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.

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

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.

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.

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

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)

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.

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.

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.

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.

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

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.

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.

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.

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.

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....

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.

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.

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...

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.

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.

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.

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

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.

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.

[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.

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

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

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.

[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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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)

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.

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.

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)

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.

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.

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.

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

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.

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.

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

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.

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.

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.

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.

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

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...

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.

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.

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.

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.

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.

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 ...

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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...

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)

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)

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.

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.

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.

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.

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)

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.

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)

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.

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.

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

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...

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.

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.

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.

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.

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.

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

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.

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.

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)

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.

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

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)

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.

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

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

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...

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...

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.

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

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

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.

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.)

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.

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.

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.

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.

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

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.

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).

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.

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)

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

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.

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)

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)

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...

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)

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.

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.

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)

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.

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.

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.

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.

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.

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

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)

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.

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....

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....

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

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.

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

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.

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.

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.

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

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.

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

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

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

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

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.

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.

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...

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).

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

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.

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

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

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).

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.

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)

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.

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.

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)

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.

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.

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

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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.

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.

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.

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.

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.

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.

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.

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.

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.

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

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.

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

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.

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.)

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.

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.

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

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

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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.

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)

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.

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

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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.

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.

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

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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.

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.

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

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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.

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.

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

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.

Anatomical image-guided fluorescence molecular tomography reconstruction using kernel method

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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

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.

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

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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.

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

a Hyperspectral Image Classification Method Using Isomap and Rvm

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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.

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.

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

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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

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...

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.

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

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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.

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.

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.

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.

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

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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.

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�

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�

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)

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.

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...

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

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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.

Classification Method in Integrated Information Network Using Vector Image Comparison

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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.

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.

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.

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.

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.

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.

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.

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.

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.

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

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.

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.

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...

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.

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)

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

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.

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.

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

[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.

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.

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.

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)

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.

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 ...

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.

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

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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.

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.

[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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.)

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...

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

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.

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...

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...

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

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)

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.

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)

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

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

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.

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

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.

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.

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.

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

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

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

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.

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...

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.)

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

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).

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.

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.

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

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

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.

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.

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

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.

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.

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.

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

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.

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.

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