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2016

Image Registration Based on Autocorrelation of Local Structure

4 years 3 months ago
Image Registration Based on Autocorrelation of Local Structure
—Registration of images in the presence of intra-image signal fluctuations is a challenging task. The definition of an appropriate objective function measuring the similarity between the images is crucial for accurate registration. This paper introduces an objective function that embeds local phase features derived from the monogenic signal in the modality independent neighborhood descriptor (MIND). The image similarity relies on the autocorrelation of local structure (ALOST) which has two important properties: 1) low sensitivity to space-variant intensity distortions (e.g., differences in contrast enhancement in MRI); 2) high distinctiveness for ‘salient’ image features such as edges. The ALOST method is quantitatively compared to the MIND approach based on three different datasets: thoracic CT images, synthetic and real abdominal MR images. The proposed method outperformed the NMI and MIND similarity measures on these three datasets. The registration of dynamic contrast enhan...
Zhang Li, Dwarikanath Mahapatra, Jeroen A. W. Tiel
Added 11 Apr 2016
Updated 11 Apr 2016
Type Journal
Year 2016
Where TMI
Authors Zhang Li, Dwarikanath Mahapatra, Jeroen A. W. Tielbeek, Jaap Stoker, Lucas J. van Vliet, Frans M. Vos
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