- Cairo, Al Qahirah, Egypt
Ahmed Elnokrashy
Benha University, Electrical Engineering, Faculty Member
4D ultrasound is one of the most advancing visualization techniques of the ultrasound dataset. it is subdivided into main five visualization modes volume render, maximum, minimum, mean, and the surface render. The surface render... more
4D ultrasound is one of the most advancing visualization techniques of the ultrasound dataset. it is subdivided into main five visualization modes volume render, maximum, minimum, mean, and the surface render. The surface render visualization mode is the most realistic mode among the five modes of visualizing the ultrasound 3D dataset. We enhance the rendered image quality of the surface render mode by enhancing the pre-processing of the 2D ultrasound image. Surface render is subdivided into four major stages, 2D image pre-processing, volume render with surface detection, surface shading and finally post-processing. Surface render mode gives a low rendered image quality because of the speckle noise nature of the ultrasound, which is the reason for the coherent nature of the ultrasound imaging. And so, pre-processing of the 2D image is needed to remove the speckle noise keeping and enhancing the surface edges. Our processing meets the Three major challenges which must be concerned when designing the pre-processing of the 2D ultrasound image. Firstly, robustly smooth the speckle noise. Secondly, preserves and enhances the organs edges. and finally, the time constrains must be met that is because of this processing is part of many intensive processing stages. in addition, the processing implemented on the current GPUs platform, which shows a very high processing power with significant low coast value. A recent review of the literature, on this topic found that, a vast publication in the area of the 4D rendering pipeline [1] and 2D image enhancement each separately, despite this interest, no one to the best of our knowledge has studied the suitable 2D image pre-processing to get the best 4D data visualization [2], considering the nature of the ultrasound image [3] and the time constrains of the ultrasound physics. Our processing is a merge between local statistics and non-linear filters. It guarantees the required suitable quality of the 2D ultrasound image and performance constrains.
Research Interests:
Research Interests:
Ultrasound (US) image quality is degraded due to many artifacts, speckle noise is the major one due to the coherent nature of sound wave. Many spatial and compounding image enhancement techniques are proposed. professional sonographers... more
Ultrasound (US) image quality is degraded due to many artifacts, speckle noise is the major one due to the coherent nature of sound wave. Many spatial and compounding image enhancement techniques are proposed. professional sonographers carefully use the image enhancement due to the loses of diagnostic details. Compound enhancement is proposed to enhance the image quality keeping enough texture details for diagnosis [1]. Many compounding methods are proposed frequency compounding, spatial compounding and motion compounding also.This paper uses the motion compounding to despeckle the ultrasound images. The speckle pattern will be decorrelated due to slightly moving the US probe or the organ being imaged. Direct image compounding of the US images will deform the tissue and blur the image. therefore, motion estimation and compensation must be take place before compounding.Optimized adaptive Rood Pattern search (O-ARPS) is proposed based on the original ARPS [2], ARPS is commonly used in video compression. O-ARPS Optimized for the ultrasound images and multicore processing platform.Experimental in vivo frames show that the speckle noise is significantly reduced without degrade the organs boundary, also better image perception achieved due to keeping a few texture details with Timing Performance close to be real time.
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Ultrasound (US) image quality is degraded due to many artifacts, speckle noise is the major one due to the coherent nature of sound wave. Many spatial and compounding image enhancement techniques are proposed. professional sonographers... more
Ultrasound (US) image quality is degraded due to many artifacts, speckle noise is the major one due to the coherent nature of sound wave. Many spatial and compounding image enhancement techniques are proposed. professional sonographers carefully use the image enhancement due to the loses of diagnostic details. Compound enhancement is proposed to enhance the image quality keeping enough texture details for diagnosis [1]. Many compounding methods are proposed frequency compounding, spatial compounding and motion compounding also.This paper uses the motion compounding to despeckle the ultrasound images. The speckle pattern will be decorrelated due to slightly moving the US probe or the organ being imaged. Direct image compounding of the US images will deform the tissue and blur the image. therefore, motion estimation and compensation must be take place before compounding.Optimized adaptive Rood Pattern search (O-ARPS) is proposed based on the original ARPS [2], ARPS is commonly used in video compression. O-ARPS Optimized for the ultrasound images and multicore processing platform.Experimental in vivo frames show that the speckle noise is significantly reduced without degrade the organs boundary, also better image perception achieved due to keeping a few texture details with Timing Performance close to be real time.
Research Interests:
Research Interests:
Pulsed wave Doppler ultrasound is commonly used in the diagnosis of cardiovascular and blood flow abnormalities. Doppler techniques have gained clinical significance due to its safety, real-time performance and affordability. This work... more
Pulsed wave Doppler ultrasound is commonly used in the diagnosis of cardiovascular and blood flow abnormalities. Doppler techniques have gained clinical significance due to its safety, real-time performance and affordability. This work presents the development of a pulsed wave spectral Doppler module, which was integrated into a reconfigurable ultrasound system. The targeted system adopts a hardware-software partitioning scheme where an FPGA handles the front-end and a PC performs the back-end. Two factors were considered during the design. First, the data transfer rate between hardware and software should be minimum. Second, the design should use as few of the FPGA resources as possible. Accordingly, the processing was divided after the range gate integration where the data rate drops significantly. In addition, a quadrature demodulator was used based on a switching mixer and a cascaded integrator comb filter. The design was implemented and integrated into the targeted system. The system was tested using a string phantom and on human volunteers. The results showed that this simple design could achieve performance comparable to designs that are more sophisticated. However, it is limited by the number of available frequencies. Hence, it is suitable for systems with limited resources such as handheld systems.
Research Interests:
Research Interests:
4D ultrasound is one of the most advancing visualization techniques of the ultrasound dataset. it is subdivided into main five visualization modes volume render, maximum, minimum, mean, and the surface render. The surface render... more
4D ultrasound is one of the most advancing visualization techniques of the ultrasound dataset. it is subdivided into main five visualization modes volume render, maximum, minimum, mean, and the surface render. The surface render visualization mode is the most realistic mode among the five modes of visualizing the ultrasound 3D dataset. We enhance the rendered image quality of the surface render mode by enhancing the pre-processing of the 2D ultrasound image. Surface render is subdivided into four major stages, 2D image pre-processing, volume render with surface detection, surface shading and finally post-processing. Surface render mode gives a low rendered image quality because of the speckle noise nature of the ultrasound, which is the reason for the coherent nature of the ultrasound imaging. And so, pre-processing of the 2D image is needed to remove the speckle noise keeping and enhancing the surface edges. Our processing meets the Three major challenges which must be concerned when designing the pre-processing of the 2D ultrasound image. Firstly, robustly smooth the speckle noise. Secondly, preserves and enhances the organs edges. and finally, the time constrains must be met that is because of this processing is part of many intensive processing stages. in addition, the processing implemented on the current GPUs platform, which shows a very high processing power with significant low coast value. A recent review of the literature, on this topic found that, a vast publication in the area of the 4D rendering pipeline [1] and 2D image enhancement each separately, despite this interest, no one to the best of our knowledge has studied the suitable 2D image pre-processing to get the best 4D data visualization [2], considering the nature of the ultrasound image [3] and the time constrains of the ultrasound physics. Our processing is a merge between local statistics and non-linear filters. It guarantees the required suitable quality of the 2D ultrasound image and performance constrains.
Ultrasound (US) image quality is degraded due to many artifacts, speckle noise is the major one due to the coherent nature of sound wave. Many spatial and compounding image enhancement techniques are proposed. professional sonographers... more
Ultrasound (US) image quality is degraded due to many artifacts, speckle noise is the major one due to the coherent nature of sound wave. Many spatial and compounding image enhancement techniques are proposed. professional sonographers carefully use the image enhancement due to the loses of diagnostic details. Compound enhancement is proposed to enhance the image quality keeping enough texture details for diagnosis [1]. Many compounding methods are proposed frequency compounding, spatial compounding and motion compounding also.This paper uses the motion compounding to despeckle the ultrasound images. The speckle pattern will be decorrelated due to slightly moving the US probe or the organ being imaged. Direct image compounding of the US images will deform the tissue and blur the image. therefore, motion estimation and compensation must be take place before compounding.Optimized adaptive Rood Pattern search (O-ARPS) is proposed based on the original ARPS [2], ARPS is commonly used in...
Four-dimensional (4D) ultrasound imaging extends the real-time capability of ultrasound to visualize a real-time volume that can be manipulated by the sonographer. Among the different visualization methods, surface rendering is a common... more
Four-dimensional (4D) ultrasound imaging extends the real-time capability of ultrasound to visualize a real-time volume that can be manipulated by the sonographer. Among the different visualization methods, surface rendering is a common mode for displaying volumetric datasets such as in obstetrical applications. A challenge in this mode is that surface shading is required to visualize the surface and enhances the surface contrast and this has very demanding computational requirements for 3D surfaces. Here, we present an optimized high-performance rendering pipeline based on four stages for preprocessing, volume rendering, surface shading, and postprocessing. The new approach is implemented to render volumes acquired on a 4D commercial ultrasound imaging system to illustrate its practicality. The results demonstrate diagnostic quality of rendered volumes at a computational time cost that is suitable for 4D real-time processing. Given its low cost of required hardware, the new pipeline has potential for making 4D imaging systems more affordable while maintaining diagnostic quality and performance.
Research Interests:
—4D ultrasound imaging extends the real-time capability of ultrasound to display a real-time volume, which can then be explored by the sonographer. Surface Rendering is one of the common modes used to display the 3D datasets. Surface... more
—4D ultrasound imaging extends the real-time capability of ultrasound to display a real-time volume, which can then be explored by the sonographer. Surface Rendering is one of the common modes used to display the 3D datasets. Surface shading is required to visualize the surface and enhances the surface contrast. Here, we show a surface rendering implementation based on three passes. In the first pass, ray casting is used with edge detection algorithm and then the edges are stored to viewing plan distance in the z-buffer of the 2D rendered image. In the second pass, filtration of the z-buffer is performed. This stage is so critical because the fuzzy nature of the ultrasound dataset then shade the 2D rendered image using image space shading. Finally, the third pass applies additional image processing mainly image smoothing on the rendered 2D image. The new method is applied to render volumes acquired on a research system and quality and computation time results show potential for clinical utility.
Research Interests:
Due to the required computational effort of 4D ultrasound imaging, such systems depend on low complexity techniques like nearest neighbor interpolation, which affects volume quality. Moreover, more accurate techniques like normalized... more
Due to the required computational effort of 4D ultrasound imaging, such systems depend on low complexity techniques like nearest neighbor interpolation, which affects volume quality. Moreover, more accurate techniques like normalized convolution, backward trilinear interpolation, and forward spherical and ellipsoidal Gaussian kernel, are avoided in real-time imaging because of the tight reconstruction time. The goal of this work is to utilize recent commercial graphics hardware technology of graphics processing unit (GPU) to speed up the reconstruction time while increasing the quality of displayed volume.
Research Interests: Computer Graphics, Ultrasound Imaging, GPU Computing, GPU based volume rendering, Ultrasound, and 13 moreImage Reconstruction, Real Time Systems, Nearest Neighbor, Opengl, Decode-And-Forward, Interpolation, Volume Rendering, Ray Casting, Texture Mapping, graphic processing unit (GPU), Low Complexity, Gaussian kernel, and IUS
Research Interests:
We propose a new nonparametric technique for clutter rejection. We consider the Doppler data sampled using a sufficiently large dynamic range to allow for the clutter rejection to be implemented on the digital side. The Doppler signal is... more
We propose a new nonparametric technique for clutter rejection. We consider the Doppler data sampled using a sufficiently large dynamic range to allow for the clutter rejection to be implemented on the digital side. The Doppler signal is modeled as the summation of the true velocity signal, a clutter component, and a random noise component. To simplify the analysis, the first two components are assumed as deterministic yet unknown signals. The Doppler data are collected from the sample volume of interest as well as from several sample volumes in its neighborhood. Given that the shape of the clutter component will be similar in all these signals and given its relatively higher magnitude, it is possible to separate this component using principal component analysis (PCA). In particular, the clutter component appears as the first eigenvector (principal component) in PCA. Given this principal component, the projection of the Doppler signal of interest onto this component is removed and the remaining signal is subsequently used to derive the Doppler spectrogram. We describe an efficient implementation methodology that allows the added computational complexity of the new system to be reasonable.