The Experts below are selected from a list of 19704 Experts worldwide ranked by ideXlab platform
John W. Clark - One of the best experts on this subject based on the ideXlab platform.
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nonlinear multiscale wavelet diffusion for speckle suppression and Edge Enhancement in ultrasound images
IEEE Transactions on Medical Imaging, 2006Co-Authors: Yong Yue, M.m. Croitoru, A. Bidani, Joseph B. Zwischenberger, John W. ClarkAbstract:This paper introduces a novel nonlinear multiscale wavelet diffusion method for ultrasound speckle suppression and Edge Enhancement. This method is designed to utilize the favorable denoising properties of two frequently used techniques: the sparsity and multiresolution properties of the wavelet, and the iterative Edge Enhancement feature of nonlinear diffusion. With fully exploited knowlEdge of speckle image models, the Edges of images are detected using normalized wavelet modulus. Relying on this feature, both the envelope-detected speckle image and the log-compressed ultrasonic image can be directly processed by the algorithm without need for additional preprocessing. Speckle is suppressed by employing the iterative multiscale diffusion on the wavelet coefficients. With a tuning diffusion threshold strategy, the proposed method can improve the image quality for both visualization and auto-segmentation applications. We validate our method using synthetic speckle images and real ultrasonic images. Performance improvement over other despeckling filters is quantified in terms of noise suppression and Edge preservation indices.
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Ultrasound Speckle Suppression and Edge Enhancement Using Multiscale Nonlinear Wavelet Diffusion
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and, 2005Co-Authors: Yong Yue, M.m. Croitoru, A. Bidani, Joseph B. Zwischenberger, John W. ClarkAbstract:This paper introduces a novel multiscale nonlinear wavelet diffusion (MNWD) method for ultrasound speckle suppression and Edge Enhancement. It considers wavelet diffusion as an approximation to nonlinear diffusion within the framework of the dyadic wavelet transform. Consequently, this knowlEdge is exploited in the design of a speckle suppression filter with an Edge Enhancement feature. MNWD takes advantage of the sparsity and multiresolution properties of wavelet, and the iterative Edge Enhancement feature of nonlinear diffusion. In our algorithm, speckle is suppressed by employing the iterative multiscale diffusion on the wavelet coefficients, while the Edges of the image are enhanced by using an iterative signal compensation process. We validate the proposed method using synthetic and real echocardiographic images. Performance improvement over other traditional denoising filters is quantified in terms of noise suppression and structural preservation indices. The application of the proposed method is demonstrated by the segmentation of the echocardiographic image using the active contour
Wenqia Wang - One of the best experts on this subject based on the ideXlab platform.
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Feature Preserving Nonlinear Diffusion for Ultrasonic Image Denoising and Edge Enhancement
2007Co-Authors: Qiuqi Ruan, Wenqia WangAbstract:Utilizing echoic intension and distribution from different organs and local details of human body, ultrasonic image can catch important medical pathological changes, which unfortunately may be affected by ultrasonic speckle noise. A feature preserving ultrasonic image denoising and Edge Enhancement scheme is put forth, which includes two terms: anisotropic diffusion and Edge Enhancement, controlled by the optimum smoothing time. In this scheme, the anisotropic diffusion is governed by the local coordinate transformation and the first and the second order normal derivatives of the image, while the Edge Enhancement is done by the hyperbolic tangent function. Experiments on real ultrasonic images indicate effective preservation of Edges, local details and ultrasonic echoic bright strips on denoising by our scheme. Keywords—anisotropic diffusion, coordinate transformation directional derivatives, Edge Enhancement, hyperbolic tangent function, image denoising.
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ISCAS (3) - A compound anisotropic diffusion for ultrasonic image denoising and Edge Enhancement
2005 IEEE International Symposium on Circuits and Systems, 1Co-Authors: Qiuqi Ruan, Wenqia WangAbstract:Utilizing the echoic intension and the distribution from different organs and local details of the human body, ultrasonic images can catch important medical pathological changes, which unfortunately may be affected by ultrasonic speckle noise. An ultrasonic image denoising and Edge Enhancement scheme is put forth, which compounds two terms: an anisotropic diffusion and an Edge Enhancement, coupled by an iterative split implementation. To preserve image features, the anisotropic diffusion is governed by a local coordinate transformation, the first and second normal derivatives of the image, and the Edge Enhancement is done by a hyperbolic tangent function. Experiments on real ultrasonic images indicate effective preservation of Edges, local details and ultrasonic echoic bright strips on denoising by our scheme.
David R Pickens - One of the best experts on this subject based on the ideXlab platform.
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Phase-contrast digital tomosynthesis.
Medical Physics, 2011Co-Authors: Jeffrey C. Hammonds, Edwin F. Donnelly, Ronald R. Price, David R PickensAbstract:PURPOSE: Phase-contrast (PC) Edge Enhancement occurs at the boundary between different tissues and is an interference effect that results from the differential phase-shifts that the x-rays acquire while traversing the two tissues. While observable in planar phase-contrast radiographs, the impact of digital tomosynthesis on this Edge Enhancement effect has not been previously reported. The purpose of this work is to demonstrate: (1) that phase-contrast digital tomosynthesis (PC-DTS) is possible with a conventional x-ray source, (2) that the reconstructed tomosynthesis images demonstrate and retain Edge Enhancement as compared to planar phase-contrast radiographs and (3) tomosynthesis improves object contrast by reducing the effects of superimposed structures. METHODS: An unmodified, commercially available cabinet x-ray system (Faxitron LX-60) was used. The system contains a tungsten anode x-ray tube that was operated at 24 kVp and 3 mAs for each PC radiographic image taken, with a nominal focal spot size of 0.010 mm. The digital detector uses CsI/CMOS with a pixel size of 0.054 mm x 0.054 mm. Objects to be imaged were attached to a computer-controlled rotating motor and are rotated +/- 25 degrees about a central position in one degree increments. At each increment, three phase-contrast radiographs are taken and then averaged to reduce the effect of noise. These planar images are then used to reconstruct a series of 56 longitudinal tomographic images with an image offset increment of about 0.7 mm. RESULTS: Tomographic z-plane resolution was measured to be approximately 4 mm. When compared to planar PC images, the tomosynthesis images were shown to retain the PC boundary Edge Enhancement in addition to an improvement in object contrast. CONCLUSIONS: Our work demonstrates that PC digital tomosynthesis retains the Edge-Enhancement observed in planar PC radiograph and further improves soft-tissue conspicuity by reducing the effects of superimposed tissue structure.
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characterization of the phase contrast radiography Edge Enhancement effect in a cabinet x ray system
Physics in Medicine and Biology, 2006Co-Authors: Edwin F. Donnelly, David R Pickens, Kenneth G Lewis, Kristy M Wolske, Ronald R. PriceAbstract:The purpose of this study was to demonstrate that a commercially available cabinet x-ray system is capable of phase-contrast radiography (PC-R) and to evaluate the effect of different system parameters on the degree of Edge Enhancement. An acrylic plastic Edge phantom was imaged at different tube potentials (25–60 kV) and in different geometries (variable object-to-detector distances, R2, at a constant source-to-detector distance, R1 + R2). In addition, the effect of noise on the perceived Edge Enhancement was studied as a function of exposure time. Our results show that a modest degree of phase contrast can be achieved in an unmodified cabinet x-ray system. In addition, the particular system evaluated allowed low-noise PC-R images to be obtained with short (6 s or less) exposures. These results suggest that with appropriate geometric choices PC-R is already available to a wide range of research scientists for use in both small-animal and human-specimen experiments.
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Quantification of the effect of system and object parameters on Edge Enhancement in phase-contrast radiography.
Medical physics, 2003Co-Authors: Edwin F. Donnelly, Ronald R. Price, David R PickensAbstract:The purpose of this study was to evaluate the effects of system parameters (focal spot size, tube voltage, geometry, detector resolution, and image noise) and object characteristics (Edge gradient/ shape, composition, thickness, and overlying attenuating material) upon the Edge Enhancement effect in phase-contrast radiography. Each variable of interest was adjusted and images of a 3 mm lucite phantom were obtained with the other variables remaining constant. A microfocus x-ray source coupled to a CCD camera with an intensifying screen was used to acquire the digital images. Two parameters of image analysis were used to quantify the effects. The Edge Enhancement index (EEI) was used to measure the absolute degree of Edge Enhancement, while the Edge Enhancement to noise ratio (EE/N) was used to measure the conspicuity of the Edge Enhancement relative to image noise. Little effect on EEI was seen from tube voltage, object thickness, overlying attenuating material, while focal spot size and system geometry demonstrated measurable effects upon the degree of Edge Enhancement. It was also shown that while the Edge Enhancement effect over straight Edges is highly dependent upon how the Edge aligns with the x-ray beam, rounded Edges, which better model biological objects, do not suffer from this dependence and the EEI reaches its maximal level at any alignment. Decreasing detector resolution diminished the EEI slightly, but even with pixel sizes of 0.360 x 0.360 mm Edge Enhancement effects were readily visible. The effect of image noise on EE/N was evaluated using different exposure times showing an expected improvement with longer exposure time with EE/N approaching a plateau at 5 min. Many of the parameters that will go into the design of a future PC-R imaging system have been quantified in terms of their effect on the degree of Edge Enhancement in the acquired image. These results, taken together, indicate that either a specimen or even clinical breast imaging system could be created with currently available technology. The major limitation to a clinical system would be the low x-ray flux from the microfocal x-ray source.
Paramasivam Senthilkumaran - One of the best experts on this subject based on the ideXlab platform.
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Edge Enhancement by negative Poincare–Hopf index filters
Optics letters, 2018Co-Authors: B S Bhargava Ram, Paramasivam SenthilkumaranAbstract:Phase and polarization are interrelated quantities, and hence polarization elements that perform like phase elements can be designed. In this Letter, we show that a polarizing element producing a negative Poincare–Hopf (PH) index beam can be used as a spatial filter to perform Edge Enhancement. Either isotropic or anisotropic Edge Enhancement can be achieved by polarization selection of the light that illuminates the sample. A conventional microscope imaging system is modified into a polarization-selective optical Fourier processor. Experimental results are presented to show that negative PH index filters, producing a set of orthogonal polarization distribution and their superpositions, can also be used for Edge Enhancement in optical signal processing.
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Polarization-based spatial filtering for directional and nondirectional Edge Enhancement using an S-waveplate
Applied optics, 2017Co-Authors: B S Bhargava Ram, Paramasivam Senthilkumaran, Anurag SharmaAbstract:Using polarization as an additional parameter apart from amplitude and phase in spatial filtering experiments offers additional advantages and possibilities. An S-waveplate that can convert a linearly polarized light into radially or azimuthally polarized light can also be used for isotropic Edge Enhancement. For anisotropic Edge Enhancement, introduction of a polarizer at the output was recommended and Edge selection was done by orientation of the polarizer. But the full potential of the S-waveplate as a spatial filter has not been exploited so far. Unlike the standard amplitude and phase-based Fourier filters, which are independent to the state of polarization of the illuminating beam, the S-waveplate acts in a different way depending on the state of polarization. The Edge selection does not need to be carried out by changing the orientation of the polarizer. With a fixed polarizer at the output, we show that either isotropic or anisotropic Edge Enhancement in any desired orientation can be performed by operating the same spatial filter setup in different illuminating polarization states.
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Selective Edge Enhancement using shifted anisotropic vortex filter
Journal of Optics, 2013Co-Authors: Manoj Kumar Sharma, Joby Joseph, Paramasivam SenthilkumaranAbstract:We propose a new method for selective Edge Enhancement using shifted anisotropic vortex phase mask. The shifted anisotropic phase mask is generated by introducing controllable anisotropy in conventional vortex mask [ $$ \exp \left( {i\theta } \right) $$ ] with the help of sine function and shifting the singularity away from the zero frequency component in the filter plane. The shifted anisotropic vortex mask is capable of enhancing the Edges of the given object selectively in any desired direction.
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selective Edge Enhancement using shifted anisotropic vortex filter
Journal of Optics, 2013Co-Authors: Manoj Kumar Sharma, Joby Joseph, Paramasivam SenthilkumaranAbstract:We propose a new method for selective Edge Enhancement using shifted anisotropic vortex phase mask. The shifted anisotropic phase mask is generated by introducing controllable anisotropy in conventional vortex mask (exp iθ ðÞ ) with the help of sine function and shifting the singularity away from the zero frequency component in the filter plane. The shifted anisotropic vortex mask is capable of enhanc- ing the Edges of the given object selectively in any desired direction.
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Selective Edge Enhancement using anisotropic vortex filter.
Applied optics, 2011Co-Authors: Manoj Kumar Sharma, Joby Joseph, Paramasivam SenthilkumaranAbstract:In optical image processing, selective Edge Enhancement is important when it is preferable to emphasize some Edges of an object more than others. We propose a new method for selective Edge Enhancement of amplitude objects using the anisotropic vortex phase mask by introducing anisotropy in a conventional vortex mask with the help of the sine function. The anisotropy is capable of Edge Enhancement in the selective region and in the required direction by changing the power and offset angle, respectively, of the sine function.
Guowei Teng - One of the best experts on this subject based on the ideXlab platform.
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Video Super-Resolution Based on Generative Adversarial Network and Edge Enhancement
Electronics, 2021Co-Authors: Jialu Wang, Guowei TengAbstract:With the help of deep neural networks, video super-resolution (VSR) has made a huge breakthrough. However, these deep learning-based methods are rarely used in specific situations. In addition, training sets may not be suitable because many methods only assume that under ideal circumstances, low-resolution (LR) datasets are downgraded from high-resolution (HR) datasets in a fixed manner. In this paper, we proposed a model based on Generative Adversarial Network (GAN) and Edge Enhancement to perform super-resolution (SR) reconstruction for LR and blur videos, such as closed-circuit television (CCTV). The adversarial loss allows discriminators to be trained to distinguish between SR frames and ground truth (GT) frames, which is helpful to produce realistic and highly detailed results. The Edge Enhancement function uses the Laplacian Edge module to perform Edge Enhancement on the intermediate result, which helps further improve the final results. In addition, we add the perceptual loss to the loss function to obtain a higher visual experience. At the same time, we also tried training network on different datasets. A large number of experiments show that our method has advantages in the Vid4 dataset and other LR videos.
