Temporally-Dependent Image Similarity Measure for Longitudinal Analysis
نویسندگان
چکیده
Current longitudinal image registration methods rely on the assumption that image appearance between time-points remains constant or changes uniformly within intensity classes. This assumption, however, is not valid for magnetic resonance imaging of brain development. Registration methods developed to align images with non-uniform appearance change either (i) locally minimize some global similarity measure, or (ii) iteratively estimate an intensity transformation that makes the images similar. However, these methods treat the individual images as independent static samples and are inadequate for the strong nonuniform appearance changes seen in neurodevelopmental data. Here, we propose a model-based similarity measure intended for aligning longitudinal images that locally estimates a temporal model of intensity change. Unlike previous approaches, the model-based formulation is able to capture complex appearance changes between time-points and we demonstrate that it is critical when using a deformable transformation model.
منابع مشابه
A Novel Image Structural Similarity Index Considering Image Content Detectability Using Maximally Stable Extremal Region Descriptor
The image content detectability and image structure preservation are closely related concepts with undeniable role in image quality assessment. However, the most attention of image quality studies has been paid to image structure evaluation, few of them focused on image content detectability. Examining the image structure was firstly introduced and assessed in Structural SIMilarity (SSIM) measu...
متن کاملEvaluation of Similarity Measures for Template Matching
Image matching is a critical process in various photogrammetry, computer vision and remote sensing applications such as image registration, 3D model reconstruction, change detection, image fusion, pattern recognition, autonomous navigation, and digital elevation model (DEM) generation and orientation. The primary goal of the image matching process is to establish the correspondence between two ...
متن کاملImproving the quality of images synthesized by discrete cosines transform – regression based method using principle component analysis
Purpose: Different views of an individuals’ image may be required for proper face recognition. Recently, discrete cosines transform (DCT) based method has been used to synthesize virtual views of an image using only one frontal image. In this work the performance of two different algorithms was examined to produce virtual views of one frontal image. Materials and Methods: Two new meth...
متن کاملLongitudinal Image Registration with Non-uniform Appearance Change
Longitudinal imaging studies are frequently used to investigate temporal changes in brain morphology. Image intensity may also change over time, for example when studying brain maturation. However, such intensity changes are not accounted for in image similarity measures for standard image registration methods. Hence, (i) local similarity measures, (ii) methods estimating intensity transformati...
متن کاملA new similarity measure between type-2 fuzzy numbers and fuzzy risk analysis
In this paper, we present a revised similarity measure based onChen-and-Chen's similarity measure for fuzzy risk analysis. The revisedsimilarity measure uses the corrected formulae to calculate the centre ofgravity points, therefore it is more effective than the Chen-and-Chen'smethod. The revised similarity measure can overcome the drawbacks of theexisting methods. We have also proposed a new ...
متن کامل