Speckle Noise Reduction in Medical Ultrasound Images

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

Pyramidal flux in an anisotropic diffusion scheme for enhancing structures in 3D images

Pyramid based methods in image processing provide a helpful framework for accelerating the propagation of information over large spatial domains, increasing the efficiency for large scale applications. Combined with an anisotropic diffusion scheme tailored to preserve the boundaries at a given level, an efficient way for enhancing large structures in 3D images is presented. In our approach, the partial differential equation defining the evolution of the intensity in the image is solved in an explicit scheme at multiple resolutions in an ascending-descending cycle. Intensity 'flux' between distant voxels is allowed, while preserving borders relative to the scale. Experiments have been performed both with phantoms and with real data from 3D Transrectal Ultrasound Imaging. The effectiveness of the method to remove speckle noise and to enhance large structures such as the prostate has been demonstrated. For instance, using two scales reduces the computation time by 87% as compared to a single scale. Furthermore, we show that the boundaries of the prostate are mainly preserved, by comparing with manually outlined edges

Curved Gabor Filters for Fingerprint Image Enhancement

Gabor filters play an important role in many application areas for the enhancement of various types of images and the extraction of Gabor features. For the purpose of enhancing curved structures in noisy images, we introduce curved Gabor filters which locally adapt their shape to the direction of flow. These curved Gabor filters enable the choice of filter parameters which increase the smoothing power without creating artifacts in the enhanced image. In this paper, curved Gabor filters are applied to the curved ridge and valley structure of low-quality fingerprint images. First, we combine two orientation field estimation methods in order to obtain a more robust estimation for very noisy images. Next, curved regions are constructed by following the respective local orientation and they are used for estimating the local ridge frequency. Lastly, curved Gabor filters are defined based on curved regions and they are applied for the enhancement of low-quality fingerprint images. Experimental results on the FVC2004 databases show improvements of this approach in comparison to state-of-the-art enhancement methods

NON-INVASIVE IMAGE DENOISING AND CONTRAST ENHANCEMENT TECHNIQUES FOR RETINAL FUNDUS IMAGES

The analysis of retinal vasculature in digital fundus images is important for diagnosing eye related diseases. However, digital colour fundus images suffer from low and varied contrast, and are also affected by noise, requiring the use of fundus angiogram modality. The Fundus Fluorescein Angiogram (FFA) modality gives 5 to 6 time’s higher contrast. However, FFA is an invasive method that requires contrast agents to be injected and this can lead other physiological problems. A reported digital image enhancement technique named RETICA that combines Retinex and ICA (Independent Component Analysis) techniques, reduces varied contrast, and enhances the low contrast blood vessels of model fundus images

Speckle reducing bilateral filter for cattle follicle segmentation

<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