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Image registration is used extensively in medical imaging. Visual assessment of its quality is time consuming and not necessarily accurate. Automatic estimation of registration accuracy is desired for many clinical applications. Current methods rely on learning a relationship between image features and registration error. In this paper we propose an unsupervised method for the detection of local registration...
Segmentation via atlas registration is a common technique in medical image analysis. Devising estimates of such segmentation outcome has been of interest in cases with multiple atlases, both for single-atlas selection and for multi-atlas fusion. This paper studies the estimation of expected Dice's similarity metric for registering atlas-target pairs, by employing registration loops with models of...
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