215 research outputs found

    Post-processing approaches for the improvement of cardiac ultrasound B-mode images:a review

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    A robust detail preserving anisotropic diffusion for speckle reduction in ultrasound images

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    <p>Abstract</p> <p>Background</p> <p>Speckles in ultrasound imaging affect image quality and can make the post-processing difficult. Speckle reduction technologies have been employed for removing speckles for some time. One of the effective speckle reduction technologies is anisotropic diffusion. Anisotropic diffusion technology can remove the speckles effectively while preserving the edges of the image and thus has drawn great attention from image processing scientists. However, the proposed methods in the past have different disadvantages, such as being sensitive to the number of iterations or low capability of preserving the details of the ultrasound images. Thus a detail preserved anisotropic diffusion speckle reduction with less sensitive to the number of iterations is needed. This paper aims to develop this kind of technologies.</p> <p>Results</p> <p>In this paper, we propose a robust detail preserving anisotropic diffusion filter (RDPAD) for speckle reduction. In order to get robust diffusion, the proposed method integrates Tukey error norm function into the detail preserving anisotropic diffusion filter (DPAD) developed recently. The proposed method could prohibit over-diffusion and thus is less sensitive to the number of iterations</p> <p>Conclusions</p> <p>The proposed anisotropic diffusion can preserve the important structure information of the original image while reducing speckles. It is also less sensitive to the number of iterations. Experimental results on real ultrasound images show the effectiveness of the proposed anisotropic diffusion filter.</p

    Speckle Noise Reduction using Local Binary Pattern

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    AbstractA novel local binary pattern (LBP) based adaptive diffusion for speckle noise reduction is presented. The LBP operator unifies traditionally divergent statistical and structural models of region analysis. We use LBP textons to classify an image around a pixel into noisy, homogenous, corner and edge regions. According to different types of regions, a variable weight is assigned in to the diffusion equation, so that our algorithm can adaptively encourage strong diffusion in homogenous/noisy regions and less on the edge/corner regions. The diffusion preserves edges, local details while diffusing more on homogenous region. The experiments results are evaluated both in terms of objective metric and the visual quality

    Disleksi bukan satu penyakit

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    Disleksia bukan satu istilah yang asing dalam masalah pembelajaran. Terdapat banyak sumber yang rancak membincang dan uar-uarkan. maklumat mengenai masalah dan cara menangani disleksia. Merujuk Sheila Devaraj dan Samsilah Roslan (2006), disleksia hanya diperkenalkan secara formal di Malaysia pada tahun 1993 menerusi Seminar Kebangsaan Pengenalan kepada Disleksia yang dianjurkan oleh Rotary Club Gombak. Dalam kajian ini, penyelidik telah mengambil seramai 20 orang kanak-kanak di bawah Persatuan Disleksia Malaysia yang terletak di sekitar Kuala Lumpur sebagai sampel. Dua kaedah digunakan dalam mendapatkan data iaitu secara temu bual dan pemerhatian. Kaedah ini dianggap bersuaian kerana gambaran secara seluruhan dapat dilihat terhadap proses pengajaran dan pembelajaran pelajar-pelajar disleksia. Persoalan kajian ini ialah 1) Apakah ciri-ciri masalah yang ketara yang dihidapi oleh pelajar-pelajar disleksia dalam pembelajaran? dan 2) Apakah langkah-langkah yang belch diambil untuk membantu pelajar-pelajar bagi mengatasi masalah disleksia

    Speckle Noise Reduction in Medical Ultrasound Images

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    Ultrasound imaging is an incontestable vital tool for diagnosis, it provides in non-invasive manner the internal structure of the body to detect eventually diseases or abnormalities tissues. Unfortunately, the presence of speckle noise in these images affects edges and fine details which limit the contrast resolution and make diagnostic more difficult. In this paper, we propose a denoising approach which combines logarithmic transformation and a non linear diffusion tensor. Since speckle noise is multiplicative and nonwhite process, the logarithmic transformation is a reasonable choice to convert signaldependent or pure multiplicative noise to an additive one. The key idea from using diffusion tensor is to adapt the flow diffusion towards the local orientation by applying anisotropic diffusion along the coherent structure direction of interesting features in the image. To illustrate the effective performance of our algorithm, we present some experimental results on synthetically and real echographic images

    Speckle reducing bilateral filter for cattle follicle segmentation

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    <p>Abstract</p> <p>Background</p> <p>Ultrasound imaging technology has wide applications in cattle reproduction and has been used to monitor individual follicles and determine the patterns of follicular development. However, the speckles in ultrasound images affect the post-processing, such as follicle segmentation and finally affect the measurement of the follicles. In order to reduce the effect of speckles, a bilateral filter is developed in this paper.</p> <p>Results</p> <p>We develop a new bilateral filter for speckle reduction in ultrasound images for follicle segmentation and measurement. Different from the previous bilateral filters, the proposed bilateral filter uses normalized difference in the computation of the Gaussian intensity difference. We also present the results of follicle segmentation after speckle reduction. Experimental results on both synthetic images and real ultrasound images demonstrate the effectiveness of the proposed filter.</p> <p>Conclusions</p> <p>Compared with the previous bilateral filters, the proposed bilateral filter can reduce speckles in both high-intensity regions and low intensity regions in ultrasound images. The segmentation of the follicles in the speckle reduced images by the proposed method has higher performance than the segmentation in the original ultrasound image, and the images filtered by Gaussian filter, the conventional bilateral filter respectively.</p
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