12 May 1995 New model and algorithm for restoring medical ultrasound rf images
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Observed medical ultrasound radio-frequency (rf) images are blurred and noisy representations of the true tissue reflectance. The blurring of the specular reflections that occur at boundaries between regions of different tissue types is particularly troublesome, and it is difficult to remove with standard restoration techniques such as Wiener filtering. In this paper we develop an iterative restoration/segmentation algorithm for 2-D ultrasound rf images, that is based on a new statistical image model incorporating spatial smoothness constraints and a physically accurate model for edge reflections. The algorithm alternates steps of restoration and segmentation, calculated using simulated annealing, and includes estimation of reflectance parameters. The smoothness constraints serve to regularize the overall procedure, and the edge reflection model allows the algorithm to use the specular reflections to help locate region boundaries. The resulting restorations of some simulated and real rf-images are significantly better than those produced by Wiener filtering.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jorn H. Hokland, Jorn H. Hokland, Patrick A. Kelly, Patrick A. Kelly, } "New model and algorithm for restoring medical ultrasound rf images", Proc. SPIE 2434, Medical Imaging 1995: Image Processing, (12 May 1995); doi: 10.1117/12.208738; https://doi.org/10.1117/12.208738

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