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Super-resolution/segmentation of 2D trabecular bone images by a Mumford-Shah approach and comparison to total variation

机译:通过Mumford-Shah方法对2D小梁骨图像进行超分辨率/分割并与总变化进行比较

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The analysis of trabecular bone micro structure from in-vivo CT images is still limited due to insufficient spatial resolution. The goal of this work is to address both the problem of increasing the resolution of the image and of the segmentation of the bone structure. To this aim, we investigate the joint super-resolution/segmentation problem by an approach based on the Mumford-Shah model. The validation of the method is performed on blurred, noisy and down-sampled images. A comparison of the reconstruction results with the Total Variation regularization is showed.
机译:由于空间分辨率不足,从体内CT图像分析小梁骨的微观结构仍然受到限制。这项工作的目的是解决增加图像分辨率和骨骼结构分割的问题。为此,我们通过基于Mumford-Shah模型的方法研究联合的超分辨率/分段问题。该方法的验证是在模糊,嘈杂和下采样的图像上执行的。显示了重建结果与总变化正则化的比较。

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