Quantifying the resolution of a template after image registration

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Authors: Matthias Glock, Thomas K. Hotz
Cited by: 0
References: 25

Abstract

Abstract In many image processing applications (e.g. computational anatomy) a groupwise registration is performed on a sample of images and a template image is simultaneously generated. From the template alone it is in general unclear to which extent the registered images are still misaligned. The local spatial variation left after registration may be seen as the resolution of the resulting template. In this sense we develop the first template resolution measure (TRM) quantifying the misalignment at each location of the template. The TRM is based on the key insight that the size of such misalignments can be determined as the amount of smoothing required to bring the registered images in agreement. This relationship is mathematically derived from characteristic examples in one dimension. This way, the TRM quantifies the remaining spatial variation in the template’s units of length. Furthermore we propose to enhance the template by an effective visualization of its resolution measure. Finally we demonstrate the TRM’s applicability and validate its interpretability for example datasets in two and three dimensions. The corresponding code is publicly available on GitHub.

Fields of Study & Subjects

Medical Image Segmentation Techniques Image and Object Detection Techniques Industrial Vision Systems and Defect Detection

Publication details

Journal / source
Pattern Analysis and Applications
Publisher
Springer Science and Business Media LLC
Volume
29
Issue
2
Publication date
25 April 2026
Language
EN