

    Chen Yang; Shi Luyao; Shu Huazhong; Luo Limin; Coatrieux, Jean-Louis; Yin Xindao; Toumoulin, Christine

    2013-01-01

    In abdomen computed tomography (CT), repeated radiation exposures are often inevitable for cancer patients who receive surgery or radiotherapy guided by CT images. Low-dose scans should thus be considered in order to avoid the harm of accumulative x-ray radiation. This work is aimed at improving abdomen tumor CT images from low-dose scans by using a fast dictionary learning (DL) based processing. Stemming from sparse representation theory, the proposed patch-based DL approach allows effective suppression of both mottled noise and streak artifacts. The experiments carried out on clinical data show that the proposed method brings encouraging improvements in abdomen low-dose CT images with tumors. (paper)

  7. Development and application of pulmonary structure-function registration methods: towards pulmonary image-guidance tools for improved airway targeted therapies and outcomes

    Science.gov (United States)

    Guo, Fumin; Pike, Damien; Svenningsen, Sarah; Coxson, Harvey O.; Drozd, John J.; Yuan, Jing; Fenster, Aaron; Parraga, Grace

    2014-03-01

    Objectives: We aimed to develop a way to rapidly generate multi-modality (MRI-CT) pulmonary imaging structurefunction maps using novel non-rigid image registration methods. This objective is part of our overarching goal to provide an image processing pipeline to generate pulmonary structure-function maps and guide airway-targeted therapies. Methods: Anatomical 1H and functional 3He MRI were acquired in 5 healthy asymptomatic ex-smokers and 7 ex-smokers with chronic obstructive pulmonary disease (COPD) at inspiration breath-hold. Thoracic CT was performed within ten minutes of MRI using the same breath-hold volume. Landmark-based affine registration methods previously validated for imaging of COPD, was based on corresponding fiducial markers located in both CT and 1H MRI coronal slices and compared with shape-based CT-MRI non-rigid registration. Shape-based CT-MRI registration was developed by first identifying the shapes of the lung cavities manually, and then registering the two shapes using affine and thin-plate spline algorithms. We compared registration accuracy using the fiducial localization error (FLE) and target registration error (TRE). Results: For landmark-based registration, the TRE was 8.4±5.3 mm for whole lung and 7.8±4.6 mm for the R and L lungs registered independently (p=0.4). For shape-based registration, the TRE was 8.0±4.6 mm for whole lung as compared to 6.9±4.4 mm for the R and L lung registered independently and this difference was significant (p=0.01). The difference for shape-based (6.9±4.4 mm) and landmark-based R and L lung registration (7.8±4.6 mm) was also significant (p=.04) Conclusion: Shape-based registration TRE was significantly improved compared to landmark-based registration when considering L and R lungs independently.

  8. Heuristically improved Bayesian segmentation of brain MR images ...

    African Journals Online (AJOL)

    Heuristically improved Bayesian segmentation of brain MR images. ... or even the most prevalent task in medical image processing is image segmentation. Among them, brain MR images suffer ... show that our algorithm performs well in comparison with the one implemented in SPM. It can be concluded that incorporating ...

  9. Underwater image quality enhancement of sea cucumbers based on improved histogram equalization and wavelet transform

    Directory of Open Access Journals (Sweden)

    Xi Qiao

    2017-09-01

    Full Text Available Sea cucumbers usually live in an environment where lighting and visibility are generally not controllable, which cause the underwater image of sea cucumbers to be distorted, blurred, and severely attenuated. Therefore, the valuable information from such an image cannot be fully extracted for further processing. To solve the problems mentioned above and improve the quality of the underwater images of sea cucumbers, pre-processing of a sea cucumber image is attracting increasing interest. This paper presents a new method based on contrast limited adaptive histogram equalization and wavelet transform (CLAHE-WT to enhance the sea cucumber image quality. CLAHE was used to process the underwater image for increasing contrast based on the Rayleigh distribution, and WT was used for de-noising based on a soft threshold. Qualitative analysis indicated that the proposed method exhibited better performance in enhancing the quality and retaining the image details. For quantitative analysis, the test with 120 underwater images showed that for the proposed method, the mean square error (MSE, peak signal to noise ratio (PSNR, and entropy were 49.2098, 13.3909, and 6.6815, respectively. The proposed method outperformed three established methods in enhancing the visual quality of sea cucumber underwater gray image.

  10. Fast and accurate denoising method applied to very high resolution optical remote sensing images

    Science.gov (United States)

    Masse, Antoine; Lefèvre, Sébastien; Binet, Renaud; Artigues, Stéphanie; Lassalle, Pierre; Blanchet, Gwendoline; Baillarin, Simon

    2017-10-01

    Restoration of Very High Resolution (VHR) optical Remote Sensing Image (RSI) is critical and leads to the problem of removing instrumental noise while keeping integrity of relevant information. Improving denoising in an image processing chain implies increasing image quality and improving performance of all following tasks operated by experts (photo-interpretation, cartography, etc.) or by algorithms (land cover mapping, change detection, 3D reconstruction, etc.). In a context of large industrial VHR image production, the selected denoising method should optimized accuracy and robustness with relevant information and saliency conservation, and rapidity due to the huge amount of data acquired and/or archived. Very recent research in image processing leads to a fast and accurate algorithm called Non Local Bayes (NLB) that we propose to adapt and optimize for VHR RSIs. This method is well suited for mass production thanks to its best trade-off between accuracy and computational complexity compared to other state-of-the-art methods. NLB is based on a simple principle: similar structures in an image have similar noise distribution and thus can be denoised with the same noise estimation. In this paper, we describe in details algorithm operations and performances, and analyze parameter sensibilities on various typical real areas observed in VHR RSIs.

  11. Abdomen disease diagnosis in CT images using flexiscale curvelet transform and improved genetic algorithm.

    Science.gov (United States)

    Sethi, Gaurav; Saini, B S

    2015-12-01

    This paper presents an abdomen disease diagnostic system based on the flexi-scale curvelet transform, which uses different optimal scales for extracting features from computed tomography (CT) images. To optimize the scale of the flexi-scale curvelet transform, we propose an improved genetic algorithm. The conventional genetic algorithm assumes that fit parents will likely produce the healthiest offspring that leads to the least fit parents accumulating at the bottom of the population, reducing the fitness of subsequent populations and delaying the optimal solution search. In our improved genetic algorithm, combining the chromosomes of a low-fitness and a high-fitness individual increases the probability of producing high-fitness offspring. Thereby, all of the least fit parent chromosomes are combined with high fit parent to produce offspring for the next population. In this way, the leftover weak chromosomes cannot damage the fitness of subsequent populations. To further facilitate the search for the optimal solution, our improved genetic algorithm adopts modified elitism. The proposed method was applied to 120 CT abdominal images; 30 images each of normal subjects, cysts, tumors and stones. The features extracted by the flexi-scale curvelet transform were more discriminative than conventional methods, demonstrating the potential of our method as a diagnostic tool for abdomen diseases.

  12. [Research on fast implementation method of image Gaussian RBF interpolation based on CUDA].

    Science.gov (United States)

    Chen, Hao; Yu, Haizhong

    2014-04-01

    Image interpolation is often required during medical image processing and analysis. Although interpolation method based on Gaussian radial basis function (GRBF) has high precision, the long calculation time still limits its application in field of image interpolation. To overcome this problem, a method of two-dimensional and three-dimensional medical image GRBF interpolation based on computing unified device architecture (CUDA) is proposed in this paper. According to single instruction multiple threads (SIMT) executive model of CUDA, various optimizing measures such as coalesced access and shared memory are adopted in this study. To eliminate the edge distortion of image interpolation, natural suture algorithm is utilized in overlapping regions while adopting data space strategy of separating 2D images into blocks or dividing 3D images into sub-volumes. Keeping a high interpolation precision, the 2D and 3D medical image GRBF interpolation achieved great acceleration in each basic computing step. The experiments showed that the operative efficiency of image GRBF interpolation based on CUDA platform was obviously improved compared with CPU calculation. The present method is of a considerable reference value in the application field of image interpolation.

  13. Improving Land Use/Land Cover Classification by Integrating Pixel Unmixing and Decision Tree Methods

    Directory of Open Access Journals (Sweden)

    Chao Yang

    2017-11-01

    Full Text Available Decision tree classification is one of the most efficient methods for obtaining land use/land cover (LULC information from remotely sensed imageries. However, traditional decision tree classification methods cannot effectively eliminate the influence of mixed pixels. This study aimed to integrate pixel unmixing and decision tree to improve LULC classification by removing mixed pixel influence. The abundance and minimum noise fraction (MNF results that were obtained from mixed pixel decomposition were added to decision tree multi-features using a three-dimensional (3D Terrain model, which was created using an image fusion digital elevation model (DEM, to select training samples (ROIs, and improve ROI separability. A Landsat-8 OLI image of the Yunlong Reservoir Basin in Kunming was used to test this proposed method. Study results showed that the Kappa coefficient and the overall accuracy of integrated pixel unmixing and decision tree method increased by 0.093% and 10%, respectively, as compared with the original decision tree method. This proposed method could effectively eliminate the influence of mixed pixels and improve the accuracy in complex LULC classifications.

  14. The narrow-band imaging examination method in otorhinolaryngology

    Directory of Open Access Journals (Sweden)

    Robert Šifrer

    2013-10-01

    Full Text Available Early diagnostics could improve the prognosis of patients with squamous-cell carcinomas of the head and neck. Narrow-Band Imaging (NBI is the latest examination method in the group of biologic endoscopies. NBI improves the distinction between malignant and benign mucosal lesions. Early suspect oncologic lesions that may otherwise be missed by normal white light illumination can also be diagnosed. The biggest benefit of NBI technology is achieved by using it together with a HDTV camera that enables better contrast and higher resolution. NBI is based on better imaging of superficial mucosal vasculature. The biologic potential of mucosal lesions could be predicted from vascular changes. The colour of normal mucosa under NBI is blue and green and the vessels show no pathological features. Well-demarcated brownish areas and scattered thick dark spots and abnormal winding and branching out of vessels on the mucosa are all oncologically suspicious features. Authors report the experience from literature on the use of NBI to identify carcinomas of the oral cavity, epipharynx, oropharynx, hypopharynx and larynx and evaluation of unknown primaries. In addition, the literature reports the benefit of NBI in identifying early stage carcinomas in previously irradiated patients. Persistence and recurrence of carcinoma and the development of new primary tumour could easily be missed by using only standard white-light illumination. The method proved to be highly sensitive and specific for predicting malignant changes in the above-mentioned circumstances. Authors report their own experience with NBI technology as well. For further improvement of the method, new technologic development is expected to enable the connection of NBI and HDTV with flexible endoscopes.

  15. Image improvement and three-dimensional reconstruction using holographic image processing

    Science.gov (United States)

    Stroke, G. W.; Halioua, M.; Thon, F.; Willasch, D. H.

    1977-01-01

    Holographic computing principles make possible image improvement and synthesis in many cases of current scientific and engineering interest. Examples are given for the improvement of resolution in electron microscopy and 3-D reconstruction in electron microscopy and X-ray crystallography, following an analysis of optical versus digital computing in such applications.

  16. Robust boundary detection of left ventricles on ultrasound images using ASM-level set method.

    Science.gov (United States)

    Zhang, Yaonan; Gao, Yuan; Li, Hong; Teng, Yueyang; Kang, Yan

    2015-01-01

    Level set method has been widely used in medical image analysis, but it has difficulties when being used in the segmentation of left ventricular (LV) boundaries on echocardiography images because the boundaries are not very distinguish, and the signal-to-noise ratio of echocardiography images is not very high. In this paper, we introduce the Active Shape Model (ASM) into the traditional level set method to enforce shape constraints. It improves the accuracy of boundary detection and makes the evolution more efficient. The experiments conducted on the real cardiac ultrasound image sequences show a positive and promising result.

  17. Spatial image modulation to improve performance of computed tomography imaging spectrometer

    Science.gov (United States)

    Bearman, Gregory H. (Inventor); Wilson, Daniel W. (Inventor); Johnson, William R. (Inventor)

    2010-01-01

    Computed tomography imaging spectrometers ("CTIS"s) having patterns for imposing spatial structure are provided. The pattern may be imposed either directly on the object scene being imaged or at the field stop aperture. The use of the pattern improves the accuracy of the captured spatial and spectral information.

  18. Spiking cortical model-based nonlocal means method for speckle reduction in optical coherence tomography images

    Science.gov (United States)

    Zhang, Xuming; Li, Liu; Zhu, Fei; Hou, Wenguang; Chen, Xinjian

    2014-06-01

    Optical coherence tomography (OCT) images are usually degraded by significant speckle noise, which will strongly hamper their quantitative analysis. However, speckle noise reduction in OCT images is particularly challenging because of the difficulty in differentiating between noise and the information components of the speckle pattern. To address this problem, the spiking cortical model (SCM)-based nonlocal means method is presented. The proposed method explores self-similarities of OCT images based on rotation-invariant features of image patches extracted by SCM and then restores the speckled images by averaging the similar patches. This method can provide sufficient speckle reduction while preserving image details very well due to its effectiveness in finding reliable similar patches under high speckle noise contamination. When applied to the retinal OCT image, this method provides signal-to-noise ratio improvements of >16 dB with a small 5.4% loss of similarity.

  19. An Image Registration Method for Colposcopic Images

    Directory of Open Access Journals (Sweden)

    Efrén Mezura-Montes

    2013-01-01

    sequence and a division of such image into small windows. A search process is then carried out to find the window with the highest affinity in each image of the sequence and replace it with the window in the reference image. The affinity value is based on polynomial approximation of the time series computed and the search is bounded by a search radius which defines the neighborhood of each window. The proposed approach is tested in ten 310-frame real cases in two experiments: the first one to determine the best values for the window size and the search radius and the second one to compare the best obtained results with respect to four registration methods found in the specialized literature. The obtained results show a robust and competitive performance of the proposed approach with a significant lower time with respect to the compared methods.

  20. An overview of methods to mitigate artifacts in optical coherence tomography imaging of the skin.

    Science.gov (United States)

    Adabi, Saba; Fotouhi, Audrey; Xu, Qiuyun; Daveluy, Steve; Mehregan, Darius; Podoleanu, Adrian; Nasiriavanaki, Mohammadreza

    2018-05-01

    Optical coherence tomography (OCT) of skin delivers three-dimensional images of tissue microstructures. Although OCT imaging offers a promising high-resolution modality, OCT images suffer from some artifacts that lead to misinterpretation of tissue structures. Therefore, an overview of methods to mitigate artifacts in OCT imaging of the skin is of paramount importance. Speckle, intensity decay, and blurring are three major artifacts in OCT images. Speckle is due to the low coherent light source used in the configuration of OCT. Intensity decay is a deterioration of light with respect to depth, and blurring is the consequence of deficiencies of optical components. Two speckle reduction methods (one based on artificial neural network and one based on spatial compounding), an attenuation compensation algorithm (based on Beer-Lambert law) and a deblurring procedure (using deconvolution), are described. Moreover, optical properties extraction algorithm based on extended Huygens-Fresnel (EHF) principle to obtain some additional information from OCT images are discussed. In this short overview, we summarize some of the image enhancement algorithms for OCT images which address the abovementioned artifacts. The results showed a significant improvement in the visibility of the clinically relevant features in the images. The quality improvement was evaluated using several numerical assessment measures. Clinical dermatologists benefit from using these image enhancement algorithms to improve OCT diagnosis and essentially function as a noninvasive optical biopsy. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  1. Depth extraction method with high accuracy in integral imaging based on moving array lenslet technique

    Science.gov (United States)

    Wang, Yao-yao; Zhang, Juan; Zhao, Xue-wei; Song, Li-pei; Zhang, Bo; Zhao, Xing

    2018-03-01

    In order to improve depth extraction accuracy, a method using moving array lenslet technique (MALT) in pickup stage is proposed, which can decrease the depth interval caused by pixelation. In this method, the lenslet array is moved along the horizontal and vertical directions simultaneously for N times in a pitch to get N sets of elemental images. Computational integral imaging reconstruction method for MALT is taken to obtain the slice images of the 3D scene, and the sum modulus (SMD) blur metric is taken on these slice images to achieve the depth information of the 3D scene. Simulation and optical experiments are carried out to verify the feasibility of this method.

  2. Evaluation of an improved technique for automated center lumen line definition in cardiovascular image data

    International Nuclear Information System (INIS)

    Gratama van Andel, Hugo A.F.; Meijering, Erik; Vrooman, Henri A.; Stokking, Rik; Lugt, Aad van der; Monye, Cecile de

    2006-01-01

    The aim of the study was to evaluate a new method for automated definition of a center lumen line in vessels in cardiovascular image data. This method, called VAMPIRE, is based on improved detection of vessel-like structures. A multiobserver evaluation study was conducted involving 40 tracings in clinical CTA data of carotid arteries to compare VAMPIRE with an established technique. This comparison showed that VAMPIRE yields considerably more successful tracings and improved handling of stenosis, calcifications, multiple vessels, and nearby bone structures. We conclude that VAMPIRE is highly suitable for automated definition of center lumen lines in vessels in cardiovascular image data. (orig.)

  3. Improving Lucky Imaging Photometry

    DEFF Research Database (Denmark)

    Skottfelt, Jesper Mirsa

    optics systems can be used to mitigate the e ects of the atmospheric turbulence, but these systems are very complicated and expensive and therefore not cost-e ective for smaller telescopes. Another solution for this problem is the use of high frame-rate imaging. At very short exposure times ( 10 ms...... resolution. Even using longer exposure times ( 100 ms) this method can be used to mitigate the e ect of image motion created by atmospheric turbulence. The Lucky Imaging technique makes use of the fact that there is some probability that the wavefront on some of these snapshots has traverse the atmosphere...... almost unperturbed. If only these snapshots are stacked, it is possible to achieve very high spatial resolution. Due to the readout noise it is not feasible to use conventional CCDs for high frame-rate imaging, unless bright sources are observed. In an electron multiplying CCD, or EMCCD, the signal...

  4. Optical Coherence Tomography Technology and Quality Improvement Methods for Optical Coherence Tomography Images of Skin: A Short Review

    Science.gov (United States)

    Adabi, Saba; Turani, Zahra; Fatemizadeh, Emad; Clayton, Anne; Nasiriavanaki, Mohammadreza

    2017-01-01

    Optical coherence tomography (OCT) delivers 3-dimensional images of tissue microstructures. Although OCT imaging offers a promising high-resolution method, OCT images experience some artifacts that lead to misapprehension of tissue structures. Speckle, intensity decay, and blurring are 3 major artifacts in OCT images. Speckle is due to the low coherent light source used in the configuration of OCT. Intensity decay is a deterioration of light with respect to depth, and blurring is the consequence of deficiencies of optical components. In this short review, we summarize some of the image enhancement algorithms for OCT images which address the abovementioned artifacts. PMID:28638245

  5. Optical Coherence Tomography Technology and Quality Improvement Methods for Optical Coherence Tomography Images of Skin: A Short Review

    Directory of Open Access Journals (Sweden)

    Saba Adabi

    2017-06-01

    Full Text Available Optical coherence tomography (OCT delivers 3-dimensional images of tissue microstructures. Although OCT imaging offers a promising high-resolution method, OCT images experience some artifacts that lead to misapprehension of tissue structures. Speckle, intensity decay, and blurring are 3 major artifacts in OCT images. Speckle is due to the low coherent light source used in the configuration of OCT. Intensity decay is a deterioration of light with respect to depth, and blurring is the consequence of deficiencies of optical components. In this short review, we summarize some of the image enhancement algorithms for OCT images which address the abovementioned artifacts.

  6. Improving the Image Quality of Synthetic Transmit Aperture Ultrasound Images - Achieving Real-Time In-Vivo Imaging

    DEFF Research Database (Denmark)

    Gammelmark, Kim

    in-vivo experiments, showed, that TMS imaging can increase the SNR by as much as 17 dB compared to the traditional imaging techniques, which improves the in-vivo image quality to a highly competitive level. An in-vivo evaluation of convex array TMS imaging for abdominal imaging applications......-vivo imaging, and that the obtained image quality is highly competitive with the techniques applied in current medical ultrasound scanners. Hereby, the goals of the PhD have been successfully achieved.......Synthetic transmit aperture (STA) imaging has the potential to increase the image quality of medical ultrasound images beyond the levels obtained by conventional imaging techniques (linear, phased, and convex array imaging). Currently, however, in-vivo applications of STA imaging is limited...

  7. Optical Coherence Tomography Technology and Quality Improvement Methods for Optical Coherence Tomography Images of Skin: A Short Review

    OpenAIRE

    Adabi, Saba; Turani, Zahra; Fatemizadeh, Emad; Clayton, Anne; Nasiriavanaki, Mohammadreza

    2017-01-01

    Optical coherence tomography (OCT) delivers 3-dimensional images of tissue microstructures. Although OCT imaging offers a promising high-resolution method, OCT images experience some artifacts that lead to misapprehension of tissue structures. Speckle, intensity decay, and blurring are 3 major artifacts in OCT images. Speckle is due to the low coherent light source used in the configuration of OCT. Intensity decay is a deterioration of light with respect to depth, and blurring is the conseque...

  8. MRI-Based Computed Tomography Metal Artifact Correction Method for Improving Proton Range Calculation Accuracy

    International Nuclear Information System (INIS)

    Park, Peter C.; Schreibmann, Eduard; Roper, Justin; Elder, Eric; Crocker, Ian; Fox, Tim; Zhu, X. Ronald; Dong, Lei; Dhabaan, Anees

    2015-01-01

    Purpose: Computed tomography (CT) artifacts can severely degrade dose calculation accuracy in proton therapy. Prompted by the recently increased popularity of magnetic resonance imaging (MRI) in the radiation therapy clinic, we developed an MRI-based CT artifact correction method for improving the accuracy of proton range calculations. Methods and Materials: The proposed method replaces corrupted CT data by mapping CT Hounsfield units (HU number) from a nearby artifact-free slice, using a coregistered MRI. MRI and CT volumetric images were registered with use of 3-dimensional (3D) deformable image registration (DIR). The registration was fine-tuned on a slice-by-slice basis by using 2D DIR. Based on the intensity of paired MRI pixel values and HU from an artifact-free slice, we performed a comprehensive analysis to predict the correct HU for the corrupted region. For a proof-of-concept validation, metal artifacts were simulated on a reference data set. Proton range was calculated using reference, artifactual, and corrected images to quantify the reduction in proton range error. The correction method was applied to 4 unique clinical cases. Results: The correction method resulted in substantial artifact reduction, both quantitatively and qualitatively. On respective simulated brain and head and neck CT images, the mean error was reduced from 495 and 370 HU to 108 and 92 HU after correction. Correspondingly, the absolute mean proton range errors of 2.4 cm and 1.7 cm were reduced to less than 2 mm in both cases. Conclusions: Our MRI-based CT artifact correction method can improve CT image quality and proton range calculation accuracy for patients with severe CT artifacts

  9. Inverse transformation algorithm of transient electromagnetic field and its high-resolution continuous imaging interpretation method

    International Nuclear Information System (INIS)

    Qi, Zhipeng; Li, Xiu; Lu, Xushan; Zhang, Yingying; Yao, Weihua

    2015-01-01

    We introduce a new and potentially useful method for wave field inverse transformation and its application in transient electromagnetic method (TEM) 3D interpretation. The diffusive EM field is known to have a unique integral representation in terms of a fictitious wave field that satisfies a wave equation. The continuous imaging of TEM can be accomplished using the imaging methods in seismic interpretation after the diffusion equation is transformed into a fictitious wave equation. The interpretation method based on the imaging of a fictitious wave field could be used as a fast 3D inversion method. Moreover, the fictitious wave field possesses some wave field features making it possible for the application of a wave field interpretation method in TEM to improve the prospecting resolution.Wave field transformation is a key issue in the migration imaging of a fictitious wave field. The equation in the wave field transformation belongs to the first class Fredholm integration equation, which is a typical ill-posed equation. Additionally, TEM has a large dynamic time range, which also facilitates the weakness of this ill-posed problem. The wave field transformation is implemented by using pre-conditioned regularized conjugate gradient method. The continuous imaging of a fictitious wave field is implemented by using Kirchhoff integration. A synthetic aperture and deconvolution algorithm is also introduced to improve the interpretation resolution. We interpreted field data by the method proposed in this paper, and obtained a satisfying interpretation result. (paper)

  10. Cryptanalysis and Improvement of the Robust and Blind Watermarking Scheme for Dual Color Image

    Directory of Open Access Journals (Sweden)

    Hai Nan

    2015-01-01

    Full Text Available With more color images being widely used on the Internet, the research on embedding color watermark image into color host image has been receiving more attention. Recently, Su et al. have proposed a robust and blind watermarking scheme for dual color image, in which the main innovation is the using of two-level DCT. However, it has been demonstrated in this paper that the original scheme in Su’s study is not secure and can be attacked by our proposed method. In addition, some errors in the original scheme have been pointed out. Also, an improvement measure is presented to enhance the security of the original watermarking scheme. The proposed method has been confirmed by both theoretical analysis and experimental results.

  11. Adaptive statistical iterative reconstruction for volume-rendered computed tomography portovenography. Improvement of image quality

    International Nuclear Information System (INIS)

    Matsuda, Izuru; Hanaoka, Shohei; Akahane, Masaaki

    2010-01-01

    Adaptive statistical iterative reconstruction (ASIR) is a reconstruction technique for computed tomography (CT) that reduces image noise. The purpose of our study was to investigate whether ASIR improves the quality of volume-rendered (VR) CT portovenography. Institutional review board approval, with waived consent, was obtained. A total of 19 patients (12 men, 7 women; mean age 69.0 years; range 25-82 years) suspected of having liver lesions underwent three-phase enhanced CT. VR image sets were prepared with both the conventional method and ASIR. The required time to make VR images was recorded. Two radiologists performed independent qualitative evaluations of the image sets. The Wilcoxon signed-rank test was used for statistical analysis. Contrast-noise ratios (CNRs) of the portal and hepatic vein were also evaluated. Overall image quality was significantly improved by ASIR (P<0.0001 and P=0.0155 for each radiologist). ASIR enhanced CNRs of the portal and hepatic vein significantly (P<0.0001). The time required to create VR images was significantly shorter with ASIR (84.7 vs. 117.1 s; P=0.014). ASIR enhances CNRs and improves image quality in VR CT portovenography. It also shortens the time required to create liver VR CT portovenographs. (author)

  12. Enhancement of image contrast in linacgram through image processing

    International Nuclear Information System (INIS)

    Suh, Hyun Suk; Shin, Hyun Kyo; Lee, Re Na

    2000-01-01

    Conventional radiation therapy portal images gives low contrast images. The purpose of this study was to enhance image contrast of a linacgram by developing a low--cost image processing method. Chest linacgram was obtained by irradiating humanoid phantom and scanned using Diagnostic-Pro scanner for image processing. Several types of scan method were used in scanning. These include optical density scan, histogram equalized scan, linear histogram based scan, linear histogram independent scan, linear optical density scan, logarithmic scan, and power square root scan. The histogram distribution of the scanned images were plotted and the ranges of the gray scale were compared among various scan types. The scanned images were then transformed to the gray window by pallette fitting method and the contrast of the reprocessed portal images were evaluated for image improvement. Portal images of patients were also taken at various anatomic sites and the images were processed by Gray Scale Expansion (GSE) method. The patient images were analyzed to examine the feasibility of using the GSE technique in clinic. The histogram distribution showed that minimum and maximum gray scale ranges of 3192 and 21940 were obtained when the image was scanned using logarithmic method and square root method, respectively. Out of 256 gray scale, only 7 to 30% of the steps were used. After expanding the gray scale to full range, contrast of the portal images were improved. Experiment performed with patient image showed that improved identification of organs were achieved by GSE in portal images of knee joint, head and neck, lung, and pelvis. Phantom study demonstrated that the GSE technique improved image contrast of a linacgram. This indicates that the decrease in image quality resulting from the dual exposure, could be improved by expanding the gray scale. As a result, the improved technique will make it possible to compare the digitally reconstructed radiographs (DRR) and simulation image for

  13. Echo-Planar Imaging-Based, J-Resolved Spectroscopic Imaging for Improved Metabolite Detection in Prostate Cancer

    Science.gov (United States)

    2016-12-01

    post-process the multi-dimensional MRS data from different prostate pathologies . Scope: Improved cancer detection (specificity) in differentiating...MATERIALS AND METHODS Patients Between March 2012 and May 2013, twenty-two patients with PCa with a mean age of 63.8 years (range, 46–79 years), who...tumor voxels, which was confirmed by the pathology report. After reconstruction, the EP-JRESI data were overlaid onto MRI images. MRI and MRSI A body

  14. Improvements on Fresnel arrays for high contrast imaging

    Science.gov (United States)

    Wilhem, Roux; Laurent, Koechlin

    2018-03-01

    The Fresnel Diffractive Array Imager (FDAI) is based on a new optical concept for space telescopes, developed at Institut de Recherche en Astrophysique et Planétologie (IRAP), Toulouse, France. For the visible and near-infrared it has already proven its performances in resolution and dynamic range. We propose it now for astrophysical applications in the ultraviolet with apertures from 6 to 30 meters, aimed at imaging in UV faint astrophysical sources close to bright ones, as well as other applications requiring high dynamic range. Of course the project needs first a probatory mission at small aperture to validate the concept in space. In collaboration with institutes in Spain and Russia, we will propose to board a small prototype of Fresnel imager on the International Space Station (ISS), with a program combining technical tests and astrophysical targets. The spectral domain should contain the Lyman- α line ( λ = 121 nm). As part of its preparation, we improve the Fresnel array design for a better Point Spread Function in UV, presently on a small laboratory prototype working at 260 nm. Moreover, we plan to validate a new optical design and chromatic correction adapted to UV. In this article we present the results of numerical propagations showing the improvement in dynamic range obtained by combining and adapting three methods : central obturation, optimization of the bars mesh holding the Fresnel rings, and orthogonal apodization. We briefly present the proposed astrophysical program of a probatory mission with such UV optics.

  15. Investigations on image improvement in radiodiagnosis under special consideration of reducing scattered radiation

    International Nuclear Information System (INIS)

    Becker, R.

    1976-10-01

    In the study, image improvement is proposed for scintiscanning, X-ray and neutron diagnosis as well as computer axial tomography. In order to reduce the scattered radiation, mainly two-dimensional radiation transport calculations are carried out, and the imaging properties are studied by simulation on a large computer. It was found, among other things, that in contrast to X-ray techniques, in diagnosis with fast neutrons the image quality can hardly be improved by screens for scattered radiation. Here the problem of scattered radiation can only be solved by using scanners with narrow beams. The new method of neutron diagnosis resulting from this is especially suited for representing structures behind bones or for the localization of bone tumors invisible to X-rays, but not for representing fatty tissue. For large depths of irradiation, the scattered radiation with neutron sources below 1 MeV gets so intensive that diagnosis becomes impossible. When fast neutrons are used are used, the method is applicable for computer axial tomography because of the narrow beams. (ORU) [de

  16. Improved medical image fusion based on cascaded PCA and shift invariant wavelet transforms.

    Science.gov (United States)

    Reena Benjamin, J; Jayasree, T

    2018-02-01

    In the medical field, radiologists need more informative and high-quality medical images to diagnose diseases. Image fusion plays a vital role in the field of biomedical image analysis. It aims to integrate the complementary information from multimodal images, producing a new composite image which is expected to be more informative for visual perception than any of the individual input images. The main objective of this paper is to improve the information, to preserve the edges and to enhance the quality of the fused image using cascaded principal component analysis (PCA) and shift invariant wavelet transforms. A novel image fusion technique based on cascaded PCA and shift invariant wavelet transforms is proposed in this paper. PCA in spatial domain extracts relevant information from the large dataset based on eigenvalue decomposition, and the wavelet transform operating in the complex domain with shift invariant properties brings out more directional and phase details of the image. The significance of maximum fusion rule applied in dual-tree complex wavelet transform domain enhances the average information and morphological details. The input images of the human brain of two different modalities (MRI and CT) are collected from whole brain atlas data distributed by Harvard University. Both MRI and CT images are fused using cascaded PCA and shift invariant wavelet transform method. The proposed method is evaluated based on three main key factors, namely structure preservation, edge preservation, contrast preservation. The experimental results and comparison with other existing fusion methods show the superior performance of the proposed image fusion framework in terms of visual and quantitative evaluations. In this paper, a complex wavelet-based image fusion has been discussed. The experimental results demonstrate that the proposed method enhances the directional features as well as fine edge details. Also, it reduces the redundant details, artifacts, distortions.

  17. Pediatric Trauma Transfer Imaging Inefficiencies—Opportunities for Improvement with Cloud Technology

    Directory of Open Access Journals (Sweden)

    Yana Puckett

    2016-02-01

    Full Text Available BACKGROUND: This study examines the inefficiencies of radiologic imaging transfers from one hospital to the other during pediatric trauma transfers in an era of cloud based information sharing. METHODS: Retrospective review of all patients transferred to a pediatric trauma center from 2008–2014 was performed. Imaging was reviewed for whether imaging accompanied the patient, whether imaging was able to be uploaded onto computer for records, whether imaging had to be repeated, and whether imaging obtained at outside hospitals (OSH was done per universal pediatric trauma guidelines. RESULTS: Of the 1761 patients retrospectively reviewed, 559 met our inclusion criteria. Imaging was sent with the patient 87.7% of the time. Imaging was unable to be uploaded 31.9% of the time. CT imaging had to be repeated 1.8% of the time. CT scan was not done per universal pediatric trauma guidelines 1.2% of the time. CONCLUSION: Our study demonstrated that current imaging transfer is inefficient, leads to excess ionizing radiation, and increased healthcare costs. Universal implementation of cloud based radiology has the potential to eliminate excess ionizing radiation to children, improve patient care, and save cost to healthcare system.

  18. Reducing charging effects in scanning electron microscope images by Rayleigh contrast stretching method (RCS).

    Science.gov (United States)

    Wan Ismail, W Z; Sim, K S; Tso, C P; Ting, H Y

    2011-01-01

    To reduce undesirable charging effects in scanning electron microscope images, Rayleigh contrast stretching is developed and employed. First, re-scaling is performed on the input image histograms with Rayleigh algorithm. Then, contrast stretching or contrast adjustment is implemented to improve the images while reducing the contrast charging artifacts. This technique has been compared to some existing histogram equalization (HE) extension techniques: recursive sub-image HE, contrast stretching dynamic HE, multipeak HE and recursive mean separate HE. Other post processing methods, such as wavelet approach, spatial filtering, and exponential contrast stretching, are compared as well. Overall, the proposed method produces better image compensation in reducing charging artifacts. Copyright © 2011 Wiley Periodicals, Inc.

  19. Magnetic resonance spectroscopy as an imaging method

    International Nuclear Information System (INIS)

    Bomsdorf, H.; Imme, M.; Jensen, D.; Kunz, D.; Menhardt, W.; Ottenberg, K.; Roeschmann, P.; Schmidt, K.H.; Tschendel, O.; Wieland, J.

    1990-01-01

    An experimental Magnetic Resonance (MR) system with 4 tesla flux density was set up. For that purpose a data acquisition system and RF coils for resonance frequencies up to 170 MHz were developed. Methods for image guided spectroscopy as well as spectroscopic imaging focussing on the nuclei 1 H and 13 C were developed and tested on volunteers and selected patients. The advantages of the high field strength with respect to spectroscopic studies were demonstrated. Developments of a new fast imaging technique for the acquisition of scout images as well as a method for mapping and displaying the magnetic field inhomogeneity in-vivo represent contributions to the optimisation of the experimental procedure in spectroscopic studies. Investigations on the interaction of RF radiation with the exposed tissue allowed conclusions regarding the applicability of MR methods at high field strengths. Methods for display and processing of multi-dimensional spectroscopic imaging data sets were developed and existing methods for real-time image synthesis were extended. Results achieved in the field of computer aided analysis of MR images comprised new techniques for image background detection, contour detection and automatic image interpretation as well as knowledge bases for textural representation of medical knowledge for diagnosis. (orig.) With 82 refs., 3 tabs., 75 figs [de

  20. Improved frame-based estimation of head motion in PET brain imaging

    International Nuclear Information System (INIS)

    Mukherjee, J. M.; Lindsay, C.; King, M. A.; Licho, R.; Mukherjee, A.; Olivier, P.; Shao, L.

    2016-01-01

    Purpose: Head motion during PET brain imaging can cause significant degradation of image quality. Several authors have proposed ways to compensate for PET brain motion to restore image quality and improve quantitation. Head restraints can reduce movement but are unreliable; thus the need for alternative strategies such as data-driven motion estimation or external motion tracking. Herein, the authors present a data-driven motion estimation method using a preprocessing technique that allows the usage of very short duration frames, thus reducing the intraframe motion problem commonly observed in the multiple frame acquisition method. Methods: The list mode data for PET acquisition is uniformly divided into 5-s frames and images are reconstructed without attenuation correction. Interframe motion is estimated using a 3D multiresolution registration algorithm and subsequently compensated for. For this study, the authors used 8 PET brain studies that used F-18 FDG as the tracer and contained minor or no initial motion. After reconstruction and prior to motion estimation, known motion was introduced to each frame to simulate head motion during a PET acquisition. To investigate the trade-off in motion estimation and compensation with respect to frames of different length, the authors summed 5-s frames accordingly to produce 10 and 60 s frames. Summed images generated from the motion-compensated reconstructed frames were then compared to the original PET image reconstruction without motion compensation. Results: The authors found that our method is able to compensate for both gradual and step-like motions using frame times as short as 5 s with a spatial accuracy of 0.2 mm on average. Complex volunteer motion involving all six degrees of freedom was estimated with lower accuracy (0.3 mm on average) than the other types investigated. Preprocessing of 5-s images was necessary for successful image registration. Since their method utilizes nonattenuation corrected frames, it is

  1. Improved frame-based estimation of head motion in PET brain imaging

    Energy Technology Data Exchange (ETDEWEB)

    Mukherjee, J. M., E-mail: joyeeta.mitra@umassmed.edu; Lindsay, C.; King, M. A.; Licho, R. [Department of Radiology, University of Massachusetts Medical School, Worcester, Massachusetts 01655 (United States); Mukherjee, A. [Aware, Inc., Bedford, Massachusetts 01730 (United States); Olivier, P. [Philips Medical Systems, Cleveland, Ohio 44143 (United States); Shao, L. [ViewRay, Oakwood Village, Ohio 44146 (United States)

    2016-05-15

    Purpose: Head motion during PET brain imaging can cause significant degradation of image quality. Several authors have proposed ways to compensate for PET brain motion to restore image quality and improve quantitation. Head restraints can reduce movement but are unreliable; thus the need for alternative strategies such as data-driven motion estimation or external motion tracking. Herein, the authors present a data-driven motion estimation method using a preprocessing technique that allows the usage of very short duration frames, thus reducing the intraframe motion problem commonly observed in the multiple frame acquisition method. Methods: The list mode data for PET acquisition is uniformly divided into 5-s frames and images are reconstructed without attenuation correction. Interframe motion is estimated using a 3D multiresolution registration algorithm and subsequently compensated for. For this study, the authors used 8 PET brain studies that used F-18 FDG as the tracer and contained minor or no initial motion. After reconstruction and prior to motion estimation, known motion was introduced to each frame to simulate head motion during a PET acquisition. To investigate the trade-off in motion estimation and compensation with respect to frames of different length, the authors summed 5-s frames accordingly to produce 10 and 60 s frames. Summed images generated from the motion-compensated reconstructed frames were then compared to the original PET image reconstruction without motion compensation. Results: The authors found that our method is able to compensate for both gradual and step-like motions using frame times as short as 5 s with a spatial accuracy of 0.2 mm on average. Complex volunteer motion involving all six degrees of freedom was estimated with lower accuracy (0.3 mm on average) than the other types investigated. Preprocessing of 5-s images was necessary for successful image registration. Since their method utilizes nonattenuation corrected frames, it is

  2. Scatter kernel estimation with an edge-spread function method for cone-beam computed tomography imaging

    International Nuclear Information System (INIS)

    Li Heng; Mohan, Radhe; Zhu, X Ronald

    2008-01-01

    The clinical applications of kilovoltage x-ray cone-beam computed tomography (CBCT) have been compromised by the limited quality of CBCT images, which typically is due to a substantial scatter component in the projection data. In this paper, we describe an experimental method of deriving the scatter kernel of a CBCT imaging system. The estimated scatter kernel can be used to remove the scatter component from the CBCT projection images, thus improving the quality of the reconstructed image. The scattered radiation was approximated as depth-dependent, pencil-beam kernels, which were derived using an edge-spread function (ESF) method. The ESF geometry was achieved with a half-beam block created by a 3 mm thick lead sheet placed on a stack of slab solid-water phantoms. Measurements for ten water-equivalent thicknesses (WET) ranging from 0 cm to 41 cm were taken with (half-blocked) and without (unblocked) the lead sheet, and corresponding pencil-beam scatter kernels or point-spread functions (PSFs) were then derived without assuming any empirical trial function. The derived scatter kernels were verified with phantom studies. Scatter correction was then incorporated into the reconstruction process to improve image quality. For a 32 cm diameter cylinder phantom, the flatness of the reconstructed image was improved from 22% to 5%. When the method was applied to CBCT images for patients undergoing image-guided therapy of the pelvis and lung, the variation in selected regions of interest (ROIs) was reduced from >300 HU to <100 HU. We conclude that the scatter reduction technique utilizing the scatter kernel effectively suppresses the artifact caused by scatter in CBCT.

  3. Speckle reduction in optical coherence tomography images of human skin by a spatial diversity method - art. no. 66270P

    DEFF Research Database (Denmark)

    Jørgensen, Thomas Martini; Thrane, Lars; Mogensen, M.

    2007-01-01

    the scheme with a mobile fiber-based time-domain real-time OCT system. Essential enhancement was obtained in image contrast when performing in vivo imaging of normal skin and lesions. Resulting images show improved delineation of structure in correspondence with the observed improvements in contrast...... system. Here, we consider a method that in principle can be fitted to most OCT systems without major modifications. Specifically, we address a spatial diversity technique for suppressing speckle noise in OCT images of human skin. The method is a variant of changing the position of the sample relative...

  4. Contrast-enhanced magnetic resonance angiography in carotid artery disease: does automated image registration improve image quality?

    International Nuclear Information System (INIS)

    Menke, Jan; Larsen, Joerg

    2009-01-01

    Contrast-enhanced magnetic resonance angiography (MRA) is a noninvasive imaging alternative to digital subtraction angiography (DSA) for patients with carotid artery disease. In DSA, image quality can be improved by shifting the mask image if the patient has moved during angiography. This study investigated whether such image registration may also help to improve the image quality of carotid MRA. Data from 370 carotid MRA examinations of patients likely to have carotid artery disease were prospectively collected. The standard nonregistered MRAs were compared to automatically linear, affine and warp registered MRA by using three image quality parameters: the vessel detection probability (VDP) in maximum intensity projection (MIP) images, contrast-to-noise ratio (CNR) in MIP images, and contrast-to-noise ratio in three-dimensional image volumes. A body shift of less than 1 mm occurred in 96.2% of cases. Analysis of variance revealed no significant influence of image registration and body shift on image quality (p > 0.05). In conclusion, standard contrast-enhanced carotid MRA usually requires no image registration to improve image quality and is generally robust against any naturally occurring body shift. (orig.)

  5. Oversampling in the computed tomography measurements applied for bone structure studies as a method of spatial resolution improvement

    International Nuclear Information System (INIS)

    Tatoń, Grzegorz; Rokita, Eugeniusz; Rok, Tomasz; Beckmann, Felix

    2012-01-01

    Our purpose was to check the potential ability of oversampling as a method for computed tomography axial resolution improvement. The method of achieving isotropic and fine resolution, when the scanning system is characterized by anisotropic resolutions is proposed. In case of typical clinical system the axial resolution is much lower than the planar one. The idea relies on the scanning with a wide overlapping layers and subsequent resolution recovery on the level of scanning step. Simulated three-dimensional images, as well as the real microtomographic images of rat femoral bone were used in proposed solution tests. Original high resolution images were virtually scanned with a wide beam and a small step in order to simulate the real measurements. The low resolution image series were subsequently processed in order to back to the original fine one. Original, virtually scanned and recovered images resolutions were compared with the use of modulation transfer function (MTF). A good ability of oversampling as a method for the resolution recovery was showed. It was confirmed by comparing the resolving powers after and before resolution recovery. The MTF analysis showed resolution improvement. The resolution improvement was achieved but the image noise raised considerably, which is clearly visible on image histograms. Despite this disadvantage the proposed method can be successfully used in practice, especially in the trabecular bone studies because of high contrast between trabeculae and intertrabecular spaces

  6. A novel method of the image processing on irregular triangular meshes

    Science.gov (United States)

    Vishnyakov, Sergey; Pekhterev, Vitaliy; Sokolova, Elizaveta

    2018-04-01

    The paper describes a novel method of the image processing based on irregular triangular meshes implementation. The triangular mesh is adaptive to the image content, least mean square linear approximation is proposed for the basic interpolation within the triangle. It is proposed to use triangular numbers to simplify using of the local (barycentric) coordinates for the further analysis - triangular element of the initial irregular mesh is to be represented through the set of the four equilateral triangles. This allows to use fast and simple pixels indexing in local coordinates, e.g. "for" or "while" loops for access to the pixels. Moreover, representation proposed allows to use discrete cosine transform of the simple "rectangular" symmetric form without additional pixels reordering (as it is used for shape-adaptive DCT forms). Furthermore, this approach leads to the simple form of the wavelet transform on triangular mesh. The results of the method application are presented. It is shown that advantage of the method proposed is a combination of the flexibility of the image-adaptive irregular meshes with the simple form of the pixel indexing in local triangular coordinates and the using of the common forms of the discrete transforms for triangular meshes. Method described is proposed for the image compression, pattern recognition, image quality improvement, image search and indexing. It also may be used as a part of video coding (intra-frame or inter-frame coding, motion detection).

  7. METHOD OF IMAGE QUALITY ENHANCEMENT FOR SPACE OBJECTS

    Directory of Open Access Journals (Sweden)

    D. S. Korshunov

    2014-07-01

    Full Text Available The paper deals with an approach for image quality improvement of the space objects in the visible range of electromagnetic wave spectrum. The proposed method is based on the joint taking into account of both the motion velocity of the space supervisory apparatus and a space object observed in the near-earth space when the time of photo-detector exposure is chosen. The timing of exposure is carried out by light-signal characteristics, which determines the optimal value of the charge package formed in the charge-coupled device being irradiated. Thus, the parameters of onboard observation equipment can be selected, which provides space images suitable for interpretation. The linear resolving capacity is used as quality indicator for space images, giving a complete picture for the image contrast and geometric properties of the object on the photo. Observation scenario modeling of the space object, done by sputnik-inspector, has shown the possibility of increasing the linear resolution up to10% - 20% or up to 40% - 50% depending on the non-complanarity angle at the movement along orbits. The proposed approach to the increase of photographs quality provides getting sharp and highcontrast images of space objects by the optical-electronic equipment of the space-based remote sensing. The usage of these images makes it possible to detect in time the space technology failures, which are the result of its exploitation in the nearearth space. The proposed method can be also applied at the stage of space systems design for optical-electronic surveillance in computer models used for facilities assessment of the shooting equipment information tract.

  8. Survey: interpolation methods for whole slide image processing.

    Science.gov (United States)

    Roszkowiak, L; Korzynska, A; Zak, J; Pijanowska, D; Swiderska-Chadaj, Z; Markiewicz, T

    2017-02-01

    Evaluating whole slide images of histological and cytological samples is used in pathology for diagnostics, grading and prognosis . It is often necessary to rescale whole slide images of a very large size. Image resizing is one of the most common applications of interpolation. We collect the advantages and drawbacks of nine interpolation methods, and as a result of our analysis, we try to select one interpolation method as the preferred solution. To compare the performance of interpolation methods, test images were scaled and then rescaled to the original size using the same algorithm. The modified image was compared to the original image in various aspects. The time needed for calculations and results of quantification performance on modified images were also compared. For evaluation purposes, we used four general test images and 12 specialized biological immunohistochemically stained tissue sample images. The purpose of this survey is to determine which method of interpolation is the best to resize whole slide images, so they can be further processed using quantification methods. As a result, the interpolation method has to be selected depending on the task involving whole slide images. © 2016 The Authors Journal of Microscopy © 2016 Royal Microscopical Society.

  9. TU-H-206-04: An Effective Homomorphic Unsharp Mask Filtering Method to Correct Intensity Inhomogeneity in Daily Treatment MR Images

    International Nuclear Information System (INIS)

    Yang, D; Gach, H; Li, H; Mutic, S

    2016-01-01

    Purpose: The daily treatment MRIs acquired on MR-IGRT systems, like diagnostic MRIs, suffer from intensity inhomogeneity issue, associated with B1 and B0 inhomogeneities. An improved homomorphic unsharp mask (HUM) filtering method, automatic and robust body segmentation, and imaging field-of-view (FOV) detection methods were developed to compute the multiplicative slow-varying correction field and correct the intensity inhomogeneity. The goal is to improve and normalize the voxel intensity so that the images could be processed more accurately by quantitative methods (e.g., segmentation and registration) that require consistent image voxel intensity values. Methods: HUM methods have been widely used for years. A body mask is required, otherwise the body surface in the corrected image would be incorrectly bright due to the sudden intensity transition at the body surface. In this study, we developed an improved HUM-based correction method that includes three main components: 1) Robust body segmentation on the normalized image gradient map, 2) Robust FOV detection (needed for body segmentation) using region growing and morphologic filters, and 3) An effective implementation of HUM using repeated Gaussian convolution. Results: The proposed method was successfully tested on patient images of common anatomical sites (H/N, lung, abdomen and pelvis). Initial qualitative comparisons showed that this improved HUM method outperformed three recently published algorithms (FCM, LEMS, MICO) in both computation speed (by 50+ times) and robustness (in intermediate to severe inhomogeneity situations). Currently implemented in MATLAB, it takes 20 to 25 seconds to process a 3D MRI volume. Conclusion: Compared to more sophisticated MRI inhomogeneity correction algorithms, the improved HUM method is simple and effective. The inhomogeneity correction, body mask, and FOV detection methods developed in this study would be useful as preprocessing tools for many MRI-related research and

  10. A robust method for processing scanning probe microscopy images and determining nanoobject position and dimensions

    NARCIS (Netherlands)

    Silly, F.

    2009-01-01

    P>Processing of scanning probe microscopy (SPM) images is essential to explore nanoscale phenomena. Image processing and pattern recognition techniques are developed to improve the accuracy and consistency of nanoobject and surface characterization. We present a robust and versatile method to

  11. Ant Colony Clustering Algorithm and Improved Markov Random Fusion Algorithm in Image Segmentation of Brain Images

    Directory of Open Access Journals (Sweden)

    Guohua Zou

    2016-12-01

    Full Text Available New medical imaging technology, such as Computed Tomography and Magnetic Resonance Imaging (MRI, has been widely used in all aspects of medical diagnosis. The purpose of these imaging techniques is to obtain various qualitative and quantitative data of the patient comprehensively and accurately, and provide correct digital information for diagnosis, treatment planning and evaluation after surgery. MR has a good imaging diagnostic advantage for brain diseases. However, as the requirements of the brain image definition and quantitative analysis are always increasing, it is necessary to have better segmentation of MR brain images. The FCM (Fuzzy C-means algorithm is widely applied in image segmentation, but it has some shortcomings, such as long computation time and poor anti-noise capability. In this paper, firstly, the Ant Colony algorithm is used to determine the cluster centers and the number of FCM algorithm so as to improve its running speed. Then an improved Markov random field model is used to improve the algorithm, so that its antinoise ability can be improved. Experimental results show that the algorithm put forward in this paper has obvious advantages in image segmentation speed and segmentation effect.

  12. A modified sparse reconstruction method for three-dimensional synthetic aperture radar image

    Science.gov (United States)

    Zhang, Ziqiang; Ji, Kefeng; Song, Haibo; Zou, Huanxin

    2018-03-01

    There is an increasing interest in three-dimensional Synthetic Aperture Radar (3-D SAR) imaging from observed sparse scattering data. However, the existing 3-D sparse imaging method requires large computing times and storage capacity. In this paper, we propose a modified method for the sparse 3-D SAR imaging. The method processes the collection of noisy SAR measurements, usually collected over nonlinear flight paths, and outputs 3-D SAR imagery. Firstly, the 3-D sparse reconstruction problem is transformed into a series of 2-D slices reconstruction problem by range compression. Then the slices are reconstructed by the modified SL0 (smoothed l0 norm) reconstruction algorithm. The improved algorithm uses hyperbolic tangent function instead of the Gaussian function to approximate the l0 norm and uses the Newton direction instead of the steepest descent direction, which can speed up the convergence rate of the SL0 algorithm. Finally, numerical simulation results are given to demonstrate the effectiveness of the proposed algorithm. It is shown that our method, compared with existing 3-D sparse imaging method, performs better in reconstruction quality and the reconstruction time.

  13. Improved Mesh_Based Image Morphing ‎

    Directory of Open Access Journals (Sweden)

    Mohammed Abdullah Taha

    2017-11-01

    Full Text Available Image morphing is a multi-step process that generates a sequence of transitions between two images. The thought is to get a ₔgrouping of middle pictures which, when ₔassembled with the first pictures would represent the change from one picture to the other.  The process of morphing requires time and attention to detail in order to get good results. Morphing image requires at least two processes warping and cross dissolve. Warping is the process of geometric transformation of images. The cross dissolve is the process interpolation of color of eachₔ pixel from the first image value to theₔ corresponding second imageₔ value over the time. Image morphing techniques differ from in the approach of image warping procedure. This work presents a survey of different techniques to construct morphing images by review the different warping techniques. One of the predominant approaches of warping process is mesh warping which suffers from some problems including ghosting. This work proposed and implements an improved mesh warping technique to construct morphing images. The results show that the proposed approach can overcome the problems of the traditional mesh technique

  14. Improvement of density resolution in short-pulse hard x-ray radiographic imaging using detector stacks

    Energy Technology Data Exchange (ETDEWEB)

    Borm, B.; Gärtner, F.; Khaghani, D. [GSI Helmholtzzentrum für Schwerionenforschung, Darmstadt (Germany); Johann Wolfgang Goethe-Universität, Frankfurt am Main (Germany); Neumayer, P. [GSI Helmholtzzentrum für Schwerionenforschung, Darmstadt (Germany)

    2016-09-15

    We demonstrate that stacking several imaging plates (IPs) constitutes an easy method to increase hard x-ray detection efficiency. Used to record x-ray radiographic images produced by an intense-laser driven hard x-ray backlighter source, the IP stacks resulted in a significant improvement of the radiograph density resolution. We attribute this to the higher quantum efficiency of the combined detectors, leading to a reduced photon noise. Electron-photon transport simulations of the interaction processes in the detector reproduce the observed contrast improvement. Increasing the detection efficiency to enhance radiographic imaging capabilities is equally effective as increasing the x-ray source yield, e.g., by a larger drive laser energy.

  15. Note: A simple image processing based fiducial auto-alignment method for sample registration.

    Science.gov (United States)

    Robertson, Wesley D; Porto, Lucas R; Ip, Candice J X; Nantel, Megan K T; Tellkamp, Friedjof; Lu, Yinfei; Miller, R J Dwayne

    2015-08-01

    A simple method for the location and auto-alignment of sample fiducials for sample registration using widely available MATLAB/LabVIEW software is demonstrated. The method is robust, easily implemented, and applicable to a wide variety of experiment types for improved reproducibility and increased setup speed. The software uses image processing to locate and measure the diameter and center point of circular fiducials for distance self-calibration and iterative alignment and can be used with most imaging systems. The method is demonstrated to be fast and reliable in locating and aligning sample fiducials, provided here by a nanofabricated array, with accuracy within the optical resolution of the imaging system. The software was further demonstrated to register, load, and sample the dynamically wetted array.

  16. Method of assessing heterogeneity in images

    Science.gov (United States)

    Jacob, Richard E.; Carson, James P.

    2016-08-23

    A method of assessing heterogeneity in images is disclosed. 3D images of an object are acquired. The acquired images may be filtered and masked. Iterative decomposition is performed on the masked images to obtain image subdivisions that are relatively homogeneous. Comparative analysis, such as variogram analysis or correlogram analysis, is performed of the decomposed images to determine spatial relationships between regions of the images that are relatively homogeneous.

  17. Novel Method to Improve Radiologist Agreement in Interpretation of Serial Chest Radiographs in the ICU

    Directory of Open Access Journals (Sweden)

    Denise A Castro

    2015-01-01

    Full Text Available Objectives: To determine whether a novel method and device, called a variable attenuation plate (VAP, which equalizes chest radiographic appearance and allows for synchronization of manual image windowing with comparison studies, would improve consistency in interpretation. Materials and Methods: Research ethics board approved the prospective cohort pilot study, which included 50 patients in the intensive care unit (ICU undergoing two serial chest radiographs with a VAP placed on each one of them. The VAP allowed for equalization of density and contrast between the patients′ serial chest radiographs. Three radiologists interpreted all the studies with and without the use of VAP. Kappa and percent agreement was used to calculate agreement between radiologists′ interpretations with and without the plate. Results: Radiologist agreement was substantially higher with the VAP method, as compared to that with the non-VAP method. Kappa values between Radiologists A and B, A and C, and B and C were 46%, 55%, and 51%, respectively, which improved to 73%, 81%, and 66%, respectively, with the use of VAP. Discrepant report impressions (i.e., one radiologist′s impression of unchanged versus one or both of the other radiologists stating improved or worsened in their impression ranged from 24 to 28.6% without the use of VAP and from 10 to 16% with the use of VAP (χ2 = 7.454, P < 0.01. Opposing views (i.e., one radiologist′s impression of improved and one of the others stating disease progression or vice versa were reported in 7 (12% cases in the non-VAP group and 4 (7% cases in the VAP group (χ2 = 0.85, P = 0.54. Conclusion: Numerous factors play a role in image acquisition and image quality, which can contribute to poor consistency and reliability of portable chest radiographic interpretations. Radiologists′ agreement of image interpretation can be improved by use of a novel method consisting of a VAP and associated software and has the potential

  18. Yet Another Method for Image Segmentation based on Histograms and Heuristics

    Directory of Open Access Journals (Sweden)

    Horia-Nicolai L. Teodorescu

    2012-07-01

    Full Text Available We introduce a method for image segmentation that requires little computations, yet providing comparable results to other methods. While the proposed method resembles to the known ones based on histograms, it is still different in the use of the gray level distribution. When to the basic procedure we add several heuristic rules, the method produces results that, in some cases, may outperform the results produced by the known methods. The paper reports preliminary results. More details on the method, improvements, and results will be presented in a future paper.

  19. Cranial nerve contrast using nerve-specific fluorophores improved by paired-agent imaging with indocyanine green as a control agent

    Science.gov (United States)

    Torres, Veronica C.; Vuong, Victoria D.; Wilson, Todd; Wewel, Joshua; Byrne, Richard W.; Tichauer, Kenneth M.

    2017-09-01

    Nerve preservation during surgery is critical because damage can result in significant morbidity. This remains a challenge especially for skull base surgeries where cranial nerves (CNs) are involved because visualization and access are particularly poor in that location. We present a paired-agent imaging method to enhance identification of CNs using nerve-specific fluorophores. Two myelin-targeting imaging agents were evaluated, Oxazine 4 and Rhodamine 800, and coadministered with a control agent, indocyanine green, either intravenously or topically in rats. Fluorescence imaging was performed on excised brains ex vivo, and nerve contrast was evaluated via paired-agent ratiometric data analysis. Although contrast was improved among all experimental groups using paired-agent imaging compared to conventional, solely targeted imaging, Oxazine 4 applied directly exhibited the greatest enhancement, with a minimum 3 times improvement in CNs delineation. This work highlights the importance of accounting for nonspecific signal of targeted agents, and demonstrates that paired-agent imaging is one method capable of doing so. Although staining, rinsing, and imaging protocols need to be optimized, these findings serve as a demonstration for the potential use of paired-agent imaging to improve contrast of CNs, and consequently, surgical outcome.

  20. Multi-scale image segmentation method with visual saliency constraints and its application

    Science.gov (United States)

    Chen, Yan; Yu, Jie; Sun, Kaimin

    2018-03-01

    Object-based image analysis method has many advantages over pixel-based methods, so it is one of the current research hotspots. It is very important to get the image objects by multi-scale image segmentation in order to carry out object-based image analysis. The current popular image segmentation methods mainly share the bottom-up segmentation principle, which is simple to realize and the object boundaries obtained are accurate. However, the macro statistical characteristics of the image areas are difficult to be taken into account, and fragmented segmentation (or over-segmentation) results are difficult to avoid. In addition, when it comes to information extraction, target recognition and other applications, image targets are not equally important, i.e., some specific targets or target groups with particular features worth more attention than the others. To avoid the problem of over-segmentation and highlight the targets of interest, this paper proposes a multi-scale image segmentation method with visually saliency graph constraints. Visual saliency theory and the typical feature extraction method are adopted to obtain the visual saliency information, especially the macroscopic information to be analyzed. The visual saliency information is used as a distribution map of homogeneity weight, where each pixel is given a weight. This weight acts as one of the merging constraints in the multi- scale image segmentation. As a result, pixels that macroscopically belong to the same object but are locally different can be more likely assigned to one same object. In addition, due to the constraint of visual saliency model, the constraint ability over local-macroscopic characteristics can be well controlled during the segmentation process based on different objects. These controls will improve the completeness of visually saliency areas in the segmentation results while diluting the controlling effect for non- saliency background areas. Experiments show that this method works

  1. An inter-crystal scatter correction method for DOI PET image reconstruction

    International Nuclear Information System (INIS)

    Lam, Chih Fung; Hagiwara, Naoki; Obi, Takashi; Yamaguchi, Masahiro; Yamaya, Taiga; Murayama, Hideo

    2006-01-01

    New positron emission tomography (PET) scanners utilize depth-of-interaction (DOI) information to improve image resolution, particularly at the edge of field-of-view while maintaining high detector sensitivity. However, the inter-crystal scatter (ICS) effect cannot be neglected in DOI scanners due to the use of smaller crystals. ICS is the phenomenon wherein there are multiple scintillations for irradiation of a gamma photon due to Compton scatter in detecting crystals. In the case of ICS, only one scintillation position is approximated for detectors with Anger-type logic calculation. This causes an error in position detection and ICS worsens the image contrast, particularly for smaller hotspots. In this study, we propose to model an ICS probability by using a Monte Carlo simulator. The probability is given as a statistical relationship between the gamma photon first interaction crystal pair and the detected crystal pair. It is then used to improve the system matrix of a statistical image reconstruction algorithm, such as maximum likehood expectation maximization (ML-EM) in order to correct for the position error caused by ICS. We apply the proposed method to simulated data of the jPET-D4, which is a four-layer DOI PET being developed at the National Institute of Radiological Sciences. Our computer simulations show that image contrast is recovered successfully by the proposed method. (author)

  2. An Approach to Improve the Quality of Infrared Images of Vein-Patterns

    Directory of Open Access Journals (Sweden)

    Chih-Lung Lin

    2011-12-01

    Full Text Available This study develops an approach to improve the quality of infrared (IR images of vein-patterns, which usually have noise, low contrast, low brightness and small objects of interest, thus requiring preprocessing to improve their quality. The main characteristics of the proposed approach are that no prior knowledge about the IR image is necessary and no parameters must be preset. Two main goals are sought: impulse noise reduction and adaptive contrast enhancement technologies. In our study, a fast median-based filter (FMBF is developed as a noise reduction method. It is based on an IR imaging mechanism to detect the noisy pixels and on a modified median-based filter to remove the noisy pixels in IR images. FMBF has the advantage of a low computation load. In addition, FMBF can retain reasonably good edges and texture information when the size of the filter window increases. The most important advantage is that the peak signal-to-noise ratio (PSNR caused by FMBF is higher than the PSNR caused by the median filter. A hybrid cumulative histogram equalization (HCHE is proposed for adaptive contrast enhancement. HCHE can automatically generate a hybrid cumulative histogram (HCH based on two different pieces of information about the image histogram. HCHE can improve the enhancement effect on hot objects rather than background. The experimental results are addressed and demonstrate that the proposed approach is feasible for use as an effective and adaptive process for enhancing the quality of IR vein-pattern images.

  3. Digital image envelope: method and evaluation

    Science.gov (United States)

    Huang, H. K.; Cao, Fei; Zhou, Michael Z.; Mogel, Greg T.; Liu, Brent J.; Zhou, Xiaoqiang

    2003-05-01

    Health data security, characterized in terms of data privacy, authenticity, and integrity, is a vital issue when digital images and other patient information are transmitted through public networks in telehealth applications such as teleradiology. Mandates for ensuring health data security have been extensively discussed (for example The Health Insurance Portability and Accountability Act, HIPAA) and health informatics guidelines (such as the DICOM standard) are beginning to focus on issues of data continue to be published by organizing bodies in healthcare; however, there has not been a systematic method developed to ensure data security in medical imaging Because data privacy and authenticity are often managed primarily with firewall and password protection, we have focused our research and development on data integrity. We have developed a systematic method of ensuring medical image data integrity across public networks using the concept of the digital envelope. When a medical image is generated regardless of the modality, three processes are performed: the image signature is obtained, the DICOM image header is encrypted, and a digital envelope is formed by combining the signature and the encrypted header. The envelope is encrypted and embedded in the original image. This assures the security of both the image and the patient ID. The embedded image is encrypted again and transmitted across the network. The reverse process is performed at the receiving site. The result is two digital signatures, one from the original image before transmission, and second from the image after transmission. If the signatures are identical, there has been no alteration of the image. This paper concentrates in the method and evaluation of the digital image envelope.

  4. A quality quantitative method of silicon direct bonding based on wavelet image analysis

    Science.gov (United States)

    Tan, Xiao; Tao, Zhi; Li, Haiwang; Xu, Tiantong; Yu, Mingxing

    2018-04-01

    The rapid development of MEMS (micro-electro-mechanical systems) has received significant attention from researchers in various fields and subjects. In particular, the MEMS fabrication process is elaborate and, as such, has been the focus of extensive research inquiries. However, in MEMS fabrication, component bonding is difficult to achieve and requires a complex approach. Thus, improvements in bonding quality are relatively important objectives. A higher quality bond can only be achieved with improved measurement and testing capabilities. In particular, the traditional testing methods mainly include infrared testing, tensile testing, and strength testing, despite the fact that using these methods to measure bond quality often results in low efficiency or destructive analysis. Therefore, this paper focuses on the development of a precise, nondestructive visual testing method based on wavelet image analysis that is shown to be highly effective in practice. The process of wavelet image analysis includes wavelet image denoising, wavelet image enhancement, and contrast enhancement, and as an end result, can display an image with low background noise. In addition, because the wavelet analysis software was developed with MATLAB, it can reveal the bonding boundaries and bonding rates to precisely indicate the bond quality at all locations on the wafer. This work also presents a set of orthogonal experiments that consist of three prebonding factors, the prebonding temperature, the positive pressure value and the prebonding time, which are used to analyze the prebonding quality. This method was used to quantify the quality of silicon-to-silicon wafer bonding, yielding standard treatment quantities that could be practical for large-scale use.

  5. Computational methods for molecular imaging

    CERN Document Server

    Shi, Kuangyu; Li, Shuo

    2015-01-01

    This volume contains original submissions on the development and application of molecular imaging computing. The editors invited authors to submit high-quality contributions on a wide range of topics including, but not limited to: • Image Synthesis & Reconstruction of Emission Tomography (PET, SPECT) and other Molecular Imaging Modalities • Molecular Imaging Enhancement • Data Analysis of Clinical & Pre-clinical Molecular Imaging • Multi-Modal Image Processing (PET/CT, PET/MR, SPECT/CT, etc.) • Machine Learning and Data Mining in Molecular Imaging. Molecular imaging is an evolving clinical and research discipline enabling the visualization, characterization and quantification of biological processes taking place at the cellular and subcellular levels within intact living subjects. Computational methods play an important role in the development of molecular imaging, from image synthesis to data analysis and from clinical diagnosis to therapy individualization. This work will bring readers fro...

  6. Methods for modeling and quantification in functional imaging by positron emissions tomography and magnetic resonance imaging

    International Nuclear Information System (INIS)

    Costes, Nicolas

    2017-01-01

    This report presents experiences and researches in the field of in vivo medical imaging by positron emission tomography (PET) and magnetic resonance imaging (MRI). In particular, advances in terms of reconstruction, quantification and modeling in PET are described. The validation of processing and analysis methods is supported by the creation of data by simulation of the imaging process in PET. The recent advances of combined PET/MRI clinical cameras, allowing simultaneous acquisition of molecular/metabolic PET information, and functional/structural MRI information opens the door to unique methodological innovations, exploiting spatial alignment and simultaneity of the PET and MRI signals. It will lead to an increase in accuracy and sensitivity in the measurement of biological phenomena. In this context, the developed projects address new methodological issues related to quantification, and to the respective contributions of MRI or PET information for a reciprocal improvement of the signals of the two modalities. They open perspectives for combined analysis of the two imaging techniques, allowing optimal use of synchronous, anatomical, molecular and functional information for brain imaging. These innovative concepts, as well as data correction and analysis methods, will be easily translated into other areas of investigation using combined PET/MRI. (author) [fr

  7. A diabetic retinopathy detection method using an improved pillar K-means algorithm.

    Science.gov (United States)

    Gogula, Susmitha Valli; Divakar, Ch; Satyanarayana, Ch; Rao, Allam Appa

    2014-01-01

    The paper presents a new approach for medical image segmentation. Exudates are a visible sign of diabetic retinopathy that is the major reason of vision loss in patients with diabetes. If the exudates extend into the macular area, blindness may occur. Automated detection of exudates will assist ophthalmologists in early diagnosis. This segmentation process includes a new mechanism for clustering the elements of high-resolution images in order to improve precision and reduce computation time. The system applies K-means clustering to the image segmentation after getting optimized by Pillar algorithm; pillars are constructed in such a way that they can withstand the pressure. Improved pillar algorithm can optimize the K-means clustering for image segmentation in aspects of precision and computation time. This evaluates the proposed approach for image segmentation by comparing with Kmeans and Fuzzy C-means in a medical image. Using this method, identification of dark spot in the retina becomes easier and the proposed algorithm is applied on diabetic retinal images of all stages to identify hard and soft exudates, where the existing pillar K-means is more appropriate for brain MRI images. This proposed system help the doctors to identify the problem in the early stage and can suggest a better drug for preventing further retinal damage.

  8. Improved quality of intrafraction kilovoltage images by triggered readout of unexposed frames

    International Nuclear Information System (INIS)

    Poulsen, Per Rugaard; Jonassen, Johnny; Jensen, Carsten; Schmidt, Mai Lykkegaard

    2015-01-01

    Purpose: The gantry-mounted kilovoltage (kV) imager of modern linear accelerators can be used for real-time tumor localization during radiation treatment delivery. However, the kV image quality often suffers from cross-scatter from the megavoltage (MV) treatment beam. This study investigates readout of unexposed kV frames as a means to improve the kV image quality in a series of experiments and a theoretical model of the observed image quality improvements. Methods: A series of fluoroscopic images were acquired of a solid water phantom with an embedded gold marker and an air cavity with and without simultaneous radiation of the phantom with a 6 MV beam delivered perpendicular to the kV beam with 300 and 600 monitor units per minute (MU/min). An in-house built device triggered readout of zero, one, or multiple unexposed frames between the kV exposures. The unexposed frames contained part of the MV scatter, consequently reducing the amount of MV scatter accumulated in the exposed frames. The image quality with and without unexposed frame readout was quantified as the contrast-to-noise ratio (CNR) of the gold marker and air cavity for a range of imaging frequencies from 1 to 15 Hz. To gain more insight into the observed CNR changes, the image lag of the kV imager was measured and used as input in a simple model that describes the CNR with unexposed frame readout in terms of the contrast, kV noise, and MV noise measured without readout of unexposed frames. Results: Without readout of unexposed kV frames, the quality of intratreatment kV images decreased dramatically with reduced kV frequencies due to MV scatter. The gold marker was only visible for imaging frequencies ≥3 Hz at 300 MU/min and ≥5 Hz for 600 MU/min. Visibility of the air cavity required even higher imaging frequencies. Readout of multiple unexposed frames ensured visibility of both structures at all imaging frequencies and a CNR that was independent of the kV frame rate. The image lag was 12.2%, 2

  9. Illumination normalization of face image based on illuminant direction estimation and improved Retinex.

    Directory of Open Access Journals (Sweden)

    Jizheng Yi

    Full Text Available Illumination normalization of face image for face recognition and facial expression recognition is one of the most frequent and difficult problems in image processing. In order to obtain a face image with normal illumination, our method firstly divides the input face image into sixteen local regions and calculates the edge level percentage in each of them. Secondly, three local regions, which meet the requirements of lower complexity and larger average gray value, are selected to calculate the final illuminant direction according to the error function between the measured intensity and the calculated intensity, and the constraint function for an infinite light source model. After knowing the final illuminant direction of the input face image, the Retinex algorithm is improved from two aspects: (1 we optimize the surround function; (2 we intercept the values in both ends of histogram of face image, determine the range of gray levels, and stretch the range of gray levels into the dynamic range of display device. Finally, we achieve illumination normalization and get the final face image. Unlike previous illumination normalization approaches, the method proposed in this paper does not require any training step or any knowledge of 3D face and reflective surface model. The experimental results using extended Yale face database B and CMU-PIE show that our method achieves better normalization effect comparing with the existing techniques.

  10. Illumination normalization of face image based on illuminant direction estimation and improved Retinex.

    Science.gov (United States)

    Yi, Jizheng; Mao, Xia; Chen, Lijiang; Xue, Yuli; Rovetta, Alberto; Caleanu, Catalin-Daniel

    2015-01-01

    Illumination normalization of face image for face recognition and facial expression recognition is one of the most frequent and difficult problems in image processing. In order to obtain a face image with normal illumination, our method firstly divides the input face image into sixteen local regions and calculates the edge level percentage in each of them. Secondly, three local regions, which meet the requirements of lower complexity and larger average gray value, are selected to calculate the final illuminant direction according to the error function between the measured intensity and the calculated intensity, and the constraint function for an infinite light source model. After knowing the final illuminant direction of the input face image, the Retinex algorithm is improved from two aspects: (1) we optimize the surround function; (2) we intercept the values in both ends of histogram of face image, determine the range of gray levels, and stretch the range of gray levels into the dynamic range of display device. Finally, we achieve illumination normalization and get the final face image. Unlike previous illumination normalization approaches, the method proposed in this paper does not require any training step or any knowledge of 3D face and reflective surface model. The experimental results using extended Yale face database B and CMU-PIE show that our method achieves better normalization effect comparing with the existing techniques.

  11. Improving supervised classification accuracy using non-rigid multimodal image registration: detecting prostate cancer

    Science.gov (United States)

    Chappelow, Jonathan; Viswanath, Satish; Monaco, James; Rosen, Mark; Tomaszewski, John; Feldman, Michael; Madabhushi, Anant

    2008-03-01

    Computer-aided diagnosis (CAD) systems for the detection of cancer in medical images require precise labeling of training data. For magnetic resonance (MR) imaging (MRI) of the prostate, training labels define the spatial extent of prostate cancer (CaP); the most common source for these labels is expert segmentations. When ancillary data such as whole mount histology (WMH) sections, which provide the gold standard for cancer ground truth, are available, the manual labeling of CaP can be improved by referencing WMH. However, manual segmentation is error prone, time consuming and not reproducible. Therefore, we present the use of multimodal image registration to automatically and accurately transcribe CaP from histology onto MRI following alignment of the two modalities, in order to improve the quality of training data and hence classifier performance. We quantitatively demonstrate the superiority of this registration-based methodology by comparing its results to the manual CaP annotation of expert radiologists. Five supervised CAD classifiers were trained using the labels for CaP extent on MRI obtained by the expert and 4 different registration techniques. Two of the registration methods were affi;ne schemes; one based on maximization of mutual information (MI) and the other method that we previously developed, Combined Feature Ensemble Mutual Information (COFEMI), which incorporates high-order statistical features for robust multimodal registration. Two non-rigid schemes were obtained by succeeding the two affine registration methods with an elastic deformation step using thin-plate splines (TPS). In the absence of definitive ground truth for CaP extent on MRI, classifier accuracy was evaluated against 7 ground truth surrogates obtained by different combinations of the expert and registration segmentations. For 26 multimodal MRI-WMH image pairs, all four registration methods produced a higher area under the receiver operating characteristic curve compared to that

  12. An instrument for small-animal imaging using time-resolved diffuse and fluorescence optical methods

    International Nuclear Information System (INIS)

    Montcel, Bruno; Poulet, Patrick

    2006-01-01

    We describe time-resolved optical methods that use diffuse near-infrared photons to image the optical properties of tissues and their inner fluorescent probe distribution. The assembled scanner uses picosecond laser diodes at 4 wavelengths, an 8-anode photo-multiplier tube and time-correlated single photon counting. Optical absorption and reduced scattering images as well as fluorescence emission images are computed from temporal profiles of diffuse photons. This method should improve the spatial resolution and the quantification of fluorescence signals. We used the diffusion approximation of the radiation transport equation and the finite element method to solve the forward problem. The inverse problem is solved with an optimization algorithm such as ART or conjugate gradient. The scanner and its performances are presented, together with absorption, scattering and fluorescent images obtained with it

  13. Applications of process improvement techniques to improve workflow in abdominal imaging.

    Science.gov (United States)

    Tamm, Eric Peter

    2016-03-01

    Major changes in the management and funding of healthcare are underway that will markedly change the way radiology studies will be reimbursed. The result will be the need to deliver radiology services in a highly efficient manner while maintaining quality. The science of process improvement provides a practical approach to improve the processes utilized in radiology. This article will address in a step-by-step manner how to implement process improvement techniques to improve workflow in abdominal imaging.

  14. Improvement of User's Accuracy Through Classification of Principal Component Images and Stacked Temporal Images

    Institute of Scientific and Technical Information of China (English)

    Nilanchal Patel; Brijesh Kumar Kaushal

    2010-01-01

    The classification accuracy of the various categories on the classified remotely sensed images are usually evaluated by two different measures of accuracy, namely, producer's accuracy (PA) and user's accuracy (UA). The PA of a category indicates to what extent the reference pixels of the category are correctly classified, whereas the UA ora category represents to what extent the other categories are less misclassified into the category in question. Therefore, the UA of the various categories determines the reliability of their interpretation on the classified image and is more important to the analyst than the PA. The present investigation has been performed in order to determine ifthere occurs improvement in the UA of the various categories on the classified image of the principal components of the original bands and on the classified image of the stacked image of two different years. We performed the analyses using the IRS LISS Ⅲ images of two different years, i.e., 1996 and 2009, that represent the different magnitude of urbanization and the stacked image of these two years pertaining to Ranchi area, Jharkhand, India, with a view to assessing the impacts of urbanization on the UA of the different categories. The results of the investigation demonstrated that there occurs significant improvement in the UA of the impervious categories in the classified image of the stacked image, which is attributable to the aggregation of the spectral information from twice the number of bands from two different years. On the other hand, the classified image of the principal components did not show any improvement in the UA as compared to the original images.

  15. MRI Brain Images Healthy and Pathological Tissues Classification with the Aid of Improved Particle Swarm Optimization and Neural Network

    Science.gov (United States)

    Sheejakumari, V.; Sankara Gomathi, B.

    2015-01-01

    The advantages of magnetic resonance imaging (MRI) over other diagnostic imaging modalities are its higher spatial resolution and its better discrimination of soft tissue. In the previous tissues classification method, the healthy and pathological tissues are classified from the MRI brain images using HGANN. But the method lacks sensitivity and accuracy measures. The classification method is inadequate in its performance in terms of these two parameters. So, to avoid these drawbacks, a new classification method is proposed in this paper. Here, new tissues classification method is proposed with improved particle swarm optimization (IPSO) technique to classify the healthy and pathological tissues from the given MRI images. Our proposed classification method includes the same four stages, namely, tissue segmentation, feature extraction, heuristic feature selection, and tissue classification. The method is implemented and the results are analyzed in terms of various statistical performance measures. The results show the effectiveness of the proposed classification method in classifying the tissues and the achieved improvement in sensitivity and accuracy measures. Furthermore, the performance of the proposed technique is evaluated by comparing it with the other segmentation methods. PMID:25977706

  16. Parallel MR image reconstruction using augmented Lagrangian methods.

    Science.gov (United States)

    Ramani, Sathish; Fessler, Jeffrey A

    2011-03-01

    Magnetic resonance image (MRI) reconstruction using SENSitivity Encoding (SENSE) requires regularization to suppress noise and aliasing effects. Edge-preserving and sparsity-based regularization criteria can improve image quality, but they demand computation-intensive nonlinear optimization. In this paper, we present novel methods for regularized MRI reconstruction from undersampled sensitivity encoded data--SENSE-reconstruction--using the augmented Lagrangian (AL) framework for solving large-scale constrained optimization problems. We first formulate regularized SENSE-reconstruction as an unconstrained optimization task and then convert it to a set of (equivalent) constrained problems using variable splitting. We then attack these constrained versions in an AL framework using an alternating minimization method, leading to algorithms that can be implemented easily. The proposed methods are applicable to a general class of regularizers that includes popular edge-preserving (e.g., total-variation) and sparsity-promoting (e.g., l(1)-norm of wavelet coefficients) criteria and combinations thereof. Numerical experiments with synthetic and in vivo human data illustrate that the proposed AL algorithms converge faster than both general-purpose optimization algorithms such as nonlinear conjugate gradient (NCG) and state-of-the-art MFISTA.

  17. Gun bore flaw image matching based on improved SIFT descriptor

    Science.gov (United States)

    Zeng, Luan; Xiong, Wei; Zhai, You

    2013-01-01

    In order to increase the operation speed and matching ability of SIFT algorithm, the SIFT descriptor and matching strategy are improved. First, a method of constructing feature descriptor based on sector area is proposed. By computing the gradients histogram of location bins which are parted into 6 sector areas, a descriptor with 48 dimensions is constituted. It can reduce the dimension of feature vector and decrease the complexity of structuring descriptor. Second, it introduce a strategy that partitions the circular region into 6 identical sector areas starting from the dominate orientation. Consequently, the computational complexity is reduced due to cancellation of rotation operation for the area. The experimental results indicate that comparing with the OpenCV SIFT arithmetic, the average matching speed of the new method increase by about 55.86%. The matching veracity can be increased even under some variation of view point, illumination, rotation, scale and out of focus. The new method got satisfied results in gun bore flaw image matching. Keywords: Metrology, Flaw image matching, Gun bore, Feature descriptor

  18. Muon tomography imaging improvement using optimized limited angle data

    Science.gov (United States)

    Bai, Chuanyong; Simon, Sean; Kindem, Joel; Luo, Weidong; Sossong, Michael J.; Steiger, Matthew

    2014-05-01

    Image resolution of muon tomography is limited by the range of zenith angles of cosmic ray muons and the flux rate at sea level. Low flux rate limits the use of advanced data rebinning and processing techniques to improve image quality. By optimizing the limited angle data, however, image resolution can be improved. To demonstrate the idea, physical data of tungsten blocks were acquired on a muon tomography system. The angular distribution and energy spectrum of muons measured on the system was also used to generate simulation data of tungsten blocks of different arrangement (geometry). The data were grouped into subsets using the zenith angle and volume images were reconstructed from the data subsets using two algorithms. One was a distributed PoCA (point of closest approach) algorithm and the other was an accelerated iterative maximal likelihood/expectation maximization (MLEM) algorithm. Image resolution was compared for different subsets. Results showed that image resolution was better in the vertical direction for subsets with greater zenith angles and better in the horizontal plane for subsets with smaller zenith angles. The overall image resolution appeared to be the compromise of that of different subsets. This work suggests that the acquired data can be grouped into different limited angle data subsets for optimized image resolution in desired directions. Use of multiple images with resolution optimized in different directions can improve overall imaging fidelity and the intended applications.

  19. Improving PET spatial resolution and detectability for prostate cancer imaging

    International Nuclear Information System (INIS)

    Bal, H; Guerin, L; Casey, M E; Conti, M; Eriksson, L; Michel, C; Fanti, S; Pettinato, C; Adler, S; Choyke, P

    2014-01-01

    Prostate cancer, one of the most common forms of cancer among men, can benefit from recent improvements in positron emission tomography (PET) technology. In particular, better spatial resolution, lower noise and higher detectability of small lesions could be greatly beneficial for early diagnosis and could provide a strong support for guiding biopsy and surgery. In this article, the impact of improved PET instrumentation with superior spatial resolution and high sensitivity are discussed, together with the latest development in PET technology: resolution recovery and time-of-flight reconstruction. Using simulated cancer lesions, inserted in clinical PET images obtained with conventional protocols, we show that visual identification of the lesions and detectability via numerical observers can already be improved using state of the art PET reconstruction methods. This was achieved using both resolution recovery and time-of-flight reconstruction, and a high resolution image with 2 mm pixel size. Channelized Hotelling numerical observers showed an increase in the area under the LROC curve from 0.52 to 0.58. In addition, a relationship between the simulated input activity and the area under the LROC curve showed that the minimum detectable activity was reduced by more than 23%. (paper)

  20. Resolution enhancement of tri-stereo remote sensing images by super resolution methods

    Science.gov (United States)

    Tuna, Caglayan; Akoguz, Alper; Unal, Gozde; Sertel, Elif

    2016-10-01

    Super resolution (SR) refers to generation of a High Resolution (HR) image from a decimated, blurred, low-resolution (LR) image set, which can be either a single frame or multi-frame that contains a collection of several images acquired from slightly different views of the same observation area. In this study, we propose a novel application of tri-stereo Remote Sensing (RS) satellite images to the super resolution problem. Since the tri-stereo RS images of the same observation area are acquired from three different viewing angles along the flight path of the satellite, these RS images are properly suited to a SR application. We first estimate registration between the chosen reference LR image and other LR images to calculate the sub pixel shifts among the LR images. Then, the warping, blurring and down sampling matrix operators are created as sparse matrices to avoid high memory and computational requirements, which would otherwise make the RS-SR solution impractical. Finally, the overall system matrix, which is constructed based on the obtained operator matrices is used to obtain the estimate HR image in one step in each iteration of the SR algorithm. Both the Laplacian and total variation regularizers are incorporated separately into our algorithm and the results are presented to demonstrate an improved quantitative performance against the standard interpolation method as well as improved qualitative results due expert evaluations.

  1. A Hybrid Vehicle Detection Method Based on Viola-Jones and HOG + SVM from UAV Images

    Science.gov (United States)

    Xu, Yongzheng; Yu, Guizhen; Wang, Yunpeng; Wu, Xinkai; Ma, Yalong

    2016-01-01

    A new hybrid vehicle detection scheme which integrates the Viola-Jones (V-J) and linear SVM classifier with HOG feature (HOG + SVM) methods is proposed for vehicle detection from low-altitude unmanned aerial vehicle (UAV) images. As both V-J and HOG + SVM are sensitive to on-road vehicles’ in-plane rotation, the proposed scheme first adopts a roadway orientation adjustment method, which rotates each UAV image to align the roads with the horizontal direction so the original V-J or HOG + SVM method can be directly applied to achieve fast detection and high accuracy. To address the issue of descending detection speed for V-J and HOG + SVM, the proposed scheme further develops an adaptive switching strategy which sophistically integrates V-J and HOG + SVM methods based on their different descending trends of detection speed to improve detection efficiency. A comprehensive evaluation shows that the switching strategy, combined with the road orientation adjustment method, can significantly improve the efficiency and effectiveness of the vehicle detection from UAV images. The results also show that the proposed vehicle detection method is competitive compared with other existing vehicle detection methods. Furthermore, since the proposed vehicle detection method can be performed on videos captured from moving UAV platforms without the need of image registration or additional road database, it has great potentials of field applications. Future research will be focusing on expanding the current method for detecting other transportation modes such as buses, trucks, motors, bicycles, and pedestrians. PMID:27548179

  2. A Hybrid Vehicle Detection Method Based on Viola-Jones and HOG + SVM from UAV Images.

    Science.gov (United States)

    Xu, Yongzheng; Yu, Guizhen; Wang, Yunpeng; Wu, Xinkai; Ma, Yalong

    2016-08-19

    A new hybrid vehicle detection scheme which integrates the Viola-Jones (V-J) and linear SVM classifier with HOG feature (HOG + SVM) methods is proposed for vehicle detection from low-altitude unmanned aerial vehicle (UAV) images. As both V-J and HOG + SVM are sensitive to on-road vehicles' in-plane rotation, the proposed scheme first adopts a roadway orientation adjustment method, which rotates each UAV image to align the roads with the horizontal direction so the original V-J or HOG + SVM method can be directly applied to achieve fast detection and high accuracy. To address the issue of descending detection speed for V-J and HOG + SVM, the proposed scheme further develops an adaptive switching strategy which sophistically integrates V-J and HOG + SVM methods based on their different descending trends of detection speed to improve detection efficiency. A comprehensive evaluation shows that the switching strategy, combined with the road orientation adjustment method, can significantly improve the efficiency and effectiveness of the vehicle detection from UAV images. The results also show that the proposed vehicle detection method is competitive compared with other existing vehicle detection methods. Furthermore, since the proposed vehicle detection method can be performed on videos captured from moving UAV platforms without the need of image registration or additional road database, it has great potentials of field applications. Future research will be focusing on expanding the current method for detecting other transportation modes such as buses, trucks, motors, bicycles, and pedestrians.

  3. Apparatus and method X-ray image processing

    International Nuclear Information System (INIS)

    1984-01-01

    The invention relates to a method for X-ray image processing. The radiation passed through the object is transformed into an electric image signal from which the logarithmic value is determined and displayed by a display device. Its main objective is to provide a method and apparatus that renders X-ray images or X-ray subtraction images with strong reduction of stray radiation. (Auth.)

  4. Color camera computed tomography imaging spectrometer for improved spatial-spectral image accuracy

    Science.gov (United States)

    Wilson, Daniel W. (Inventor); Bearman, Gregory H. (Inventor); Johnson, William R. (Inventor)

    2011-01-01

    Computed tomography imaging spectrometers ("CTIS"s) having color focal plane array detectors are provided. The color FPA detector may comprise a digital color camera including a digital image sensor, such as a Foveon X3.RTM. digital image sensor or a Bayer color filter mosaic. In another embodiment, the CTIS includes a pattern imposed either directly on the object scene being imaged or at the field stop aperture. The use of a color FPA detector and the pattern improves the accuracy of the captured spatial and spectral information.

  5. An Interactive Method Based on the Live Wire for Segmentation of the Breast in Mammography Images

    OpenAIRE

    Zewei, Zhang; Tianyue, Wang; Li, Guo; Tingting, Wang; Lu, Xu

    2014-01-01

    In order to improve accuracy of computer-aided diagnosis of breast lumps, the authors introduce an improved interactive segmentation method based on Live Wire. This paper presents the Gabor filters and FCM clustering algorithm is introduced to the Live Wire cost function definition. According to the image FCM analysis for image edge enhancement, we eliminate the interference of weak edge and access external features clear segmentation results of breast lumps through improving Live Wire on two...

  6. A NEW IMAGE REGISTRATION METHOD FOR GREY IMAGES

    Institute of Scientific and Technical Information of China (English)

    Nie Xuan; Zhao Rongchun; Jiang Zetao

    2004-01-01

    The proposed algorithm relies on a group of new formulas for calculating tangent slope so as to address angle feature of edge curves of image. It can utilize tangent angle features to estimate automatically and fully the rotation parameters of geometric transform and enable rough matching of images with huge rotation difference. After angle compensation, it can search for matching point sets by correlation criterion, then calculate parameters of affine transform, enable higher-precision emendation of rotation and transferring. Finally, it fulfills precise matching for images with relax-tense iteration method. Compared with the registration approach based on wavelet direction-angle features, the matching algorithm with tangent feature of image edge is more robust and realizes precise registration of various images. Furthermore, it is also helpful in graphics matching.

  7. Numerical methods for image registration

    CERN Document Server

    Modersitzki, Jan

    2003-01-01

    Based on the author's lecture notes and research, this well-illustrated and comprehensive text is one of the first to provide an introduction to image registration with particular emphasis on numerical methods in medical imaging. Ideal for researchers in industry and academia, it is also a suitable study guide for graduate mathematicians, computer scientists, engineers, medical physicists, and radiologists.Image registration is utilised whenever information obtained from different viewpoints needs to be combined or compared and unwanted distortion needs to be eliminated. For example, CCTV imag

  8. A color fusion method of infrared and low-light-level images based on visual perception

    Science.gov (United States)

    Han, Jing; Yan, Minmin; Zhang, Yi; Bai, Lianfa

    2014-11-01

    The color fusion images can be obtained through the fusion of infrared and low-light-level images, which will contain both the information of the two. The fusion images can help observers to understand the multichannel images comprehensively. However, simple fusion may lose the target information due to inconspicuous targets in long-distance infrared and low-light-level images; and if targets extraction is adopted blindly, the perception of the scene information will be affected seriously. To solve this problem, a new fusion method based on visual perception is proposed in this paper. The extraction of the visual targets ("what" information) and parallel processing mechanism are applied in traditional color fusion methods. The infrared and low-light-level color fusion images are achieved based on efficient typical targets learning. Experimental results show the effectiveness of the proposed method. The fusion images achieved by our algorithm can not only improve the detection rate of targets, but also get rich natural information of the scenes.

  9. Method of improving the performance of lenses for use in thermal infrared

    Science.gov (United States)

    McDowell, M. W.; Klee, H. W.

    1980-10-01

    A method is described whereby the field performance of an all-germanium triplet, as used for imaging radiation in the 8 to 13 micron waveband, can be improved. The principle of the method, which could also be used to improve the performance of achromatic triplets or aspherized doublets, involves the use of a field flattener lens which replaces the germanium window of the detector. The curvature of this lens can be optimized to minimize field curvature, which together with chromatic aberration is one of the most serious residuals of thermal imaging systems with relative apertures of around f/0.7. It is also shown that for such relative apertures, and for typical fields of less than 15 degrees, at 100 mm focal length, the location of the aperture stop is not a significant design parameter. This arises as a result of the intrinsic optical properties of germanium.

  10. Development of rapid methods for relaxation time mapping and motion estimation using magnetic resonance imaging

    Energy Technology Data Exchange (ETDEWEB)

    Gilani, Syed Irtiza Ali

    2008-09-15

    Recent technological developments in the field of magnetic resonance imaging have resulted in advanced techniques that can reduce the total time to acquire images. For applications such as relaxation time mapping, which enables improved visualisation of in vivo structures, rapid imaging techniques are highly desirable. TAPIR is a Look- Locker-based sequence for high-resolution, multislice T{sub 1} relaxation time mapping. Despite the high accuracy and precision of TAPIR, an improvement in the k-space sampling trajectory is desired to acquire data in clinically acceptable times. In this thesis, a new trajectory, termed line-sharing, is introduced for TAPIR that can potentially reduce the acquisition time by 40 %. Additionally, the line-sharing method was compared with the GRAPPA parallel imaging method. These methods were employed to reconstruct time-point images from the data acquired on a 4T high-field MR research scanner. Multislice, multipoint in vivo results obtained using these methods are presented. Despite improvement in acquisition speed, through line-sharing, for example, motion remains a problem and artefact-free data cannot always be obtained. Therefore, in this thesis, a rapid technique is introduced to estimate in-plane motion. The presented technique is based on calculating the in-plane motion parameters, i.e., translation and rotation, by registering the low-resolution MR images. The rotation estimation method is based on the pseudo-polar FFT, where the Fourier domain is composed of frequencies that reside in an oversampled set of non-angularly, equispaced points. The essence of the method is that unlike other Fourier-based registration schemes, the employed approach does not require any interpolation to calculate the pseudo-polar FFT grid coordinates. Translation parameters are estimated by the phase correlation method. However, instead of two-dimensional analysis of the phase correlation matrix, a low complexity subspace identification of the phase

  11. Development of rapid methods for relaxation time mapping and motion estimation using magnetic resonance imaging

    International Nuclear Information System (INIS)

    Gilani, Syed Irtiza Ali

    2008-09-01

    Recent technological developments in the field of magnetic resonance imaging have resulted in advanced techniques that can reduce the total time to acquire images. For applications such as relaxation time mapping, which enables improved visualisation of in vivo structures, rapid imaging techniques are highly desirable. TAPIR is a Look- Locker-based sequence for high-resolution, multislice T 1 relaxation time mapping. Despite the high accuracy and precision of TAPIR, an improvement in the k-space sampling trajectory is desired to acquire data in clinically acceptable times. In this thesis, a new trajectory, termed line-sharing, is introduced for TAPIR that can potentially reduce the acquisition time by 40 %. Additionally, the line-sharing method was compared with the GRAPPA parallel imaging method. These methods were employed to reconstruct time-point images from the data acquired on a 4T high-field MR research scanner. Multislice, multipoint in vivo results obtained using these methods are presented. Despite improvement in acquisition speed, through line-sharing, for example, motion remains a problem and artefact-free data cannot always be obtained. Therefore, in this thesis, a rapid technique is introduced to estimate in-plane motion. The presented technique is based on calculating the in-plane motion parameters, i.e., translation and rotation, by registering the low-resolution MR images. The rotation estimation method is based on the pseudo-polar FFT, where the Fourier domain is composed of frequencies that reside in an oversampled set of non-angularly, equispaced points. The essence of the method is that unlike other Fourier-based registration schemes, the employed approach does not require any interpolation to calculate the pseudo-polar FFT grid coordinates. Translation parameters are estimated by the phase correlation method. However, instead of two-dimensional analysis of the phase correlation matrix, a low complexity subspace identification of the phase

  12. Multiscale bilateral filtering for improving image quality in digital breast tomosynthesis

    Science.gov (United States)

    Lu, Yao; Chan, Heang-Ping; Wei, Jun; Hadjiiski, Lubomir M.; Samala, Ravi K.

    2015-01-01

    Purpose: Detection of subtle microcalcifications in digital breast tomosynthesis (DBT) is a challenging task because of the large, noisy DBT volume. It is important to enhance the contrast-to-noise ratio (CNR) of microcalcifications in DBT reconstruction. Most regularization methods depend on local gradient and may treat the ill-defined margins or subtle spiculations of masses and subtle microcalcifications as noise because of their small gradient. The authors developed a new multiscale bilateral filtering (MSBF) regularization method for the simultaneous algebraic reconstruction technique (SART) to improve the CNR of microcalcifications without compromising the quality of masses. Methods: The MSBF exploits a multiscale structure of DBT images to suppress noise and selectively enhance high frequency structures. At the end of each SART iteration, every DBT slice is decomposed into several frequency bands via Laplacian pyramid decomposition. No regularization is applied to the low frequency bands so that subtle edges of masses and structured background are preserved. Bilateral filtering is applied to the high frequency bands to enhance microcalcifications while suppressing noise. The regularized DBT images are used for updating in the next SART iteration. The new MSBF method was compared with the nonconvex total p-variation (TpV) method for noise regularization with SART. A GE GEN2 prototype DBT system was used for acquisition of projections at 21 angles in 3° increments over a ±30° range. The reconstruction image quality with no regularization (NR) and that with the two regularization methods were compared using the DBT scans of a heterogeneous breast phantom and several human subjects with masses and microcalcifications. The CNR and the full width at half maximum (FWHM) of the line profiles of microcalcifications and across the spiculations within their in-focus DBT slices were used as image quality measures. Results: The MSBF method reduced contouring artifacts

  13. Institutional Image: How to Define, Improve, Market It.

    Science.gov (United States)

    Topor, Robert S.

    Advice for colleges on how to identify, develop, and communicate a positive image for the institution is offered in this handbook. The use of market research techniques to measure image is discussed along with advice on how to improve an image so that it contributes to a unified marketing plan. The first objective is to create and communicate some…

  14. ImageX: new and improved image explorer for astronomical images and beyond

    Science.gov (United States)

    Hayashi, Soichi; Gopu, Arvind; Kotulla, Ralf; Young, Michael D.

    2016-08-01

    The One Degree Imager - Portal, Pipeline, and Archive (ODI-PPA) has included the Image Explorer interactive image visualization tool since it went operational. Portal users were able to quickly open up several ODI images within any HTML5 capable web browser, adjust the scaling, apply color maps, and perform other basic image visualization steps typically done on a desktop client like DS9. However, the original design of the Image Explorer required lossless PNG tiles to be generated and stored for all raw and reduced ODI images thereby taking up tens of TB of spinning disk space even though a small fraction of those images were being accessed by portal users at any given time. It also caused significant overhead on the portal web application and the Apache webserver used by ODI-PPA. We found it hard to merge in improvements made to a similar deployment in another project's portal. To address these concerns, we re-architected Image Explorer from scratch and came up with ImageX, a set of microservices that are part of the IU Trident project software suite, with rapid interactive visualization capabilities useful for ODI data and beyond. We generate a full resolution JPEG image for each raw and reduced ODI FITS image before producing a JPG tileset, one that can be rendered using the ImageX frontend code at various locations as appropriate within a web portal (for example: on tabular image listings, views allowing quick perusal of a set of thumbnails or other image sifting activities). The new design has decreased spinning disk requirements, uses AngularJS for the client side Model/View code (instead of depending on backend PHP Model/View/Controller code previously used), OpenSeaDragon to render the tile images, and uses nginx and a lightweight NodeJS application to serve tile images thereby significantly decreasing the Time To First Byte latency by a few orders of magnitude. We plan to extend ImageX for non-FITS images including electron microscopy and radiology scan

  15. A study of the x-ray image quality improvement in the examination of the respiratory system based on the new image processing technique

    Science.gov (United States)

    Nagai, Yuichi; Kitagawa, Mayumi; Torii, Jun; Iwase, Takumi; Aso, Tomohiko; Ihara, Kanyu; Fujikawa, Mari; Takeuchi, Yumiko; Suzuki, Katsumi; Ishiguro, Takashi; Hara, Akio

    2014-03-01

    Recently, the double contrast technique in a gastrointestinal examination and the transbronchial lung biopsy in an examination for the respiratory system [1-3] have made a remarkable progress. Especially in the transbronchial lung biopsy, better quality of x-ray fluoroscopic images is requested because this examination is performed under a guidance of x-ray fluoroscopic images. On the other hand, various image processing methods [4] for x-ray fluoroscopic images have been developed as an x-ray system with a flat panel detector [5-7] is widely used. A recursive filtering is an effective method to reduce a random noise in x-ray fluoroscopic images. However it has a limitation for its effectiveness of a noise reduction in case of a moving object exists in x-ray fluoroscopic images because the recursive filtering is a noise reduction method by adding last few images. After recursive filtering a residual signal was produced if a moving object existed in x-ray images, and this residual signal disturbed a smooth procedure of the examinations. To improve this situation, new noise reduction method has been developed. The Adaptive Noise Reduction [ANR] is the brand-new noise reduction technique which can be reduced only a noise regardless of the moving object in x-ray fluoroscopic images. Therefore the ANR is a very suitable noise reduction method for the transbronchial lung biopsy under a guidance of x-ray fluoroscopic images because the residual signal caused of the moving object in x-ray fluoroscopic images is never produced after the ANR. In this paper, we will explain an advantage of the ANR by comparing of a performance between the ANR images and the conventional recursive filtering images.

  16. Evaluation of automatic cloud removal method for high elevation areas in Landsat 8 OLI images to improve environmental indexes computation

    Science.gov (United States)

    Alvarez, César I.; Teodoro, Ana; Tierra, Alfonso

    2017-10-01

    Thin clouds in the optical remote sensing data are frequent and in most of the cases don't allow to have a pure surface data in order to calculate some indexes as Normalized Difference Vegetation Index (NDVI). This paper aims to evaluate the Automatic Cloud Removal Method (ACRM) algorithm over a high elevation city like Quito (Ecuador), with an altitude of 2800 meters above sea level, where the clouds are presented all the year. The ACRM is an algorithm that considers a linear regression between each Landsat 8 OLI band and the Cirrus band using the slope obtained with the linear regression established. This algorithm was employed without any reference image or mask to try to remove the clouds. The results of the application of the ACRM algorithm over Quito didn't show a good performance. Therefore, was considered improving this algorithm using a different slope value data (ACMR Improved). After, the NDVI computation was compared with a reference NDVI MODIS data (MOD13Q1). The ACMR Improved algorithm had a successful result when compared with the original ACRM algorithm. In the future, this Improved ACRM algorithm needs to be tested in different regions of the world with different conditions to evaluate if the algorithm works successfully for all conditions.

  17. Image restoration and processing methods

    International Nuclear Information System (INIS)

    Daniell, G.J.

    1984-01-01

    This review will stress the importance of using image restoration techniques that deal with incomplete, inconsistent, and noisy data and do not introduce spurious features into the processed image. No single image is equally suitable for both the resolution of detail and the accurate measurement of intensities. A good general purpose technique is the maximum entropy method and the basis and use of this will be explained. (orig.)

  18. Examination of attenuation correction method for cerebral blood Flow SPECT Using MR imaging

    International Nuclear Information System (INIS)

    Mizuno, Takashi; Takahashi, Masaaki

    2009-01-01

    Authors developed a software for attenuation correction using MR imaging (MRAC) (Toshiba Med. System Engineer.) based on the idea that precision of AC could be improved by the head contour in MRI T2-weighted images (T2WI) obtained before 123 I-iofetamine (IMP) single photon emission computed tomography (SPECT) for cerebral blood flow (CBF) measurement. In the present study, this MRAC was retrospectively evaluated by comparison with the previous standard AC methods derived from transmission CT (TCT) and X-CT which overcoming the problem of sinogram threshold Chang method but still having cost and patient exposure issues. MRAC was essentially performed in the Toshiba GMS5500/PI processor where 3D registration was conducted with images of SPECT and MRI of the same patient. The gamma camera for 123 I-IMP SPECT and 99m TcO 4 - TCT was Toshiba 3-detector GCA9300A equipped with the above processor for MRAC and with low energy high resolution (LEHR) fan beam collimator. Machines for MRI and CT were Siemens-Asahi Meditech. MAGNETOM Symphony 1.5T and SOMATOM plus4, respectively. MRAC was examined in 8 patients with images of T1WI, TCT and SPECT, and in 18 of T2WI, CT and SPECT. Evaluation was made by comparison of attenuation coefficients (μ) by the 4 methods. As a result, the present MRAC was found to be closer to AC by TCT and CT than by the Chang method since MRAC, due to exact imaging of the head contour, was independent on radiation count, and was thought to be useful for improving the precision of CBF SPECT. (K.T.)

  19. Numerical study of water diffusion in biological tissues using an improved finite difference method

    International Nuclear Information System (INIS)

    Xu Junzhong; Does, Mark D; Gore, John C

    2007-01-01

    An improved finite difference (FD) method has been developed in order to calculate the behaviour of the nuclear magnetic resonance signal variations caused by water diffusion in biological tissues more accurately and efficiently. The algorithm converts the conventional image-based finite difference method into a convenient matrix-based approach and includes a revised periodic boundary condition which eliminates the edge effects caused by artificial boundaries in conventional FD methods. Simulated results for some modelled tissues are consistent with analytical solutions for commonly used diffusion-weighted pulse sequences, whereas the improved FD method shows improved efficiency and accuracy. A tightly coupled parallel computing approach was also developed to implement the FD methods to enable large-scale simulations of realistic biological tissues. The potential applications of the improved FD method for understanding diffusion in tissues are also discussed. (note)

  20. A pilot study of three dimensional color CT images of brain diseases to improve informed consent

    International Nuclear Information System (INIS)

    Tanizaki, Yoshio; Akiyama, Takenori; Hiraga, Kenji; Akaji, Kazunori

    2005-01-01

    We have described brain diseases to patients and their family using monochrome CT images. It is thought that patients have difficulties in giving their consent to our conventional explanation because their understanding of brain diseases is based on three dimensional and color images, however, standard CT images are two dimensional and gray scale images. We have been trying to use three dimensional color CT images to improve the typical patient's comprehension of brain diseases. We also try to simulate surgery using these images. Multi-slice CT accumulates precise isotropic voxel data within a half minute. These two dimensional and monochrome data are converted to three dimensional color CT images by 3D workstation. Three dimensional color CT images of each brain structures (e.g. scalp, skull, brain, ventricles and lesions) are created separately. Then, selected structures are fused together for different purposes. These images are able to rotate around any axis. Because the methods to generate three-dimensional color images have not established, we neurosurgeons must create these images. In particular, when an operation is required, the surgeon should create the images. In this paper, we demonstrate how three-dimensional color CT images can improve informed consent. (author)

  1. A novel method based on learning automata for automatic lesion detection in breast magnetic resonance imaging.

    Science.gov (United States)

    Salehi, Leila; Azmi, Reza

    2014-07-01

    Breast cancer continues to be a significant public health problem in the world. Early detection is the key for improving breast cancer prognosis. In this way, magnetic resonance imaging (MRI) is emerging as a powerful tool for the detection of breast cancer. Breast MRI presently has two major challenges. First, its specificity is relatively poor, and it detects many false positives (FPs). Second, the method involves acquiring several high-resolution image volumes before, during, and after the injection of a contrast agent. The large volume of data makes the task of interpretation by the radiologist both complex and time-consuming. These challenges have led to the development of the computer-aided detection systems to improve the efficiency and accuracy of the interpretation process. Detection of suspicious regions of interests (ROIs) is a critical preprocessing step in dynamic contrast-enhanced (DCE)-MRI data evaluation. In this regard, this paper introduces a new automatic method to detect the suspicious ROIs for breast DCE-MRI based on region growing. The results indicate that the proposed method is thoroughly able to identify suspicious regions (accuracy of 75.39 ± 3.37 on PIDER breast MRI dataset). Furthermore, the FP per image in this method is averagely 7.92, which shows considerable improvement comparing to other methods like ROI hunter.

  2. Prognostic aspects of imaging method development

    International Nuclear Information System (INIS)

    Steinhart, L.

    1987-01-01

    A survey is presented of X-ray diagnostic methods and techniques and possibilities of their further development. Promising methods include direct imaging using digital radiography. In connection with computer technology these methods achieve higher resolution. The storage of obtained images in the computer memory will allow automated processing and evaluation and the use of expert systems. Development is expected to take place especially in computerized tomography using magnetic resonance, and positron computed tomography and other non-radioactive diagnostic methods. (J.B.). 5 figs., 1 tab., 1 ref

  3. Double-compression method for biomedical images

    Science.gov (United States)

    Antonenko, Yevhenii A.; Mustetsov, Timofey N.; Hamdi, Rami R.; Małecka-Massalska, Teresa; Orshubekov, Nurbek; DzierŻak, RóŻa; Uvaysova, Svetlana

    2017-08-01

    This paper describes a double compression method (DCM) of biomedical images. A comparison of image compression factors in size JPEG, PNG and developed DCM was carried out. The main purpose of the DCM - compression of medical images while maintaining the key points that carry diagnostic information. To estimate the minimum compression factor an analysis of the coding of random noise image is presented.

  4. Distributed MIMO-ISAR Sub-image Fusion Method

    Directory of Open Access Journals (Sweden)

    Gu Wenkun

    2017-02-01

    Full Text Available The fast fluctuation associated with maneuvering a target’s radar cross-section often affects the imaging performance stability of traditional monostatic Inverse Synthetic Aperture Radar (ISAR. To address this problem, in this study, we propose an imaging method based on the fusion of sub-images of frequencydiversity-distributed multiple Input-Multiple Output-Inverse Synthetic Aperture Radar (MIMO-ISAR. First, we establish the analytic expression of a two-dimensional ISAR sub-image acquired by different channels of distributed MIMO-ISAR. Then, we derive the distance and azimuth distortion factors of the image acquired by the different channels. By compensating for the distortion of the ISAR image, we ultimately realize distributed MIMO-ISAR fusion imaging. Simulations verify the validity of this imaging method using distributed MIMO-ISAR.

  5. Signal Amplification Technique (SAT): an approach for improving resolution and reducing image noise in computed tomography

    International Nuclear Information System (INIS)

    Phelps, M.E.; Huang, S.C.; Hoffman, E.J.; Plummer, D.; Carson, R.

    1981-01-01

    Spatial resolution improvements in computed tomography (CT) have been limited by the large and unique error propagation properties of this technique. The desire to provide maximum image resolution has resulted in the use of reconstruction filter functions designed to produce tomographic images with resolution as close as possible to the intrinsic detector resolution. Thus, many CT systems produce images with excessive noise with the system resolution determined by the detector resolution rather than the reconstruction algorithm. CT is a rigorous mathematical technique which applies an increasing amplification to increasing spatial frequencies in the measured data. This mathematical approach to spatial frequency amplification cannot distinguish between signal and noise and therefore both are amplified equally. We report here a method in which tomographic resolution is improved by using very small detectors to selectively amplify the signal and not noise. Thus, this approach is referred to as the signal amplification technique (SAT). SAT can provide dramatic improvements in image resolution without increases in statistical noise or dose because increases in the cutoff frequency of the reconstruction algorithm are not required to improve image resolution. Alternatively, in cases where image counts are low, such as in rapid dynamic or receptor studies, statistical noise can be reduced by lowering the cutoff frequency while still maintaining the best possible image resolution. A possible system design for a positron CT system with SAT is described

  6. A new method for face detection in colour images for emotional bio-robots

    Institute of Scientific and Technical Information of China (English)

    HAPESHI; Kevin

    2010-01-01

    Emotional bio-robots have become a hot research topic in last two decades. Though there have been some progress in research, design and development of various emotional bio-robots, few of them can be used in practical applications. The study of emotional bio-robots demands multi-disciplinary co-operation. It involves computer science, artificial intelligence, 3D computation, engineering system modelling, analysis and simulation, bionics engineering, automatic control, image processing and pattern recognition etc. Among them, face detection belongs to image processing and pattern recognition. An emotional robot must have the ability to recognize various objects, particularly, it is very important for a bio-robot to be able to recognize human faces from an image. In this paper, a face detection method is proposed for identifying any human faces in colour images using human skin model and eye detection method. Firstly, this method can be used to detect skin regions from the input colour image after normalizing its luminance. Then, all face candidates are identified using an eye detection method. Comparing with existing algorithms, this method only relies on the colour and geometrical data of human face rather than using training datasets. From experimental results, it is shown that this method is effective and fast and it can be applied to the development of an emotional bio-robot with further improvements of its speed and accuracy.

  7. Improved image quality in pinhole SPECT by accurate modeling of the point spread function in low magnification systems

    International Nuclear Information System (INIS)

    Pino, Francisco; Roé, Nuria; Aguiar, Pablo; Falcon, Carles; Ros, Domènec; Pavía, Javier

    2015-01-01

    Purpose: Single photon emission computed tomography (SPECT) has become an important noninvasive imaging technique in small-animal research. Due to the high resolution required in small-animal SPECT systems, the spatially variant system response needs to be included in the reconstruction algorithm. Accurate modeling of the system response should result in a major improvement in the quality of reconstructed images. The aim of this study was to quantitatively assess the impact that an accurate modeling of spatially variant collimator/detector response has on image-quality parameters, using a low magnification SPECT system equipped with a pinhole collimator and a small gamma camera. Methods: Three methods were used to model the point spread function (PSF). For the first, only the geometrical pinhole aperture was included in the PSF. For the second, the septal penetration through the pinhole collimator was added. In the third method, the measured intrinsic detector response was incorporated. Tomographic spatial resolution was evaluated and contrast, recovery coefficients, contrast-to-noise ratio, and noise were quantified using a custom-built NEMA NU 4–2008 image-quality phantom. Results: A high correlation was found between the experimental data corresponding to intrinsic detector response and the fitted values obtained by means of an asymmetric Gaussian distribution. For all PSF models, resolution improved as the distance from the point source to the center of the field of view increased and when the acquisition radius diminished. An improvement of resolution was observed after a minimum of five iterations when the PSF modeling included more corrections. Contrast, recovery coefficients, and contrast-to-noise ratio were better for the same level of noise in the image when more accurate models were included. Ring-type artifacts were observed when the number of iterations exceeded 12. Conclusions: Accurate modeling of the PSF improves resolution, contrast, and recovery

  8. Improved image quality in pinhole SPECT by accurate modeling of the point spread function in low magnification systems

    Energy Technology Data Exchange (ETDEWEB)

    Pino, Francisco [Unitat de Biofísica, Facultat de Medicina, Universitat de Barcelona, Barcelona 08036, Spain and Servei de Física Mèdica i Protecció Radiològica, Institut Català d’Oncologia, L’Hospitalet de Llobregat 08907 (Spain); Roé, Nuria [Unitat de Biofísica, Facultat de Medicina, Universitat de Barcelona, Barcelona 08036 (Spain); Aguiar, Pablo, E-mail: pablo.aguiar.fernandez@sergas.es [Fundación Ramón Domínguez, Complexo Hospitalario Universitario de Santiago de Compostela 15706, Spain and Grupo de Imagen Molecular, Instituto de Investigacións Sanitarias de Santiago de Compostela (IDIS), Galicia 15782 (Spain); Falcon, Carles; Ros, Domènec [Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona 08036, Spain and CIBER en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Barcelona 08036 (Spain); Pavía, Javier [Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona 080836 (Spain); CIBER en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Barcelona 08036 (Spain); and Servei de Medicina Nuclear, Hospital Clínic, Barcelona 08036 (Spain)

    2015-02-15

    Purpose: Single photon emission computed tomography (SPECT) has become an important noninvasive imaging technique in small-animal research. Due to the high resolution required in small-animal SPECT systems, the spatially variant system response needs to be included in the reconstruction algorithm. Accurate modeling of the system response should result in a major improvement in the quality of reconstructed images. The aim of this study was to quantitatively assess the impact that an accurate modeling of spatially variant collimator/detector response has on image-quality parameters, using a low magnification SPECT system equipped with a pinhole collimator and a small gamma camera. Methods: Three methods were used to model the point spread function (PSF). For the first, only the geometrical pinhole aperture was included in the PSF. For the second, the septal penetration through the pinhole collimator was added. In the third method, the measured intrinsic detector response was incorporated. Tomographic spatial resolution was evaluated and contrast, recovery coefficients, contrast-to-noise ratio, and noise were quantified using a custom-built NEMA NU 4–2008 image-quality phantom. Results: A high correlation was found between the experimental data corresponding to intrinsic detector response and the fitted values obtained by means of an asymmetric Gaussian distribution. For all PSF models, resolution improved as the distance from the point source to the center of the field of view increased and when the acquisition radius diminished. An improvement of resolution was observed after a minimum of five iterations when the PSF modeling included more corrections. Contrast, recovery coefficients, and contrast-to-noise ratio were better for the same level of noise in the image when more accurate models were included. Ring-type artifacts were observed when the number of iterations exceeded 12. Conclusions: Accurate modeling of the PSF improves resolution, contrast, and recovery

  9. Transfer learning improves supervised image segmentation across imaging protocols.

    Science.gov (United States)

    van Opbroek, Annegreet; Ikram, M Arfan; Vernooij, Meike W; de Bruijne, Marleen

    2015-05-01

    The variation between images obtained with different scanners or different imaging protocols presents a major challenge in automatic segmentation of biomedical images. This variation especially hampers the application of otherwise successful supervised-learning techniques which, in order to perform well, often require a large amount of labeled training data that is exactly representative of the target data. We therefore propose to use transfer learning for image segmentation. Transfer-learning techniques can cope with differences in distributions between training and target data, and therefore may improve performance over supervised learning for segmentation across scanners and scan protocols. We present four transfer classifiers that can train a classification scheme with only a small amount of representative training data, in addition to a larger amount of other training data with slightly different characteristics. The performance of the four transfer classifiers was compared to that of standard supervised classification on two magnetic resonance imaging brain-segmentation tasks with multi-site data: white matter, gray matter, and cerebrospinal fluid segmentation; and white-matter-/MS-lesion segmentation. The experiments showed that when there is only a small amount of representative training data available, transfer learning can greatly outperform common supervised-learning approaches, minimizing classification errors by up to 60%.

  10. Separation method of heavy-ion particle image from gamma-ray mixed images using an imaging plate

    CERN Document Server

    Yamadera, A; Ohuchi, H; Nakamura, T; Fukumura, A

    1999-01-01

    We have developed a separation method of alpha-ray and gamma-ray images using the imaging plate (IP). The IP from which the first image was read out by an image reader was annealed at 50 deg. C for 2 h in a drying oven and the second image was read out by the image reader. It was found out that an annealing ratio, k, which is defined as a ratio of the photo-stimulated luminescence (PSL) density at the first measurement to that at the second measurement, was different for alpha rays and gamma rays. By subtracting the second image multiplied by a factor of k from the first image, the alpha-ray image was separated from the alpha and gamma-ray mixed images. This method was applied to identify the images of helium, carbon and neon particles of high energies using the heavy-ion medical accelerator, HIMAC. (author)

  11. APPLICATION OF SENSOR FUSION TO IMPROVE UAV IMAGE CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    S. Jabari

    2017-08-01

    Full Text Available Image classification is one of the most important tasks of remote sensing projects including the ones that are based on using UAV images. Improving the quality of UAV images directly affects the classification results and can save a huge amount of time and effort in this area. In this study, we show that sensor fusion can improve image quality which results in increasing the accuracy of image classification. Here, we tested two sensor fusion configurations by using a Panchromatic (Pan camera along with either a colour camera or a four-band multi-spectral (MS camera. We use the Pan camera to benefit from its higher sensitivity and the colour or MS camera to benefit from its spectral properties. The resulting images are then compared to the ones acquired by a high resolution single Bayer-pattern colour camera (here referred to as HRC. We assessed the quality of the output images by performing image classification tests. The outputs prove that the proposed sensor fusion configurations can achieve higher accuracies compared to the images of the single Bayer-pattern colour camera. Therefore, incorporating a Pan camera on-board in the UAV missions and performing image fusion can help achieving higher quality images and accordingly higher accuracy classification results.

  12. Application of Sensor Fusion to Improve Uav Image Classification

    Science.gov (United States)

    Jabari, S.; Fathollahi, F.; Zhang, Y.

    2017-08-01

    Image classification is one of the most important tasks of remote sensing projects including the ones that are based on using UAV images. Improving the quality of UAV images directly affects the classification results and can save a huge amount of time and effort in this area. In this study, we show that sensor fusion can improve image quality which results in increasing the accuracy of image classification. Here, we tested two sensor fusion configurations by using a Panchromatic (Pan) camera along with either a colour camera or a four-band multi-spectral (MS) camera. We use the Pan camera to benefit from its higher sensitivity and the colour or MS camera to benefit from its spectral properties. The resulting images are then compared to the ones acquired by a high resolution single Bayer-pattern colour camera (here referred to as HRC). We assessed the quality of the output images by performing image classification tests. The outputs prove that the proposed sensor fusion configurations can achieve higher accuracies compared to the images of the single Bayer-pattern colour camera. Therefore, incorporating a Pan camera on-board in the UAV missions and performing image fusion can help achieving higher quality images and accordingly higher accuracy classification results.

  13. Image change detection systems, methods, and articles of manufacture

    Science.gov (United States)

    Jones, James L.; Lassahn, Gordon D.; Lancaster, Gregory D.

    2010-01-05

    Aspects of the invention relate to image change detection systems, methods, and articles of manufacture. According to one aspect, a method of identifying differences between a plurality of images is described. The method includes loading a source image and a target image into memory of a computer, constructing source and target edge images from the source and target images to enable processing of multiband images, displaying the source and target images on a display device of the computer, aligning the source and target edge images, switching displaying of the source image and the target image on the display device, to enable identification of differences between the source image and the target image.

  14. Imaging reconstruction based on improved wavelet denoising combined with parallel-beam filtered back-projection algorithm

    Science.gov (United States)

    Ren, Zhong; Liu, Guodong; Huang, Zhen

    2012-11-01

    The image reconstruction is a key step in medical imaging (MI) and its algorithm's performance determinates the quality and resolution of reconstructed image. Although some algorithms have been used, filter back-projection (FBP) algorithm is still the classical and commonly-used algorithm in clinical MI. In FBP algorithm, filtering of original projection data is a key step in order to overcome artifact of the reconstructed image. Since simple using of classical filters, such as Shepp-Logan (SL), Ram-Lak (RL) filter have some drawbacks and limitations in practice, especially for the projection data polluted by non-stationary random noises. So, an improved wavelet denoising combined with parallel-beam FBP algorithm is used to enhance the quality of reconstructed image in this paper. In the experiments, the reconstructed effects were compared between the improved wavelet denoising and others (directly FBP, mean filter combined FBP and median filter combined FBP method). To determine the optimum reconstruction effect, different algorithms, and different wavelet bases combined with three filters were respectively test. Experimental results show the reconstruction effect of improved FBP algorithm is better than that of others. Comparing the results of different algorithms based on two evaluation standards i.e. mean-square error (MSE), peak-to-peak signal-noise ratio (PSNR), it was found that the reconstructed effects of the improved FBP based on db2 and Hanning filter at decomposition scale 2 was best, its MSE value was less and the PSNR value was higher than others. Therefore, this improved FBP algorithm has potential value in the medical imaging.

  15. Universal Image Steganalytic Method

    Directory of Open Access Journals (Sweden)

    V. Banoci

    2014-12-01

    Full Text Available In the paper we introduce a new universal steganalytic method in JPEG file format that is detecting well-known and also newly developed steganographic methods. The steganalytic model is trained by MHF-DZ steganographic algorithm previously designed by the same authors. The calibration technique with the Feature Based Steganalysis (FBS was employed in order to identify statistical changes caused by embedding a secret data into original image. The steganalyzer concept utilizes Support Vector Machine (SVM classification for training a model that is later used by the same steganalyzer in order to identify between a clean (cover and steganographic image. The aim of the paper was to analyze the variety in accuracy of detection results (ACR while detecting testing steganographic algorithms as F5, Outguess, Model Based Steganography without deblocking, JP Hide and Seek which represent the generally used steganographic tools. The comparison of four feature vectors with different lengths FBS (22, FBS (66 FBS(274 and FBS(285 shows promising results of proposed universal steganalytic method comparing to binary methods.

  16. A Method of Spatial Mapping and Reclassification for High-Spatial-Resolution Remote Sensing Image Classification

    Directory of Open Access Journals (Sweden)

    Guizhou Wang

    2013-01-01

    Full Text Available This paper presents a new classification method for high-spatial-resolution remote sensing images based on a strategic mechanism of spatial mapping and reclassification. The proposed method includes four steps. First, the multispectral image is classified by a traditional pixel-based classification method (support vector machine. Second, the panchromatic image is subdivided by watershed segmentation. Third, the pixel-based multispectral image classification result is mapped to the panchromatic segmentation result based on a spatial mapping mechanism and the area dominant principle. During the mapping process, an area proportion threshold is set, and the regional property is defined as unclassified if the maximum area proportion does not surpass the threshold. Finally, unclassified regions are reclassified based on spectral information using the minimum distance to mean algorithm. Experimental results show that the classification method for high-spatial-resolution remote sensing images based on the spatial mapping mechanism and reclassification strategy can make use of both panchromatic and multispectral information, integrate the pixel- and object-based classification methods, and improve classification accuracy.

  17. Handbook of mathematical methods in imaging

    CERN Document Server

    2015-01-01

    The Handbook of Mathematical Methods in Imaging provides a comprehensive treatment of the mathematical techniques used in imaging science. The material is grouped into two central themes, namely, Inverse Problems (Algorithmic Reconstruction) and Signal and Image Processing. Each section within the themes covers applications (modeling), mathematics, numerical methods (using a case example) and open questions. Written by experts in the area, the presentation is mathematically rigorous. This expanded and revised second edition contains updates to existing chapters and 16 additional entries on important mathematical methods such as graph cuts, morphology, discrete geometry, PDEs, conformal methods, to name a few. The entries are cross-referenced for easy navigation through connected topics. Available in both print and electronic forms, the handbook is enhanced by more than 200 illustrations and an extended bibliography. It will benefit students, scientists and researchers in applied mathematics. Engineers and com...

  18. Improvement of the image quality of a high-temperature vision system

    International Nuclear Information System (INIS)

    Fabijańska, Anna; Sankowski, Dominik

    2009-01-01

    In this paper, the issues of controlling and improving the image quality of a high-temperature vision system are considered. The image quality improvement is needed to measure the surface properties of metals and alloys. Two levels of image quality control and improvement are defined in the system. The first level in hardware aims at adjusting the system configuration to obtain the highest contrast and weakest aura images. When optimal configuration is obtained, the second level in software is applied. In this stage, image enhancement algorithms are applied which have been developed with consideration of distortions arising from the vision system components and specificity of images acquired during the measurement process. The developed algorithms have been applied in the vision system to images. The influence on the accuracy of wetting angles and surface tension determination are considered

  19. Improvement in cognitive and psychosocial functioning and self image among adolescent inpatient suicide attempters

    Directory of Open Access Journals (Sweden)

    Laukkanen Eila

    2006-12-01

    Full Text Available Abstract Background Psychiatric treatment of suicidal youths is often difficult and non-compliance in treatment is a significant problem. This prospective study compared characteristics and changes in cognitive functioning, self image and psychosocial functioning among 13 to 18 year-old adolescent psychiatric inpatients with suicide attempts (n = 16 and with no suicidality (n = 39 Methods The two-group pre-post test prospective study design included assessments by a psychiatrist, a psychologist and medical staff members as well as self-rated measures. DSM-III-R diagnoses were assigned using the SCID and thereafter transformed to DSM-IV diagnoses. Staff members assessed psychosocial functioning using the Global Assessment Scale (GAS. Cognitive performance was assessed using the Wechsler Adult Intelligence Scale, while the Offer Self-Image Questionnaire (OSIQ was used to assess the subjects' self-image. ANCOVA with repeated measures was used to test changes from entry to discharge among the suicide attempters and non suicidal patients. Logistic regression modeling was used to assess variables associated with an improvement of 10 points or more in the GAS score. Results Among suicide attempter patients, psychosocial functioning, cognitive performance and both the psychological self and body-image improved during treatment and their treatment compliance and outcome were as good as that of the non-suicidal patients. Suicidal ideation and hopelessness declined, and psychosocial functioning improved. Changes in verbal cognitive performance were more pronounced among the suicide attempters. Having an improved body-image associated with a higher probability of improvement in psychosocial functioning while higher GAS score at entry was associated with lower probability of functional improvement in both patient groups. Conclusion These findings illustrate that a multimodal treatment program seems to improve psychosocial functioning and self-image among

  20. Improving Eastern Bluebird nest box performance using computer analysis of satellite images

    Directory of Open Access Journals (Sweden)

    Sarah Svatora

    2012-06-01

    Full Text Available Bird conservationists have been introducing man-made boxes in an effort to increase the bluebird population. In this study we use computer analysis of satellite images to show that the performance of the boxes used by Eastern Bluebirds (Sialia sialis in Michigan can be improved by about 48%. The analysis is based on a strongcorrelation found between the edge directionality measured in the satellite image of the area around the box, and the preferences of the birds when selecting their nesting site. The method is based on satellite images taken from Google Earth, and can be used by conservationists to select a box placement strategy that will optimize the efficacy of the boxes deployed in a given area.

  1. Improving signal-to-noise in the direct imaging of exoplanets and circumstellar disks with MLOCI

    Science.gov (United States)

    Wahhaj, Zahed; Cieza, Lucas A.; Mawet, Dimitri; Yang, Bin; Canovas, Hector; de Boer, Jozua; Casassus, Simon; Ménard, François; Schreiber, Matthias R.; Liu, Michael C.; Biller, Beth A.; Nielsen, Eric L.; Hayward, Thomas L.

    2015-09-01

    We present a new algorithm designed to improve the signal-to-noise ratio (S/N) of point and extended source detections around bright stars in direct imaging data.One of our innovations is that we insert simulated point sources into the science images, which we then try to recover with maximum S/N. This improves the S/N of real point sources elsewhere in the field. The algorithm, based on the locally optimized combination of images (LOCI) method, is called Matched LOCI or MLOCI. We show with Gemini Planet Imager (GPI) data on HD 135344 B and Near-Infrared Coronagraphic Imager (NICI) data on several stars that the new algorithm can improve the S/N of point source detections by 30-400% over past methods. We also find no increase in false detections rates. No prior knowledge of candidate companion locations is required to use MLOCI. On the other hand, while non-blind applications may yield linear combinations of science images that seem to increase the S/N of true sources by a factor >2, they can also yield false detections at high rates. This is a potential pitfall when trying to confirm marginal detections or to redetect point sources found in previous epochs. These findings are relevant to any method where the coefficients of the linear combination are considered tunable, e.g., LOCI and principal component analysis (PCA). Thus we recommend that false detection rates be analyzed when using these techniques. Based on observations obtained at the Gemini Observatory, which is operated by the Association of Universities for Research in Astronomy, Inc., under a cooperative agreement with the NSF on behalf of the Gemini partnership: the National Science Foundation (USA), the Science and Technology Facilities Council (UK), the National Research Council (Canada), CONICYT (Chile), the Australian Research Council (Australia), Ministério da Ciência e Tecnologia (Brazil) and Ministerio de Ciencia, Tecnología e Innovación Productiva (Argentina).

  2. An Improved Random Walker with Bayes Model for Volumetric Medical Image Segmentation

    Directory of Open Access Journals (Sweden)

    Chunhua Dong

    2017-01-01

    Full Text Available Random walk (RW method has been widely used to segment the organ in the volumetric medical image. However, it leads to a very large-scale graph due to a number of nodes equal to a voxel number and inaccurate segmentation because of the unavailability of appropriate initial seed point setting. In addition, the classical RW algorithm was designed for a user to mark a few pixels with an arbitrary number of labels, regardless of the intensity and shape information of the organ. Hence, we propose a prior knowledge-based Bayes random walk framework to segment the volumetric medical image in a slice-by-slice manner. Our strategy is to employ the previous segmented slice to obtain the shape and intensity knowledge of the target organ for the adjacent slice. According to the prior knowledge, the object/background seed points can be dynamically updated for the adjacent slice by combining the narrow band threshold (NBT method and the organ model with a Gaussian process. Finally, a high-quality image segmentation result can be automatically achieved using Bayes RW algorithm. Comparing our method with conventional RW and state-of-the-art interactive segmentation methods, our results show an improvement in the accuracy for liver segmentation (p<0.001.

  3. INTEGRATED FUSION METHOD FOR MULTIPLE TEMPORAL-SPATIAL-SPECTRAL IMAGES

    Directory of Open Access Journals (Sweden)

    H. Shen

    2012-08-01

    Full Text Available Data fusion techniques have been widely researched and applied in remote sensing field. In this paper, an integrated fusion method for remotely sensed images is presented. Differently from the existed methods, the proposed method has the performance to integrate the complementary information in multiple temporal-spatial-spectral images. In order to represent and process the images in one unified framework, two general image observation models are firstly presented, and then the maximum a posteriori (MAP framework is used to set up the fusion model. The gradient descent method is employed to solve the fused image. The efficacy of the proposed method is validated using simulated images.

  4. DCS-SVM: a novel semi-automated method for human brain MR image segmentation.

    Science.gov (United States)

    Ahmadvand, Ali; Daliri, Mohammad Reza; Hajiali, Mohammadtaghi

    2017-11-27

    In this paper, a novel method is proposed which appropriately segments magnetic resonance (MR) brain images into three main tissues. This paper proposes an extension of our previous work in which we suggested a combination of multiple classifiers (CMC)-based methods named dynamic classifier selection-dynamic local training local Tanimoto index (DCS-DLTLTI) for MR brain image segmentation into three main cerebral tissues. This idea is used here and a novel method is developed that tries to use more complex and accurate classifiers like support vector machine (SVM) in the ensemble. This work is challenging because the CMC-based methods are time consuming, especially on huge datasets like three-dimensional (3D) brain MR images. Moreover, SVM is a powerful method that is used for modeling datasets with complex feature space, but it also has huge computational cost for big datasets, especially those with strong interclass variability problems and with more than two classes such as 3D brain images; therefore, we cannot use SVM in DCS-DLTLTI. Therefore, we propose a novel approach named "DCS-SVM" to use SVM in DCS-DLTLTI to improve the accuracy of segmentation results. The proposed method is applied on well-known datasets of the Internet Brain Segmentation Repository (IBSR) and promising results are obtained.

  5. Keyframes Global Map Establishing Method for Robot Localization through Content-Based Image Matching

    Directory of Open Access Journals (Sweden)

    Tianyang Cao

    2017-01-01

    Full Text Available Self-localization and mapping are important for indoor mobile robot. We report a robust algorithm for map building and subsequent localization especially suited for indoor floor-cleaning robots. Common methods, for example, SLAM, can easily be kidnapped by colliding or disturbed by similar objects. Therefore, keyframes global map establishing method for robot localization in multiple rooms and corridors is needed. Content-based image matching is the core of this method. It is designed for the situation, by establishing keyframes containing both floor and distorted wall images. Image distortion, caused by robot view angle and movement, is analyzed and deduced. And an image matching solution is presented, consisting of extraction of overlap regions of keyframes extraction and overlap region rebuild through subblocks matching. For improving accuracy, ceiling points detecting and mismatching subblocks checking methods are incorporated. This matching method can process environment video effectively. In experiments, less than 5% frames are extracted as keyframes to build global map, which have large space distance and overlap each other. Through this method, robot can localize itself by matching its real-time vision frames with our keyframes map. Even with many similar objects/background in the environment or kidnapping robot, robot localization is achieved with position RMSE <0.5 m.

  6. WE-G-17A-01: Improving Tracking Image Spatial Resolution for Onboard MR Image Guided Radiation Therapy Using the WHISKEE Technique

    Energy Technology Data Exchange (ETDEWEB)

    Hu, Y; Mutic, S; Du, D; Green, O [Washington University School of Medicine, Saint Louis, MO (United States); Zeng, Q; Nana, R; Patrick, J; Shvartsman, S; Dempsey, J [ViewRay Incorporated, Oakwood Village, OH (United States)

    2014-06-15

    Purpose: To evaluate the feasibility of using the weighted hybrid iterative spiral k-space encoded estimation (WHISKEE) technique to improve spatial resolution of tracking images for onboard MR image guided radiation therapy (MR-IGRT). Methods: MR tracking images of abdomen and pelvis had been acquired from healthy volunteers using the ViewRay onboard MRIGRT system (ViewRay Inc. Oakwood Village, OH) at a spatial resolution of 2.0mm*2.0mm*5.0mm. The tracking MR images were acquired using the TrueFISP sequence. The temporal resolution had to be traded off to 2 frames per second (FPS) to achieve the 2.0mm in-plane spatial resolution. All MR images were imported into the MATLAB software. K-space data were synthesized through the Fourier Transform of the MR images. A mask was created to selected k-space points that corresponded to the under-sampled spiral k-space trajectory with an acceleration (or undersampling) factor of 3. The mask was applied to the fully sampled k-space data to synthesize the undersampled k-space data. The WHISKEE method was applied to the synthesized undersampled k-space data to reconstructed tracking MR images at 6 FPS. As a comparison, the undersampled k-space data were also reconstructed using the zero-padding technique. The reconstructed images were compared to the original image. The relatively reconstruction error was evaluated using the percentage of the norm of the differential image over the norm of the original image. Results: Compared to the zero-padding technique, the WHISKEE method was able to reconstruct MR images with better image quality. It significantly reduced the relative reconstruction error from 39.5% to 3.1% for the pelvis image and from 41.5% to 4.6% for the abdomen image at an acceleration factor of 3. Conclusion: We demonstrated that it was possible to use the WHISKEE method to expedite MR image acquisition for onboard MR-IGRT systems to achieve good spatial and temporal resolutions simultaneously. Y. Hu and O. green

  7. WE-G-17A-01: Improving Tracking Image Spatial Resolution for Onboard MR Image Guided Radiation Therapy Using the WHISKEE Technique

    International Nuclear Information System (INIS)

    Hu, Y; Mutic, S; Du, D; Green, O; Zeng, Q; Nana, R; Patrick, J; Shvartsman, S; Dempsey, J

    2014-01-01

    Purpose: To evaluate the feasibility of using the weighted hybrid iterative spiral k-space encoded estimation (WHISKEE) technique to improve spatial resolution of tracking images for onboard MR image guided radiation therapy (MR-IGRT). Methods: MR tracking images of abdomen and pelvis had been acquired from healthy volunteers using the ViewRay onboard MRIGRT system (ViewRay Inc. Oakwood Village, OH) at a spatial resolution of 2.0mm*2.0mm*5.0mm. The tracking MR images were acquired using the TrueFISP sequence. The temporal resolution had to be traded off to 2 frames per second (FPS) to achieve the 2.0mm in-plane spatial resolution. All MR images were imported into the MATLAB software. K-space data were synthesized through the Fourier Transform of the MR images. A mask was created to selected k-space points that corresponded to the under-sampled spiral k-space trajectory with an acceleration (or undersampling) factor of 3. The mask was applied to the fully sampled k-space data to synthesize the undersampled k-space data. The WHISKEE method was applied to the synthesized undersampled k-space data to reconstructed tracking MR images at 6 FPS. As a comparison, the undersampled k-space data were also reconstructed using the zero-padding technique. The reconstructed images were compared to the original image. The relatively reconstruction error was evaluated using the percentage of the norm of the differential image over the norm of the original image. Results: Compared to the zero-padding technique, the WHISKEE method was able to reconstruct MR images with better image quality. It significantly reduced the relative reconstruction error from 39.5% to 3.1% for the pelvis image and from 41.5% to 4.6% for the abdomen image at an acceleration factor of 3. Conclusion: We demonstrated that it was possible to use the WHISKEE method to expedite MR image acquisition for onboard MR-IGRT systems to achieve good spatial and temporal resolutions simultaneously. Y. Hu and O. green

  8. Enhanced iris recognition method based on multi-unit iris images

    Science.gov (United States)

    Shin, Kwang Yong; Kim, Yeong Gon; Park, Kang Ryoung

    2013-04-01

    For the purpose of biometric person identification, iris recognition uses the unique characteristics of the patterns of the iris; that is, the eye region between the pupil and the sclera. When obtaining an iris image, the iris's image is frequently rotated because of the user's head roll toward the left or right shoulder. As the rotation of the iris image leads to circular shifting of the iris features, the accuracy of iris recognition is degraded. To solve this problem, conventional iris recognition methods use shifting of the iris feature codes to perform the matching. However, this increases the computational complexity and level of false acceptance error. To solve these problems, we propose a novel iris recognition method based on multi-unit iris images. Our method is novel in the following five ways compared with previous methods. First, to detect both eyes, we use Adaboost and a rapid eye detector (RED) based on the iris shape feature and integral imaging. Both eyes are detected using RED in the approximate candidate region that consists of the binocular region, which is determined by the Adaboost detector. Second, we classify the detected eyes into the left and right eyes, because the iris patterns in the left and right eyes in the same person are different, and they are therefore considered as different classes. We can improve the accuracy of iris recognition using this pre-classification of the left and right eyes. Third, by measuring the angle of head roll using the two center positions of the left and right pupils, detected by two circular edge detectors, we obtain the information of the iris rotation angle. Fourth, in order to reduce the error and processing time of iris recognition, adaptive bit-shifting based on the measured iris rotation angle is used in feature matching. Fifth, the recognition accuracy is enhanced by the score fusion of the left and right irises. Experimental results on the iris open database of low-resolution images showed that the

  9. AN IMPROVED FUZZY CLUSTERING ALGORITHM FOR MICROARRAY IMAGE SPOTS SEGMENTATION

    Directory of Open Access Journals (Sweden)

    V.G. Biju

    2015-11-01

    Full Text Available An automatic cDNA microarray image processing using an improved fuzzy clustering algorithm is presented in this paper. The spot segmentation algorithm proposed uses the gridding technique developed by the authors earlier, for finding the co-ordinates of each spot in an image. Automatic cropping of spots from microarray image is done using these co-ordinates. The present paper proposes an improved fuzzy clustering algorithm Possibility fuzzy local information c means (PFLICM to segment the spot foreground (FG from background (BG. The PFLICM improves fuzzy local information c means (FLICM algorithm by incorporating typicality of a pixel along with gray level information and local spatial information. The performance of the algorithm is validated using a set of simulated cDNA microarray images added with different levels of AWGN noise. The strength of the algorithm is tested by computing the parameters such as the Segmentation matching factor (SMF, Probability of error (pe, Discrepancy distance (D and Normal mean square error (NMSE. SMF value obtained for PFLICM algorithm shows an improvement of 0.9 % and 0.7 % for high noise and low noise microarray images respectively compared to FLICM algorithm. The PFLICM algorithm is also applied on real microarray images and gene expression values are computed.

  10. Improvement of Sidestream Dark Field Imaging with an Image Acquisition Stabilizer

    NARCIS (Netherlands)

    Balestra, Gianmarco M.; Bezemer, Rick; Boerma, E. Christiaan; Yong, Ze-Yie; Sjauw, Krishan D.; Engstrom, Annemarie E.; Koopmans, Matty; Ince, Can

    2010-01-01

    ABSTRACT: BACKGROUND: In the present study we developed, evaluated in volunteers, and clinically validated an image acquisition stabilizer (IAS) for Sidestream Dark Field (SDF) imaging. METHODS: The IAS is a stainless steel sterilizable ring which fits around the SDF probe tip. The IAS creates

  11. Improvement of Sidestream Dark Field Imaging with an Image Acquisition Stabilizer

    NARCIS (Netherlands)

    G. Balestra (Gianmarco); R. Bezemer (Rick); E.C. Boerma (Christiaan); Z-Y. Yong (Ze-Yie); K.D. Sjauw (Krishan); A.E. Engstrom (Annemarie); M. Koopmans (Matty); C. Ince (Can)

    2010-01-01

    textabstractBackground: In the present study we developed, evaluated in volunteers, and clinically validated an image acquisition stabilizer (IAS) for Sidestream Dark Field (SDF) imaging.Methods: The IAS is a stainless steel sterilizable ring which fits around the SDF probe tip. The IAS creates

  12. Improve the efficiency of PEMFC using neutron imaging

    International Nuclear Information System (INIS)

    Kim, Tae Joo; Shim, Chulmuu

    2010-01-01

    The water management is one of the most critical issues for PEMFC commercialization. In order to make a proper scheme for water management, the information of water distribution and behavior is very important. But the visualization is difficult due to metallic coverage. Recently, neutron imaging has joined the canon of diagnostic methods for fuel cell research and is applied worldwide with qualitative and quantitative results. In this investigation, we prepared 3-parallel serpentine single PEMFC. The active area is 250 mm 2 and channel size is 1 Χ 1 mm, respectively. Distribution and transport of water in an operating PEMFC were observed as functions of flow directions and differential pressures between anode and cathodes. This investigation was performed at BST-2, Nest. The collimation ratio is 600 and neutron fluence of BST-2 is 7.2 Χ 10 6 n/s, respectively. Neutron image was captured by A-Si detector with 1 sec expsosure time. The PEMFC has different performances for each differential pressure and flow directions. When the neutron images are compared with operating conditions, the distribution and behavior of water are different. Total water fraction is increased and then decreases as the current density increases. This situation is similar trend for the flow directions. It is shown that neutron imaging technique is powerful tool to visualize the PEMFC and the water distribution and behavior of an operating PEMFC helps improve the efficiency of PEMFC

  13. An Improved Isotropic Periodic Sum Method That Uses Linear Combinations of Basis Potentials

    KAUST Repository

    Takahashi, Kazuaki Z.; Narumi, Tetsu; Suh, Donguk; Yasuoka, Kenji

    2012-01-01

    Isotropic periodic sum (IPS) is a technique that calculates long-range interactions differently than conventional lattice sum methods. The difference between IPS and lattice sum methods lies in the shape and distribution of remote images for long-range interaction calculations. The images used in lattice sum calculations are identical to those generated from periodic boundary conditions and are discretely positioned at lattice points in space. The images for IPS calculations are "imaginary", which means they do not explicitly exist in a simulation system and are distributed isotropically and periodically around each particle. Two different versions of the original IPS method exist. The IPSn method is applied to calculations for point charges, whereas the IPSp method calculates polar molecules. However, both IPSn and IPSp have their advantages and disadvantages in simulating bulk water or water-vapor interfacial systems. In bulk water systems, the cutoff radius effect of IPSn strongly affects the configuration, whereas IPSp does not provide adequate estimations of water-vapor interfacial systems unless very long cutoff radii are used. To extend the applicability of the IPS technique, an improved IPS method, which has better accuracy in both homogeneous and heterogeneous systems has been developed and named the linear-combination-based isotropic periodic sum (LIPS) method. This improved IPS method uses linear combinations of basis potentials. We performed molecular dynamics (MD) simulations of bulk water and water-vapor interfacial systems to evaluate the accuracy of the LIPS method. For bulk water systems, the LIPS method has better accuracy than IPSn in estimating thermodynamic and configurational properties without the countercharge assumption, which is used for IPSp. For water-vapor interfacial systems, LIPS has better accuracy than IPSp and properly estimates thermodynamic and configurational properties. In conclusion, the LIPS method can successfully estimate

  14. An Improved Isotropic Periodic Sum Method That Uses Linear Combinations of Basis Potentials

    KAUST Repository

    Takahashi, Kazuaki Z.

    2012-11-13

    Isotropic periodic sum (IPS) is a technique that calculates long-range interactions differently than conventional lattice sum methods. The difference between IPS and lattice sum methods lies in the shape and distribution of remote images for long-range interaction calculations. The images used in lattice sum calculations are identical to those generated from periodic boundary conditions and are discretely positioned at lattice points in space. The images for IPS calculations are "imaginary", which means they do not explicitly exist in a simulation system and are distributed isotropically and periodically around each particle. Two different versions of the original IPS method exist. The IPSn method is applied to calculations for point charges, whereas the IPSp method calculates polar molecules. However, both IPSn and IPSp have their advantages and disadvantages in simulating bulk water or water-vapor interfacial systems. In bulk water systems, the cutoff radius effect of IPSn strongly affects the configuration, whereas IPSp does not provide adequate estimations of water-vapor interfacial systems unless very long cutoff radii are used. To extend the applicability of the IPS technique, an improved IPS method, which has better accuracy in both homogeneous and heterogeneous systems has been developed and named the linear-combination-based isotropic periodic sum (LIPS) method. This improved IPS method uses linear combinations of basis potentials. We performed molecular dynamics (MD) simulations of bulk water and water-vapor interfacial systems to evaluate the accuracy of the LIPS method. For bulk water systems, the LIPS method has better accuracy than IPSn in estimating thermodynamic and configurational properties without the countercharge assumption, which is used for IPSp. For water-vapor interfacial systems, LIPS has better accuracy than IPSp and properly estimates thermodynamic and configurational properties. In conclusion, the LIPS method can successfully estimate

  15. Deep learning methods for CT image-domain metal artifact reduction

    Science.gov (United States)

    Gjesteby, Lars; Yang, Qingsong; Xi, Yan; Shan, Hongming; Claus, Bernhard; Jin, Yannan; De Man, Bruno; Wang, Ge

    2017-09-01

    Artifacts resulting from metal objects have been a persistent problem in CT images over the last four decades. A common approach to overcome their effects is to replace corrupt projection data with values synthesized from an interpolation scheme or by reprojection of a prior image. State-of-the-art correction methods, such as the interpolation- and normalization-based algorithm NMAR, often do not produce clinically satisfactory results. Residual image artifacts remain in challenging cases and even new artifacts can be introduced by the interpolation scheme. Metal artifacts continue to be a major impediment, particularly in radiation and proton therapy planning as well as orthopedic imaging. A new solution to the long-standing metal artifact reduction (MAR) problem is deep learning, which has been successfully applied to medical image processing and analysis tasks. In this study, we combine a convolutional neural network (CNN) with the state-of-the-art NMAR algorithm to reduce metal streaks in critical image regions. Training data was synthesized from CT simulation scans of a phantom derived from real patient images. The CNN is able to map metal-corrupted images to artifact-free monoenergetic images to achieve additional correction on top of NMAR for improved image quality. Our results indicate that deep learning is a novel tool to address CT reconstruction challenges, and may enable more accurate tumor volume estimation for radiation therapy planning.

  16. A collimator optimization method for quantitative imaging: application to Y-90 bremsstrahlung SPECT.

    Science.gov (United States)

    Rong, Xing; Frey, Eric C

    2013-08-01

    general, the authors simulated multiple tumors of various sizes in the liver. The authors realistically simulated human anatomy using a digital phantom and the image formation process using a previously validated and computationally efficient method for modeling the image-degrading effects including object scatter, attenuation, and the full collimator-detector response (CDR). The scatter kernels and CDR function tables used in the modeling method were generated using a previously validated Monte Carlo simulation code. The hole length, hole diameter, and septal thickness of the obtained optimal collimator were 84, 3.5, and 1.4 mm, respectively. Compared to a commercial high-energy general-purpose collimator, the optimal collimator improved the resolution and FOM by 27% and 18%, respectively. The proposed collimator optimization method may be useful for improving quantitative SPECT imaging for radionuclides with complex energy spectra. The obtained optimal collimator provided a substantial improvement in quantitative performance for the microsphere radioembolization task considered.

  17. Technical approach to improvement of SPECT images

    International Nuclear Information System (INIS)

    Fukukita, Hiroyoshi

    1985-01-01

    At present, a large number of SPECT systems are being widely used in Japan, hence, it is reasonable for us to know the physical and imaging characteristics of these SPECT devices, and also to recommend the optimum utility of SPECT systems. For this reason, a survey respect of characteristics of the commercialy available SPECT devices was carried out. In addition to this, various factors which have significant influence over SPECT image quality, such as, data acquisition matrix, reconstruction filter, γ-ray attenuation correction and daily quality control procedure, were also investigated. The materials used for this study are PET/SPECT phantom, Alderson liver phantom filled with Tc-99m solution, and either LFOV-E or ZLC-7500 interfaced to Scintipac 2400 minicomputer with 256 K byte of memory. Following are the results of this study. 1) The suitable data acquisition procedure was 128 x 128 matrix for linear sampling and approximately 64 views for angular sampling. 2) Reconstructed image using pre-processing filter with Wiener and Butterworth filters provided high quality image as compared with the Ramp filter. 3) Weighted backprojection method (WBP) proposed by Tanaka was superior to other methods, such as Sorenson method and Chang method in the object with non-uniform distribution of radionuclide. 4) It was found that uniformity correction of gamma camera and precise adjustment of the center of rotation are most important to maintain the images with a high quality. (author)

  18. Multi-reception strategy with improved SNR for multichannel MR imaging.

    Directory of Open Access Journals (Sweden)

    Bing Wu

    Full Text Available A multi-reception strategy with extended GRAPPA is proposed in this work to improve MR imaging performance at ultra-high field MR systems with limited receiver channels. In this method, coil elements are separated to two or more groups under appropriate grouping criteria. Those groups are enabled in sequence for imaging first, and then parallel acquisition is performed to compensate for the redundant scan time caused by the multiple receptions. To efficiently reconstruct the data acquired from elements of each group, a specific extended GRAPPA was developed. This approach was evaluated by using a 16-element head array on a 7 Tesla whole-body MRI scanner with 8 receive channels. The in-vivo experiments demonstrate that with the same scan time, the 16-element array with twice receptions and acceleration rate of 2 can achieve significant SNR gain in the periphery area of the brain and keep nearly the same SNR in the center area over an eight-element array, which indicates the proposed multi-reception strategy and extended GRAPPA are feasible to improve image quality for MRI systems with limited receive channels. This study also suggests that it is advantageous for a MR system with N receiver channels to utilize a coil array with more than N elements if an appropriate acquisition strategy is applied.

  19. A new and fast image feature selection method for developing an optimal mammographic mass detection scheme.

    Science.gov (United States)

    Tan, Maxine; Pu, Jiantao; Zheng, Bin

    2014-08-01

    Selecting optimal features from a large image feature pool remains a major challenge in developing computer-aided detection (CAD) schemes of medical images. The objective of this study is to investigate a new approach to significantly improve efficacy of image feature selection and classifier optimization in developing a CAD scheme of mammographic masses. An image dataset including 1600 regions of interest (ROIs) in which 800 are positive (depicting malignant masses) and 800 are negative (depicting CAD-generated false positive regions) was used in this study. After segmentation of each suspicious lesion by a multilayer topographic region growth algorithm, 271 features were computed in different feature categories including shape, texture, contrast, isodensity, spiculation, local topological features, as well as the features related to the presence and location of fat and calcifications. Besides computing features from the original images, the authors also computed new texture features from the dilated lesion segments. In order to select optimal features from this initial feature pool and build a highly performing classifier, the authors examined and compared four feature selection methods to optimize an artificial neural network (ANN) based classifier, namely: (1) Phased Searching with NEAT in a Time-Scaled Framework, (2) A sequential floating forward selection (SFFS) method, (3) A genetic algorithm (GA), and (4) A sequential forward selection (SFS) method. Performances of the four approaches were assessed using a tenfold cross validation method. Among these four methods, SFFS has highest efficacy, which takes 3%-5% of computational time as compared to GA approach, and yields the highest performance level with the area under a receiver operating characteristic curve (AUC) = 0.864 ± 0.034. The results also demonstrated that except using GA, including the new texture features computed from the dilated mass segments improved the AUC results of the ANNs optimized

  20. Improved radioanalytical methods

    International Nuclear Information System (INIS)

    Erickson, M.D.; Aldstadt, J.H.; Alvarado, J.S.; Crain, J.S.; Orlandini, K.A.; Smith, L.L.

    1995-01-01

    Methods for the chemical characterization of the environment are being developed under a multitask project for the Analytical Services Division (EM-263) within the US Department of Energy (DOE) Office of Environmental Management. This project focuses on improvement of radioanalytical methods with an emphasis on faster and cheaper routine methods. We have developed improved methods, for separation of environmental levels of technetium-99 and strontium-89/90, radium, and actinides from soil and water; and for separation of actinides from soil and water matrix interferences. Among the novel separation techniques being used are element- and class-specific resins and membranes. (The 3M Corporation is commercializing Empore trademark membranes under a cooperative research and development agreement [CRADA] initiated under this project). We have also developed methods for simultaneous detection of multiple isotopes using inductively coupled plasma-mass spectrometry (ICP-MS). The ICP-MS method requires less rigorous chemical separations than traditional radiochemical analyses because of its mass-selective mode of detection. Actinides and their progeny have been isolated and concentrated from a variety of natural water matrices by using automated batch separation incorporating selective resins prior to ICP-MS analyses. In addition, improvements in detection limits, sample volume, and time of analysis were obtained by using other sample introduction techniques, such as ultrasonic nebulization and electrothermal vaporization. Integration and automation of the separation methods with the ICP-MS methodology by using flow injection analysis is underway, with an objective of automating methods to achieve more reproducible results, reduce labor costs, cut analysis time, and minimize secondary waste generation through miniaturization of the process

  1. Novel Variants of a Histogram Shift-Based Reversible Watermarking Technique for Medical Images to Improve Hiding Capacity

    Directory of Open Access Journals (Sweden)

    Vishakha Kelkar

    2017-01-01

    Full Text Available In telemedicine systems, critical medical data is shared on a public communication channel. This increases the risk of unauthorised access to patient’s information. This underlines the importance of secrecy and authentication for the medical data. This paper presents two innovative variations of classical histogram shift methods to increase the hiding capacity. The first technique divides the image into nonoverlapping blocks and embeds the watermark individually using the histogram method. The second method separates the region of interest and embeds the watermark only in the region of noninterest. This approach preserves the medical information intact. This method finds its use in critical medical cases. The high PSNR (above 45 dB obtained for both techniques indicates imperceptibility of the approaches. Experimental results illustrate superiority of the proposed approaches when compared with other methods based on histogram shifting techniques. These techniques improve embedding capacity by 5–15% depending on the image type, without affecting the quality of the watermarked image. Both techniques also enable lossless reconstruction of the watermark and the host medical image. A higher embedding capacity makes the proposed approaches attractive for medical image watermarking applications without compromising the quality of the image.

  2. Novel Variants of a Histogram Shift-Based Reversible Watermarking Technique for Medical Images to Improve Hiding Capacity

    Science.gov (United States)

    Tuckley, Kushal

    2017-01-01

    In telemedicine systems, critical medical data is shared on a public communication channel. This increases the risk of unauthorised access to patient's information. This underlines the importance of secrecy and authentication for the medical data. This paper presents two innovative variations of classical histogram shift methods to increase the hiding capacity. The first technique divides the image into nonoverlapping blocks and embeds the watermark individually using the histogram method. The second method separates the region of interest and embeds the watermark only in the region of noninterest. This approach preserves the medical information intact. This method finds its use in critical medical cases. The high PSNR (above 45 dB) obtained for both techniques indicates imperceptibility of the approaches. Experimental results illustrate superiority of the proposed approaches when compared with other methods based on histogram shifting techniques. These techniques improve embedding capacity by 5–15% depending on the image type, without affecting the quality of the watermarked image. Both techniques also enable lossless reconstruction of the watermark and the host medical image. A higher embedding capacity makes the proposed approaches attractive for medical image watermarking applications without compromising the quality of the image. PMID:29104744

  3. A comparative study on medical image segmentation methods

    Directory of Open Access Journals (Sweden)

    Praylin Selva Blessy SELVARAJ ASSLEY

    2014-03-01

    Full Text Available Image segmentation plays an important role in medical images. It has been a relevant research area in computer vision and image analysis. Many segmentation algorithms have been proposed for medical images. This paper makes a review on segmentation methods for medical images. In this survey, segmentation methods are divided into five categories: region based, boundary based, model based, hybrid based and atlas based. The five different categories with their principle ideas, advantages and disadvantages in segmenting different medical images are discussed.

  4. Improvement of Sidestream Dark Field Imaging with an Image Acquisition Stabilizer

    OpenAIRE

    Balestra, Gianmarco M; Bezemer, Rick; Boerma, E Christiaan; Yong, Ze-Yie; Sjauw, Krishan D; Engstrom, Annemarie E; Koopmans, Matty; Ince, Can

    2010-01-01

    Abstract Background In the present study we developed, evaluated in volunteers, and clinically validated an image acquisition stabilizer (IAS) for Sidestream Dark Field (SDF) imaging. Methods The IAS is a stainless steel sterilizable ring which fits around the SDF probe tip. The IAS creates adhesion to the imaged tissue by application of negative pressure. The effects of the IAS on the sublingual microcirculatory flow velocities, the force required to induce pressure artifacts (PA), the time ...

  5. Exploiting Microwave Imaging Methods for Real-Time Monitoring of Thermal Ablation

    Directory of Open Access Journals (Sweden)

    Rosa Scapaticci

    2017-01-01

    Full Text Available Microwave thermal ablation is a cancer treatment that exploits local heating caused by a microwave electromagnetic field to induce coagulative necrosis of tumor cells. Recently, such a technique has significantly progressed in the clinical practice. However, its effectiveness would dramatically improve if paired with a noninvasive system for the real-time monitoring of the evolving dimension and shape of the thermally ablated area. In this respect, microwave imaging can be a potential candidate to monitor the overall treatment evolution in a noninvasive way, as it takes direct advantage from the dependence of the electromagnetic properties of biological tissues from temperature. This paper explores such a possibility by presenting a proof of concept validation based on accurate simulated imaging experiments, run with respect to a scenario that mimics an ex vivo experimental setup. In particular, two model-based inversion algorithms are exploited to tackle the imaging task. These methods provide independent results in real-time and their integration improves the quality of the overall tracking of the variations occurring in the target and surrounding regions.

  6. Advanced virtual monoenergetic images: improving the contrast of dual-energy CT pulmonary angiography

    International Nuclear Information System (INIS)

    Meier, A.; Wurnig, M.; Desbiolles, L.; Leschka, S.; Frauenfelder, T.; Alkadhi, H.

    2015-01-01

    Aim: To investigate the value of advanced virtual monoenergetic image reconstruction (mono-plus) from dual-energy computed tomography (CT) for improving the contrast of CT pulmonary angiography (CTPA). Materials and methods: Forty consecutive patients (25 women, mean 62.5 years, range 28–87 years) underwent 192-section dual-source CTPA with dual-energy CT (90/150 SnkVp) after the administration of 60 ml contrast media (300 mg iodine/ml). Conventional virtual monochromatic images at 60 keV and 17 mono-plus image datasets from 40–190 keV (in 10 keV steps) were reconstructed. Subjective image quality (artefacts, subjective noise) was rated. Attenuation was measured in the pulmonary trunk and in the right lower lobe pulmonary artery; noise was measured in the periscapular musculature. The signal-to-noise (SNR) and contrast-to-noise ratios (CNR) were calculated for each patient and dataset. Comparisons between monochromatic images and mono-plus images were performed by repeated measures analysis of variance (ANOVA) with post-hoc Bonferroni correction. Results: Interreader agreement was good to excellent for subjective image quality (ICC: 0.616–0.889). As compared to conventional 60 keV images, artefacts occurred less (p=0.001) and subjective noise was rated lower (p<0.001) in mono-plus 40 keV images. Noise was lower (p<0.001), and the SNR and CNR in the pulmonary trunk and right lower lobe pulmonary artery were higher (both, p<0.001) in mono-plus 40 keV images compared to conventional monoenergetic 60 keV images. Transient interruption of contrast (TIC) was found in 14/40 (35%) of patients, with subjective contrast being similar 8/40 (20%) or higher 32/40 (80%) in mono-plus 40 keV as compared to conventional monoenergetic 60 keV images. Conclusions: Compared to conventional virtual monoenergetic imaging, mono-plus images at 40 keV improve the contrast of dual-energy CTPA. - Highlights: • Advanced monoenergetic image reconstruction from dual-energy CT

  7. Robust methods for automatic image-to-world registration in cone-beam CT interventional guidance

    International Nuclear Information System (INIS)

    Dang, H.; Otake, Y.; Schafer, S.; Stayman, J. W.; Kleinszig, G.; Siewerdsen, J. H.

    2012-01-01

    anatomical sites, including challenging scenarios involving the presence of interventional tools. The reprojection error of marker localization was independent of the distance of the ARM from isocenter, and the overall TRE was dominated by the configuration of individual fiducials and distance from the target as predicted by theory. The median TRE increased with greater ARM-to-isocenter distance (e.g., for the Free-Form method, TRE increasing from 0.78 mm to 2.04 mm at distances of ∼75 mm and 370 mm, respectively). The median TRE within ∼200 mm distance was consistently lower than that of the manual method (TRE = 0.82 mm). Registration performance was independent of anatomical site (head, thorax, and abdomen). The Free-Form method demonstrated a statistically significant improvement (p= 0.0044) in reproducibility compared to manual registration (0.22 mm versus 0.30 mm, respectively). Conclusions: Automatic image-to-world registration methods demonstrate the potential for improved accuracy, reproducibility, and workflow in CBCT-guided procedures. A Free-Form method was shown to exhibit robustness against anatomical site, with comparable or improved TRE compared to manual registration. It was also comparable or superior in performance to a Known-Model method in which the ARM configuration is specified as a predefined tool, thereby allowing configuration of fiducials on the fly or attachment to the patient.

  8. Magnetic imager and method

    Science.gov (United States)

    Powell, James; Reich, Morris; Danby, Gordon

    1997-07-22

    A magnetic imager 10 includes a generator 18 for practicing a method of applying a background magnetic field over a concealed object, with the object being effective to locally perturb the background field. The imager 10 also includes a sensor 20 for measuring perturbations of the background field to detect the object. In one embodiment, the background field is applied quasi-statically. And, the magnitude or rate of change of the perturbations may be measured for determining location, size, and/or condition of the object.

  9. The optimal monochromatic spectral computed tomographic imaging plus adaptive statistical iterative reconstruction algorithm can improve the superior mesenteric vessel image quality

    Energy Technology Data Exchange (ETDEWEB)

    Yin, Xiao-Ping; Zuo, Zi-Wei; Xu, Ying-Jin; Wang, Jia-Ning [CT/MRI room, Affiliated Hospital of Hebei University, Baoding, Hebei, 071000 (China); Liu, Huai-Jun, E-mail: hebeiliu@outlook.com [Department of Medical Imaging, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, 050000 (China); Liang, Guang-Lu [CT/MRI room, Affiliated Hospital of Hebei University, Baoding, Hebei, 071000 (China); Gao, Bu-Lang, E-mail: browngao@163.com [Department of Medical Research, Shijiazhuang First Hospital, Shijiazhuang, Hebei, 050011 (China)

    2017-04-15

    Objective: To investigate the effect of the optimal monochromatic spectral computed tomography (CT) plus adaptive statistical iterative reconstruction on the improvement of the image quality of the superior mesenteric artery and vein. Materials and methods: The gemstone spectral CT angiographic data of 25 patients were reconstructed in the following three groups: 70 KeV, the optimal monochromatic imaging, and the optimal monochromatic plus 40%iterative reconstruction mode. The CT value, image noises (IN), background CT value and noises, contrast-to-noise ratio (CNR), signal-to-noise ratio (SNR) and image scores of the vessels and surrounding tissues were analyzed. Results: In the 70 KeV, the optimal monochromatic and the optimal monochromatic images plus 40% iterative reconstruction group, the mean scores of image quality were 3.86, 4.24 and 4.25 for the superior mesenteric artery and 3.46, 3.78 and 3.81 for the superior mesenteric vein, respectively. The image quality scores for the optimal monochromatic and the optimal monochromatic plus 40% iterative reconstruction groups were significantly greater than for the 70 KeV group (P < 0.05). The vascular CT value, image noise, background noise, CNR and SNR were significantly (P < 0.001) greater in the optimal monochromatic and the optimal monochromatic images plus 40% iterative reconstruction group than in the 70 KeV group. The optimal monochromatic plus 40% iterative reconstruction group had significantly (P < 0.05) lower image and background noise but higher CNR and SNR than the other two groups. Conclusion: The optimal monochromatic imaging combined with 40% iterative reconstruction using low-contrast agent dosage and low injection rate can significantly improve the image quality of the superior mesenteric artery and vein.

  10. A Flexible Method for Multi-Material Decomposition of Dual-Energy CT Images.

    Science.gov (United States)

    Mendonca, Paulo R S; Lamb, Peter; Sahani, Dushyant V

    2014-01-01

    The ability of dual-energy computed-tomographic (CT) systems to determine the concentration of constituent materials in a mixture, known as material decomposition, is the basis for many of dual-energy CT's clinical applications. However, the complex composition of tissues and organs in the human body poses a challenge for many material decomposition methods, which assume the presence of only two, or at most three, materials in the mixture. We developed a flexible, model-based method that extends dual-energy CT's core material decomposition capability to handle more complex situations, in which it is necessary to disambiguate among and quantify the concentration of a larger number of materials. The proposed method, named multi-material decomposition (MMD), was used to develop two image analysis algorithms. The first was virtual unenhancement (VUE), which digitally removes the effect of contrast agents from contrast-enhanced dual-energy CT exams. VUE has the ability to reduce patient dose and improve clinical workflow, and can be used in a number of clinical applications such as CT urography and CT angiography. The second algorithm developed was liver-fat quantification (LFQ), which accurately quantifies the fat concentration in the liver from dual-energy CT exams. LFQ can form the basis of a clinical application targeting the diagnosis and treatment of fatty liver disease. Using image data collected from a cohort consisting of 50 patients and from phantoms, the application of MMD to VUE and LFQ yielded quantitatively accurate results when compared against gold standards. Furthermore, consistent results were obtained across all phases of imaging (contrast-free and contrast-enhanced). This is of particular importance since most clinical protocols for abdominal imaging with CT call for multi-phase imaging. We conclude that MMD can successfully form the basis of a number of dual-energy CT image analysis algorithms, and has the potential to improve the clinical utility

  11. Improvement of Breast Cancer Detection Using Non-subsampled Contourlet Transform and Super-Resolution Technique in Mammographic Images

    Directory of Open Access Journals (Sweden)

    Fatemeh Pak

    2015-05-01

    Full Text Available Introduction Breast cancer is one of the most life-threatening conditions among women. Early detection of this disease is the only way to reduce the associated mortality rate. Mammography is a standard method for the early detection of breast cancer. Today, considering the importance of breast cancer detection, computer-aided detection techniques have been employed to increase the quality of mammographic images and help physicians reduce false positive rate (FPR. Materials and Methods In this study, a method was proposed for improving the quality of mammographic images to help radiologists establish a prompt and accurate diagnosis. The proposed approach included three major parts including pre-processing, feature extraction, and classification. In the pre-processing stage, the region of interest was determined and the image quality was improved by non-subsampled contourlet transform and super-resolution algorithm. In the feature extraction stage, some features of image components were extracted and skewness of each feature was calculated. Finally, a support vector machine was utilized to classify the features and determine the probability of benignity or malignancy of the disease. Results Based on the obtained results using Mammographic Image Analysis Society (MIAS database, the mean accuracy was estimated at 87.26% and maximum accuracy was 96.29%. Also, the mean and minimum FPRs were estimated at 9.55% and 2.87%, respectively.     Conclusion The results obtained using MIAS database indicated the superiority of the proposed method to other techniques. The reduced FPR in the proposed method was a significant finding in the present article.

  12. WE-AB-207A-08: BEST IN PHYSICS (IMAGING): Advanced Scatter Correction and Iterative Reconstruction for Improved Cone-Beam CT Imaging On the TrueBeam Radiotherapy Machine

    Energy Technology Data Exchange (ETDEWEB)

    Wang, A; Paysan, P; Brehm, M; Maslowski, A; Lehmann, M; Messmer, P; Munro, P; Yoon, S; Star-Lack, J; Seghers, D [Varian Medical Systems, Palo Alto, CA (United States)

    2016-06-15

    Purpose: To improve CBCT image quality for image-guided radiotherapy by applying advanced reconstruction algorithms to overcome scatter, noise, and artifact limitations Methods: CBCT is used extensively for patient setup in radiotherapy. However, image quality generally falls short of diagnostic CT, limiting soft-tissue based positioning and potential applications such as adaptive radiotherapy. The conventional TrueBeam CBCT reconstructor uses a basic scatter correction and FDK reconstruction, resulting in residual scatter artifacts, suboptimal image noise characteristics, and other artifacts like cone-beam artifacts. We have developed an advanced scatter correction that uses a finite-element solver (AcurosCTS) to model the behavior of photons as they pass (and scatter) through the object. Furthermore, iterative reconstruction is applied to the scatter-corrected projections, enforcing data consistency with statistical weighting and applying an edge-preserving image regularizer to reduce image noise. The combined algorithms have been implemented on a GPU. CBCT projections from clinically operating TrueBeam systems have been used to compare image quality between the conventional and improved reconstruction methods. Planning CT images of the same patients have also been compared. Results: The advanced scatter correction removes shading and inhomogeneity artifacts, reducing the scatter artifact from 99.5 HU to 13.7 HU in a typical pelvis case. Iterative reconstruction provides further benefit by reducing image noise and eliminating streak artifacts, thereby improving soft-tissue visualization. In a clinical head and pelvis CBCT, the noise was reduced by 43% and 48%, respectively, with no change in spatial resolution (assessed visually). Additional benefits include reduction of cone-beam artifacts and reduction of metal artifacts due to intrinsic downweighting of corrupted rays. Conclusion: The combination of an advanced scatter correction with iterative reconstruction

  13. Least Square NUFFT Methods Applied to 2D and 3D Radially Encoded MR Image Reconstruction

    Science.gov (United States)

    Song, Jiayu; Liu, Qing H.; Gewalt, Sally L.; Cofer, Gary; Johnson, G. Allan

    2009-01-01

    Radially encoded MR imaging (MRI) has gained increasing attention in applications such as hyperpolarized gas imaging, contrast-enhanced MR angiography, and dynamic imaging, due to its motion insensitivity and improved artifact properties. However, since the technique collects k-space samples nonuniformly, multidimensional (especially 3D) radially sampled MRI image reconstruction is challenging. The balance between reconstruction accuracy and speed becomes critical when a large data set is processed. Kaiser-Bessel gridding reconstruction has been widely used for non-Cartesian reconstruction. The objective of this work is to provide an alternative reconstruction option in high dimensions with on-the-fly kernels calculation. The work develops general multi-dimensional least square nonuniform fast Fourier transform (LS-NUFFT) algorithms and incorporates them into a k-space simulation and image reconstruction framework. The method is then applied to reconstruct the radially encoded k-space, although the method addresses general nonuniformity and is applicable to any non-Cartesian patterns. Performance assessments are made by comparing the LS-NUFFT based method with the conventional Kaiser-Bessel gridding method for 2D and 3D radially encoded computer simulated phantoms and physically scanned phantoms. The results show that the LS-NUFFT reconstruction method has better accuracy-speed efficiency than the Kaiser-Bessel gridding method when the kernel weights are calculated on the fly. The accuracy of the LS-NUFFT method depends on the choice of scaling factor, and it is found that for a particular conventional kernel function, using its corresponding deapodization function as scaling factor and utilizing it into the LS-NUFFT framework has the potential to improve accuracy. When a cosine scaling factor is used, in particular, the LS-NUFFT method is faster than Kaiser-Bessel gridding method because of a quasi closed-form solution. The method is successfully applied to 2D and

  14. Well test imaging - a new method for determination of boundaries from well test data

    Energy Technology Data Exchange (ETDEWEB)

    Slevinsky, B.A.

    1997-08-01

    A new method has been developed for analysis of well test data, which allows the direct calculation of the location of arbitrary reservoir boundaries which are detected during a well test. The method is based on elements of ray tracing and information theory, and is centered on the calculation of an instantaneous {open_quote}angle of view{close_quote} of the reservoir boundaries. In the absence of other information, the relative reservoir shape and boundary distances are retrievable in the form of a Diagnostic Image. If other reservoir information, such as 3-D seismic, is available; the full shape and orientation of arbitrary (non-straight line or circular arc) boundaries can be determined in the form of a Reservoir Image. The well test imaging method can be used to greatly enhance the information available from well tests and other geological data, and provides a method to integrate data from multiple disciplines to improve reservoir characterization. This paper covers the derivation of the analytical technique of well test imaging and shows examples of application of the technique to a number of reservoirs.

  15. Development of comprehensive image processing technique for differential diagnosis of liver disease by using multi-modality images. Pixel-based cross-correlation method using a profile

    International Nuclear Information System (INIS)

    Inoue, Akira; Okura, Yasuhiko; Akiyama, Mitoshi; Ishida, Takayuki; Kawashita, Ikuo; Ito, Katsuyoshi; Matsunaga, Naofumi; Sanada, Taizo

    2009-01-01

    Imaging techniques such as high magnetic field imaging and multidetector-row CT have been markedly improved recently. The final image-reading systems easily produce more than a thousand diagnostic images per patient. Therefore, we developed a comprehensive cross-correlation processing technique using multi-modality images, in order to decrease the considerable time and effort involved in the interpretation of a radiogram (multi-formatted display and/or stack display method, etc). In this scheme, the criteria of an attending radiologist for the differential diagnosis of liver cyst, hemangioma of liver, hepatocellular carcinoma, and metastatic liver cancer on magnetic resonance images with various sequences and CT images with and without contrast enhancement employ a cross-correlation coefficient. Using a one-dimensional cross-correlation method, comprehensive image processing could be also adapted for various artifacts (some depending on modality imaging, and some on patients), which may be encountered at the clinical scene. This comprehensive image-processing technique could assist radiologists in the differential diagnosis of liver diseases. (author)

  16. Finite element formulation for a digital image correlation method

    International Nuclear Information System (INIS)

    Sun Yaofeng; Pang, John H. L.; Wong, Chee Khuen; Su Fei

    2005-01-01

    A finite element formulation for a digital image correlation method is presented that will determine directly the complete, two-dimensional displacement field during the image correlation process on digital images. The entire interested image area is discretized into finite elements that are involved in the common image correlation process by use of our algorithms. This image correlation method with finite element formulation has an advantage over subset-based image correlation methods because it satisfies the requirements of displacement continuity and derivative continuity among elements on images. Numerical studies and a real experiment are used to verify the proposed formulation. Results have shown that the image correlation with the finite element formulation is computationally efficient, accurate, and robust

  17. A new method for information retrieval in two-dimensional grating-based X-ray phase contrast imaging

    International Nuclear Information System (INIS)

    Wang Zhi-Li; Gao Kun; Chen Jian; Ge Xin; Tian Yang-Chao; Wu Zi-Yu; Zhu Pei-Ping

    2012-01-01

    Grating-based X-ray phase contrast imaging has been demonstrated to be an extremely powerful phase-sensitive imaging technique. By using two-dimensional (2D) gratings, the observable contrast is extended to two refraction directions. Recently, we have developed a novel reverse-projection (RP) method, which is capable of retrieving the object information efficiently with one-dimensional (1D) grating-based phase contrast imaging. In this contribution, we present its extension to the 2D grating-based X-ray phase contrast imaging, named the two-dimensional reverse-projection (2D-RP) method, for information retrieval. The method takes into account the nonlinear contributions of two refraction directions and allows the retrieval of the absorption, the horizontal and the vertical refraction images. The obtained information can be used for the reconstruction of the three-dimensional phase gradient field, and for an improved phase map retrieval and reconstruction. Numerical experiments are carried out, and the results confirm the validity of the 2D-RP method

  18. Evaluation of six scatter correction methods based on spectral analysis in 99m Tc SPECT imaging using SIMIND Monte Carlo simulation

    Directory of Open Access Journals (Sweden)

    Mahsa Noori Asl

    2013-01-01

    Full Text Available Compton-scattered photons included within the photopeak pulse-height window result in the degradation of SPECT images both qualitatively and quantitatively. The purpose of this study is to evaluate and compare six scatter correction methods based on setting the energy windows in 99m Tc spectrum. SIMIND Monte Carlo simulation is used to generate the projection images from a cold-sphere hot-background phantom. For evaluation of different scatter correction methods, three assessment criteria including image contrast, signal-to-noise ratio (SNR and relative noise of the background (RNB are considered. Except for the dual-photopeak window (DPW method, the image contrast of the five cold spheres is improved in the range of 2.7-26%. Among methods considered, two methods show a nonuniform correction performance. The RNB for all of the scatter correction methods is ranged from minimum 0.03 for DPW method to maximum 0.0727 for the three energy window (TEW method using trapezoidal approximation. The TEW method using triangular approximation because of ease of implementation, good improvement of the image contrast and the SNR for the five cold spheres, and the low noise level is proposed as most appropriate correction method.

  19. Method of orthogonally splitting imaging pose measurement

    Science.gov (United States)

    Zhao, Na; Sun, Changku; Wang, Peng; Yang, Qian; Liu, Xintong

    2018-01-01

    In order to meet the aviation's and machinery manufacturing's pose measurement need of high precision, fast speed and wide measurement range, and to resolve the contradiction between measurement range and resolution of vision sensor, this paper proposes an orthogonally splitting imaging pose measurement method. This paper designs and realizes an orthogonally splitting imaging vision sensor and establishes a pose measurement system. The vision sensor consists of one imaging lens, a beam splitter prism, cylindrical lenses and dual linear CCD. Dual linear CCD respectively acquire one dimensional image coordinate data of the target point, and two data can restore the two dimensional image coordinates of the target point. According to the characteristics of imaging system, this paper establishes the nonlinear distortion model to correct distortion. Based on cross ratio invariability, polynomial equation is established and solved by the least square fitting method. After completing distortion correction, this paper establishes the measurement mathematical model of vision sensor, and determines intrinsic parameters to calibrate. An array of feature points for calibration is built by placing a planar target in any different positions for a few times. An terative optimization method is presented to solve the parameters of model. The experimental results show that the field angle is 52 °, the focus distance is 27.40 mm, image resolution is 5185×5117 pixels, displacement measurement error is less than 0.1mm, and rotation angle measurement error is less than 0.15°. The method of orthogonally splitting imaging pose measurement can satisfy the pose measurement requirement of high precision, fast speed and wide measurement range.

  20. Application of video imaging for improvement of patient set-up

    International Nuclear Information System (INIS)

    Ploeger, Lennert S.; Frenay, Michel; Betgen, Anja; Bois, Josien A. de; Gilhuijs, Kenneth G.A.; Herk, Marcel van

    2003-01-01

    Background and purpose: For radiotherapy of prostate cancer, the patient is usually positioned in the left-right (LR) direction by aligning a single marker on the skin with the projection of a room laser. The aim of this study is to investigate the feasibility of a room-mounted video camera in combination with previously acquired CT data to improve patient set-up along the LR axis. Material and methods: The camera was mounted in the treatment room at the caudal side of the patient. For 22 patients with prostate cancer 127 video and portal images were acquired. The set-up error determined by video imaging was found by matching video images with rendered CT images using various techniques. This set-up error was retrospectively compared with the set-up error derived from portal images. It was investigated whether the number of corrections based on portal imaging would decrease if the information obtained from the video images had been used prior to irradiation. Movement of the skin with respect to bone was quantified using an analysis of variance method. Results: The measurement of the set-up error was most accurate for a technique where outlines and groins on the left and right side of the patient were delineated and aligned individually to the corresponding features extracted from the rendered CT image. The standard deviations (SD) of the systematic and random components of the set-up errors derived from the portal images in the LR direction were 1.5 and 2.1 mm, respectively. When the set-up of the patients was retrospectively adjusted based on the video images, the SD of the systematic and random errors decreased to 1.1 and 1.3 mm, respectively. From retrospective analysis, a reduction of the number of set-up corrections (from nine to six corrections) is expected when the set-up would have been adjusted using the video images. The SD of the magnitude of motion of the skin of the patient with respect to the bony anatomy was estimated to be 1.1 mm. Conclusion: Video

  1. A new method by steering kernel-based Richardson–Lucy algorithm for neutron imaging restoration

    International Nuclear Information System (INIS)

    Qiao, Shuang; Wang, Qiao; Sun, Jia-ning; Huang, Ji-peng

    2014-01-01

    Motivated by industrial applications, neutron radiography has become a powerful tool for non-destructive investigation techniques. However, resulted from a combined effect of neutron flux, collimated beam, limited spatial resolution of detector and scattering, etc., the images made with neutrons are degraded severely by blur and noise. For dealing with it, by integrating steering kernel regression into Richardson–Lucy approach, we present a novel restoration method in this paper, which is capable of suppressing noise while restoring details of the blurred imaging result efficiently. Experimental results show that compared with the other methods, the proposed method can improve the restoration quality both visually and quantitatively

  2. Matrix-based image reconstruction methods for tomography

    International Nuclear Information System (INIS)

    Llacer, J.; Meng, J.D.

    1984-10-01

    Matrix methods of image reconstruction have not been used, in general, because of the large size of practical matrices, ill condition upon inversion and the success of Fourier-based techniques. An exception is the work that has been done at the Lawrence Berkeley Laboratory for imaging with accelerated radioactive ions. An extension of that work into more general imaging problems shows that, with a correct formulation of the problem, positron tomography with ring geometries results in well behaved matrices which can be used for image reconstruction with no distortion of the point response in the field of view and flexibility in the design of the instrument. Maximum Likelihood Estimator methods of reconstruction, which use the system matrices tailored to specific instruments and do not need matrix inversion, are shown to result in good preliminary images. A parallel processing computer structure based on multiple inexpensive microprocessors is proposed as a system to implement the matrix-MLE methods. 14 references, 7 figures

  3. Ultrasound contrast-agent improves imaging of lower limb occlusive disease

    DEFF Research Database (Denmark)

    Eiberg, J P; Hansen, M A; Jensen, F

    2003-01-01

    to evaluate if ultrasound contrast-agent infusion could improve duplex-ultrasound imaging of peripheral arterial disease (PAD) and increase the agreement with digital subtraction arteriography (DSA).......to evaluate if ultrasound contrast-agent infusion could improve duplex-ultrasound imaging of peripheral arterial disease (PAD) and increase the agreement with digital subtraction arteriography (DSA)....

  4. Study on two-dimensional distribution of X-ray image based on improved Elman algorithm

    International Nuclear Information System (INIS)

    Wang, Fang; Wang, Ming-Yuan; Tian, Feng-Shuo; Liu, Yu-Fang; Li, Lei; Zhao, Jing

    2015-01-01

    The principle of the X-ray detector which can simultaneously perform the measurement of the exposure rate and 2D (two-dimensional) distribution is described. A commercially available CMOS image sensor has been adopted as the key part to receive X-ray without any scintillators. The correlation between the pixel value (PV) and the absorbed exposure rate of X-ray is studied using the improved Elman neural network. Comparing the optimal adjustment process of the BP (Back Propagation) neural network and the improved Elman neural network, the neural network parameters are selected based on the fitting curve and the error curve. The experiments using the practical production data show that the proposed method achieves high accurate predictions to 10 −15 , which is consistent with the anticipated value. It is proven that it is possible to detect the exposure rate using the X-ray detector with the improved Elman algorithm for its advantages of fast converges and smooth error curve. - Highlights: • A method to measure the X-ray radiation with low cost and miniaturization. • A general CMOS image sensor is used to detect X-ray. • The system can measure exposure rate and 2D distribution simultaneously. • The Elman algorithm is adopted to improve the precision of the radiation detector

  5. Generalized Row-Action Methods for Tomographic Imaging

    DEFF Research Database (Denmark)

    Andersen, Martin Skovgaard; Hansen, Per Christian

    2014-01-01

    Row-action methods play an important role in tomographic image reconstruction. Many such methods can be viewed as incremental gradient methods for minimizing a sum of a large number of convex functions, and despite their relatively poor global rate of convergence, these methods often exhibit fast...... initial convergence which is desirable in applications where a low-accuracy solution is acceptable. In this paper, we propose relaxed variants of a class of incremental proximal gradient methods, and these variants generalize many existing row-action methods for tomographic imaging. Moreover, they allow...

  6. Hyperspectral image compressing using wavelet-based method

    Science.gov (United States)

    Yu, Hui; Zhang, Zhi-jie; Lei, Bo; Wang, Chen-sheng

    2017-10-01

    Hyperspectral imaging sensors can acquire images in hundreds of continuous narrow spectral bands. Therefore each object presented in the image can be identified from their spectral response. However, such kind of imaging brings a huge amount of data, which requires transmission, processing, and storage resources for both airborne and space borne imaging. Due to the high volume of hyperspectral image data, the exploration of compression strategies has received a lot of attention in recent years. Compression of hyperspectral data cubes is an effective solution for these problems. Lossless compression of the hyperspectral data usually results in low compression ratio, which may not meet the available resources; on the other hand, lossy compression may give the desired ratio, but with a significant degradation effect on object identification performance of the hyperspectral data. Moreover, most hyperspectral data compression techniques exploits the similarities in spectral dimensions; which requires bands reordering or regrouping, to make use of the spectral redundancy. In this paper, we explored the spectral cross correlation between different bands, and proposed an adaptive band selection method to obtain the spectral bands which contain most of the information of the acquired hyperspectral data cube. The proposed method mainly consist three steps: First, the algorithm decomposes the original hyperspectral imagery into a series of subspaces based on the hyper correlation matrix of the hyperspectral images between different bands. And then the Wavelet-based algorithm is applied to the each subspaces. At last the PCA method is applied to the wavelet coefficients to produce the chosen number of components. The performance of the proposed method was tested by using ISODATA classification method.

  7. Advanced neutron imaging methods with a potential to benefit from pulsed sources

    International Nuclear Information System (INIS)

    Strobl, M.; Kardjilov, N.; Hilger, A.; Penumadu, D.; Manke, I.

    2011-01-01

    During the last decade neutron imaging has seen significant improvements in instrumentation, detection and spatial resolution. Additionally, a variety of new applications and methods have been explored. As a consequence of an outstanding development nowadays various techniques of neutron imaging go far beyond a two- and three-dimensional mapping of the attenuation coefficients for a broad range of samples. Neutron imaging has become sensitive to neutron scattering in the small angle scattering range as well as with respect to Bragg scattering. Corresponding methods potentially provide spatially resolved and volumetric data revealing microstructural inhomogeneities, texture variations, crystalline phase distributions and even strains in bulk samples. Other techniques allow for the detection of refractive index distribution through phase sensitive measurements and the utilization of polarized neutrons enables radiographic and tomographic investigations of magnetic fields and properties as well as electrical currents within massive samples. All these advanced methods utilize or depend on wavelength dependent signals, and are hence suited to profit significantly from pulsed neutron sources as will be discussed.

  8. 3D Seismic Imaging using Marchenko Methods

    Science.gov (United States)

    Lomas, A.; Curtis, A.

    2017-12-01

    Marchenko methods are novel, data driven techniques that allow seismic wavefields from sources and receivers on the Earth's surface to be redatumed to construct wavefields with sources in the subsurface - including complex multiply-reflected waves, and without the need for a complex reference model. In turn, this allows subsurface images to be constructed at any such subsurface redatuming points (image or virtual receiver points). Such images are then free of artefacts from multiply-scattered waves that usually contaminate migrated seismic images. Marchenko algorithms require as input the same information as standard migration methods: the full reflection response from sources and receivers at the Earth's surface, and an estimate of the first arriving wave between the chosen image point and the surface. The latter can be calculated using a smooth velocity model estimated using standard methods. The algorithm iteratively calculates a signal that focuses at the image point to create a virtual source at that point, and this can be used to retrieve the signal between the virtual source and the surface. A feature of these methods is that the retrieved signals are naturally decomposed into up- and down-going components. That is, we obtain both the signal that initially propagated upwards from the virtual source and arrived at the surface, separated from the signal that initially propagated downwards. Figure (a) shows a 3D subsurface model with a variable density but a constant velocity (3000m/s). Along the surface of this model (z=0) in both the x and y directions are co-located sources and receivers at 20-meter intervals. The redatumed signal in figure (b) has been calculated using Marchenko methods from a virtual source (1200m, 500m and 400m) to the surface. For comparison the true solution is given in figure (c), and shows a good match when compared to figure (b). While these 2D redatuming and imaging methods are still in their infancy having first been developed in

  9. THE EFFECT OF IMAGE ENHANCEMENT METHODS DURING FEATURE DETECTION AND MATCHING OF THERMAL IMAGES

    Directory of Open Access Journals (Sweden)

    O. Akcay

    2017-05-01

    Full Text Available A successful image matching is essential to provide an automatic photogrammetric process accurately. Feature detection, extraction and matching algorithms have performed on the high resolution images perfectly. However, images of cameras, which are equipped with low-resolution thermal sensors are problematic with the current algorithms. In this paper, some digital image processing techniques were applied to the low-resolution images taken with Optris PI 450 382 x 288 pixel optical resolution lightweight thermal camera to increase extraction and matching performance. Image enhancement methods that adjust low quality digital thermal images, were used to produce more suitable images for detection and extraction. Three main digital image process techniques: histogram equalization, high pass and low pass filters were considered to increase the signal-to-noise ratio, sharpen image, remove noise, respectively. Later on, the pre-processed images were evaluated using current image detection and feature extraction methods Maximally Stable Extremal Regions (MSER and Speeded Up Robust Features (SURF algorithms. Obtained results showed that some enhancement methods increased number of extracted features and decreased blunder errors during image matching. Consequently, the effects of different pre-process techniques were compared in the paper.

  10. Actions improving the image of a nurse in electronic media. Opinion of students at medical courses

    Directory of Open Access Journals (Sweden)

    Jakubowska Klaudia

    2017-09-01

    Full Text Available Aim. The aim of study was to define actions improving the image of nurses in electronic media. Material and method. 219 women and 44 men took part in a survey. They were the students of the following courses: nursing, medical rescue, obstetrics, medicine, dentistry, pharmaceutics, physiotherapy, public health. The studies were undertaken with use of own questionnaire in 2015. Results. Majority of respondents 64,6% (n=169 stated that improvement of image of their own profession belongs to the nurses, and only 35,4% (n=93 respondents indicated that the professional organizations of nurses and midwives have their impact on it. According to the students, the most crucial action that should be undertaken by professional organizations in order to improve the image of profession in electronic media was the improvement of wages and working conditions (72,2%, n=189 and better promotion of the profession in electronic media (73,8%, n=193. The nurses can influence the improvement of their image in media by taking care of the good opinion about the profession by setting good example (32%, n=84, and also by creating blogs, social forum, online information services, etc. (26,2%, n=69. Conclusions. According to the respondents, the image of a nurse in electronic media is shaped by the television and radio. The mentioned media tend to present nursing environment in a negative light. The data analysis shows that according to the respondents, the professional organizations of nurses and midwives and nurses themselves should be responsible for improvement of the situation. In order to improve the image, the nurses should promote professional achievements, change the stereotype used in shows and movies, and familiarize the public with the profession. The following branches of mass media should be used: internet websites, television and radio.

  11. Application of image processing methods to industrial radiography

    International Nuclear Information System (INIS)

    Goutte, R.; Odet, C.; Tuncer, T.; Bodson, F.; Varcin, E.

    1985-01-01

    This study was carried out with the financial support of the Commission of the European Communities as part of the CECA research program comprising of IRSID, INSA de Lyon and the Framatome and Creusot Loire companies. Its purpose was to evaluate the possibility of using digital enhancement of radiographic images to improve defect visibility in industrial radiography, thereby providing assistance in defect detection and a method for automatic analysis of radiographs. This paper provides full results obtained from work on digital processing of radiographs showing real and artificial defects. Furthermore, work on simulated automatic defect detection is also presented. 2 refs

  12. Does thorax EIT image analysis depend on the image reconstruction method?

    Science.gov (United States)

    Zhao, Zhanqi; Frerichs, Inéz; Pulletz, Sven; Müller-Lisse, Ullrich; Möller, Knut

    2013-04-01

    Different methods were proposed to analyze the resulting images of electrical impedance tomography (EIT) measurements during ventilation. The aim of our study was to examine if the analysis methods based on back-projection deliver the same results when applied on images based on other reconstruction algorithms. Seven mechanically ventilated patients with ARDS were examined by EIT. The thorax contours were determined from the routine CT images. EIT raw data was reconstructed offline with (1) filtered back-projection with circular forward model (BPC); (2) GREIT reconstruction method with circular forward model (GREITC) and (3) GREIT with individual thorax geometry (GREITT). Three parameters were calculated on the resulting images: linearity, global ventilation distribution and regional ventilation distribution. The results of linearity test are 5.03±2.45, 4.66±2.25 and 5.32±2.30 for BPC, GREITC and GREITT, respectively (median ±interquartile range). The differences among the three methods are not significant (p = 0.93, Kruskal-Wallis test). The proportions of ventilation in the right lung are 0.58±0.17, 0.59±0.20 and 0.59±0.25 for BPC, GREITC and GREITT, respectively (p = 0.98). The differences of the GI index based on different reconstruction methods (0.53±0.16, 0.51±0.25 and 0.54±0.16 for BPC, GREITC and GREITT, respectively) are also not significant (p = 0.93). We conclude that the parameters developed for images generated with GREITT are comparable with filtered back-projection and GREITC.

  13. Improved initial guess with semi-subpixel level accuracy in digital image correlation by feature-based method

    Science.gov (United States)

    Zhang, Yunlu; Yan, Lei; Liou, Frank

    2018-05-01

    The quality initial guess of deformation parameters in digital image correlation (DIC) has a serious impact on convergence, robustness, and efficiency of the following subpixel level searching stage. In this work, an improved feature-based initial guess (FB-IG) scheme is presented to provide initial guess for points of interest (POIs) inside a large region. Oriented FAST and Rotated BRIEF (ORB) features are semi-uniformly extracted from the region of interest (ROI) and matched to provide initial deformation information. False matched pairs are eliminated by the novel feature guided Gaussian mixture model (FG-GMM) point set registration algorithm, and nonuniform deformation parameters of the versatile reproducing kernel Hilbert space (RKHS) function are calculated simultaneously. Validations on simulated images and real-world mini tensile test verify that this scheme can robustly and accurately compute initial guesses with semi-subpixel level accuracy in cases with small or large translation, deformation, or rotation.

  14. Methods of producing luminescent images

    International Nuclear Information System (INIS)

    Broadhead, P.; Newman, G.A.

    1977-01-01

    A method is described for producing a luminescent image in a layer of a binding material in which is dispersed a thermoluminescent material. The layer is heated uniformly to a temperature of 80 to 300 0 C and is exposed to luminescence inducing radiation whilst so heated. The preferred exposing radiation is X-rays and preferably the thermoluminescent material is insensitive to electromagnetic radiation of wavelength longer than 300 mm. Information concerning preparation of the luminescent material is given in BP 1,347,672; this material has the advantage that at elevated temperatures it shows increased sensitivity compared with room temperature. At temperatures in the range 80 to 150 0 C the thermoluminescent material exhibits 'afterglow', allowing the image to persist for several seconds after the X-radiation has ceased, thus allowing the image to be retained for visual inspection in this temperature range. At higher temperatures, however, there is negligible 'afterglow'. The thermoluminescent layers so produced are particularly useful as fluoroscopic screens. The preferred method of heating the thermoluminescent material is described in BP 1,354,149. An example is given of the application of the method. (U.K.)

  15. Mathematical methods in elasticity imaging

    CERN Document Server

    Ammari, Habib; Garnier, Josselin; Kang, Hyeonbae; Lee, Hyundae; Wahab, Abdul

    2015-01-01

    This book is the first to comprehensively explore elasticity imaging and examines recent, important developments in asymptotic imaging, modeling, and analysis of deterministic and stochastic elastic wave propagation phenomena. It derives the best possible functional images for small inclusions and cracks within the context of stability and resolution, and introduces a topological derivative-based imaging framework for detecting elastic inclusions in the time-harmonic regime. For imaging extended elastic inclusions, accurate optimal control methodologies are designed and the effects of uncertainties of the geometric or physical parameters on stability and resolution properties are evaluated. In particular, the book shows how localized damage to a mechanical structure affects its dynamic characteristics, and how measured eigenparameters are linked to elastic inclusion or crack location, orientation, and size. Demonstrating a novel method for identifying, locating, and estimating inclusions and cracks in elastic...

  16. FUSION SEGMENTATION METHOD BASED ON FUZZY THEORY FOR COLOR IMAGES

    Directory of Open Access Journals (Sweden)

    J. Zhao

    2017-09-01

    Full Text Available The image segmentation method based on two-dimensional histogram segments the image according to the thresholds of the intensity of the target pixel and the average intensity of its neighborhood. This method is essentially a hard-decision method. Due to the uncertainties when labeling the pixels around the threshold, the hard-decision method can easily get the wrong segmentation result. Therefore, a fusion segmentation method based on fuzzy theory is proposed in this paper. We use membership function to model the uncertainties on each color channel of the color image. Then, we segment the color image according to the fuzzy reasoning. The experiment results show that our proposed method can get better segmentation results both on the natural scene images and optical remote sensing images compared with the traditional thresholding method. The fusion method in this paper can provide new ideas for the information extraction of optical remote sensing images and polarization SAR images.

  17. TU-CD-BRA-12: Coupling PET Image Restoration and Segmentation Using Variational Method with Multiple Regularizations

    Energy Technology Data Exchange (ETDEWEB)

    Li, L; Tan, S [Huazhong University of Science and Technology, Wuhan, Hubei (China); Lu, W [University of Maryland School of Medicine, Baltimore, MD (United States)

    2015-06-15

    Purpose: To propose a new variational method which couples image restoration with tumor segmentation for PET images using multiple regularizations. Methods: Partial volume effect (PVE) is a major degrading factor impacting tumor segmentation accuracy in PET imaging. The existing segmentation methods usually need to take prior calibrations to compensate PVE and they are highly system-dependent. Taking into account that image restoration and segmentation can promote each other and they are tightly coupled, we proposed a variational method to solve the two problems together. Our method integrated total variation (TV) semi-blind deconvolution and Mumford-Shah (MS) segmentation. The TV norm was used on edges to protect the edge information, and the L{sub 2} norm was used to avoid staircase effect in the no-edge area. The blur kernel was constrained to the Gaussian model parameterized by its variance and we assumed that the variances in the X-Y and Z directions are different. The energy functional was iteratively optimized by an alternate minimization algorithm. Segmentation performance was tested on eleven patients with non-Hodgkin’s lymphoma, and evaluated by Dice similarity index (DSI) and classification error (CE). For comparison, seven other widely used methods were also tested and evaluated. Results: The combination of TV and L{sub 2} regularizations effectively improved the segmentation accuracy. The average DSI increased by around 0.1 than using either the TV or the L{sub 2} norm. The proposed method was obviously superior to other tested methods. It has an average DSI and CE of 0.80 and 0.41, while the FCM method — the second best one — has only an average DSI and CE of 0.66 and 0.64. Conclusion: Coupling image restoration and segmentation can handle PVE and thus improves tumor segmentation accuracy in PET. Alternate use of TV and L2 regularizations can further improve the performance of the algorithm. This work was supported in part by National Natural

  18. Preliminary study on effects of 60Co γ-irradiation on video quality and the image de-noising methods

    International Nuclear Information System (INIS)

    Yuan Mei; Zhao Jianbin; Cui Lei

    2011-01-01

    There will be variable noises appear on images in video once the play device irradiated by γ-rays, so as to affect the image clarity. In order to eliminate the image noising, the affection mechanism of γ-irradiation on video-play device was studied in this paper and the methods to improve the image quality with both hardware and software were proposed by use of protection program and de-noising algorithm. The experimental results show that the scheme of video de-noising based on hardware and software can improve effectively the PSNR by 87.5 dB. (authors)

  19. GRAPHICS-IMAGE MIXED METHOD FOR LARGE-SCALE BUILDINGS RENDERING

    Directory of Open Access Journals (Sweden)

    Y. Zhou

    2018-05-01

    Full Text Available Urban 3D model data is huge and unstructured, LOD and Out-of-core algorithm are usually used to reduce the amount of data that drawn in each frame to improve the rendering efficiency. When the scene is large enough, even the complex optimization algorithm is difficult to achieve better results. Based on the traditional study, a novel idea was developed. We propose a graphics and image mixed method for large-scale buildings rendering. Firstly, the view field is divided into several regions, the graphics-image mixed method used to render the scene on both screen and FBO, then blending the FBO with scree. The algorithm is tested on the huge CityGML model data in the urban areas of New York which contained 188195 public building models, and compared with the Cesium platform. The experiment result shows the system was running smoothly. The experimental results confirm that the algorithm can achieve more massive building scene roaming under the same hardware conditions, and can rendering the scene without vision loss.

  20. A comparison of reconstruction methods for undersampled atomic force microscopy images

    International Nuclear Information System (INIS)

    Luo, Yufan; Andersson, Sean B

    2015-01-01

    Non-raster scanning and undersampling of atomic force microscopy (AFM) images is a technique for improving imaging rate and reducing the amount of tip–sample interaction needed to produce an image. Generation of the final image can be done using a variety of image processing techniques based on interpolation or optimization. The choice of reconstruction method has a large impact on the quality of the recovered image and the proper choice depends on the sample under study. In this work we compare interpolation through the use of inpainting algorithms with reconstruction based on optimization through the use of the basis pursuit algorithm commonly used for signal recovery in compressive sensing. Using four different sampling patterns found in non-raster AFM, namely row subsampling, spiral scanning, Lissajous scanning, and random scanning, we subsample data from existing images and compare reconstruction performance against the original image. The results illustrate that inpainting generally produces superior results when the image contains primarily low frequency content while basis pursuit is better when the images have mixed, but sparse, frequency content. Using support vector machines, we then classify images based on their frequency content and sparsity and, from this classification, develop a fast decision strategy to select a reconstruction algorithm to be used on subsampled data. The performance of the classification and decision test are demonstrated on test AFM images. (paper)

  1. An attenuation correction method for PET/CT images

    International Nuclear Information System (INIS)

    Ue, Hidenori; Yamazaki, Tomohiro; Haneishi, Hideaki

    2006-01-01

    In PET/CT systems, accurate attenuation correction can be achieved by creating an attenuation map from an X-ray CT image. On the other hand, respiratory-gated PET acquisition is an effective method for avoiding motion blurring of the thoracic and abdominal organs caused by respiratory motion. In PET/CT systems employing respiratory-gated PET, using an X-ray CT image acquired during breath-holding for attenuation correction may have a large effect on the voxel values, especially in regions with substantial respiratory motion. In this report, we propose an attenuation correction method in which, as the first step, a set of respiratory-gated PET images is reconstructed without attenuation correction, as the second step, the motion of each phase PET image from the PET image in the same phase as the CT acquisition timing is estimated by the previously proposed method, as the third step, the CT image corresponding to each respiratory phase is generated from the original CT image by deformation according to the motion vector maps, and as the final step, attenuation correction using these CT images and reconstruction are performed. The effectiveness of the proposed method was evaluated using 4D-NCAT phantoms, and good stability of the voxel values near the diaphragm was observed. (author)

  2. A method to test the reproducibility and to improve performance of computer-aided detection schemes for digitized mammograms

    International Nuclear Information System (INIS)

    Zheng Bin; Gur, David; Good, Walter F.; Hardesty, Lara A.

    2004-01-01

    The purpose of this study is to develop a new method for assessment of the reproducibility of computer-aided detection (CAD) schemes for digitized mammograms and to evaluate the possibility of using the implemented approach for improving CAD performance. Two thousand digitized mammograms (representing 500 cases) with 300 depicted verified masses were selected in the study. Series of images were generated for each digitized image by resampling after a series of slight image rotations. A CAD scheme developed in our laboratory was applied to all images to detect suspicious mass regions. We evaluated the reproducibility of the scheme using the detection sensitivity and false-positive rates for the original and resampled images. We also explored the possibility of improving CAD performance using three methods of combining results from the original and resampled images, including simple grouping, averaging output scores, and averaging output scores after grouping. The CAD scheme generated a detection score (from 0 to 1) for each identified suspicious region. A region with a detection score >0.5 was considered as positive. The CAD scheme detected 238 masses (79.3% case-based sensitivity) and identified 1093 false-positive regions (average 0.55 per image) in the original image dataset. In eleven repeated tests using original and ten sets of rotated and resampled images, the scheme detected a maximum of 271 masses and identified as many as 2359 false-positive regions. Two hundred and eighteen masses (80.4%) and 618 false-positive regions (26.2%) were detected in all 11 sets of images. Combining detection results improved reproducibility and the overall CAD performance. In the range of an average false-positive detection rate between 0.5 and 1 per image, the sensitivity of the scheme could be increased approximately 5% after averaging the scores of the regions detected in at least four images. At low false-positive rate (e.g., ≤average 0.3 per image), the grouping method

  3. Registration methods for pulmonary image analysis integration of morphological and physiological knowledge

    CERN Document Server

    Schmidt-Richberg, Alexander

    2014-01-01

    Various applications in the field of pulmonary image analysis require a registration of CT images of the lung. For example, a registration-based estimation of the breathing motion is employed to increase the accuracy of dose distribution in radiotherapy. Alexander Schmidt-Richberg develops methods to explicitly model morphological and physiological knowledge about respiration in algorithms for the registration of thoracic CT images. The author focusses on two lung-specific issues: on the one hand, the alignment of the interlobular fissures and on the other hand, the estimation of sliding motion at the lung boundaries. He shows that by explicitly considering these aspects based on a segmentation of the respective structure, registration accuracy can be significantly improved.

  4. Improved quality of image got through whole-body CT scanner

    International Nuclear Information System (INIS)

    Asahina, Kiyotaka

    1980-01-01

    The quality of brain images taken with a whole-body CT scanner has so far been generally inferior in quality to those got through a CT scanner exclusively used for brains. In order to improve the whole-body CT scanner so as to get better brain image, its detection system has been made multichannel; the capacity of its X-ray tube, increased; and its software, innovated. As a result, the spatial resolution has been improved from 5.51 p/cm to 9.01 p/cm, the contrast resolution has been improved from 3.2 mm% to 1.5 mm%, with the noise maintained at 0.5%. In clinical examination, the image quality has been improved equally well for brains, abdomens and lungs. Especially high appreciation is given to the diagnosis information got through this new scanner. (author)

  5. Data-adapted moving least squares method for 3-D image interpolation

    International Nuclear Information System (INIS)

    Jang, Sumi; Lee, Yeon Ju; Jeong, Byeongseon; Nam, Haewon; Lee, Rena; Yoon, Jungho

    2013-01-01

    In this paper, we present a nonlinear three-dimensional interpolation scheme for gray-level medical images. The scheme is based on the moving least squares method but introduces a fundamental modification. For a given evaluation point, the proposed method finds the local best approximation by reproducing polynomials of a certain degree. In particular, in order to obtain a better match to the local structures of the given image, we employ locally data-adapted least squares methods that can improve the classical one. Some numerical experiments are presented to demonstrate the performance of the proposed method. Five types of data sets are used: MR brain, MR foot, MR abdomen, CT head, and CT foot. From each of the five types, we choose five volumes. The scheme is compared with some well-known linear methods and other recently developed nonlinear methods. For quantitative comparison, we follow the paradigm proposed by Grevera and Udupa (1998). (Each slice is first assumed to be unknown then interpolated by each method. The performance of each interpolation method is assessed statistically.) The PSNR results for the estimated volumes are also provided. We observe that the new method generates better results in both quantitative and visual quality comparisons. (paper)