In this paper, we propose a novel approach for estimating image similarity. This measure is of importance in assessing image correspondence or image alignment and plays an important role in image registration. Currently, this problem is approached rather one-dimensionally since most registration methods consider the problem as either mono- or multi-modal. This perspective leads to the selection of some form of either the correlation coefficient (CC) or mutual information (MI) as image similarity measure (ISM). We propose a more generic framework for ISM construction, based on absolute joint moments, which can be considered as a generalization of CC. Within this framework, we propose a specific ISM that provides a different trade-off between...
We address the alignment of a group of images with simultaneous registration. Therefore, we provide ...
Multi-modal image registration is becoming an increasingly powerful tool for medical diagnosis and t...
Image registration is an important topic for many imaging systems and computer vision applications. ...
In this paper, we propose a novel approach for estimating image similarity. This measure is of impor...
Mutual information (MI) is one of the most popular and widely used similarity measures in image regi...
Measures of image similarity that inspect the intensity probability distribution of the images have ...
High-dimensional non-rigid registration of multi-modal data requires similarity measures with two im...
We propose a similarity measure for comparing digital images. The technique is based on mutual info...
Abstract Similarity measures for non-rigid multimodal registration are required to be local in order...
International audienceWe propose a new similarity measure for iconic medical image registration, an ...
In image-guided intervention, 2D/3D medical image registration is crucial to supply the clinician sp...
Mutual information (MI) is a popular entropy-based similarity measure used in the medical imaging fi...
Two new similarity measures for rigid image registration, based on the normalization of Jensen'...
Mutual information (MI) has been widely used as a similarity measure for rigid registration of multi...
Image registration is widely used in different areas, including medical image analysis and image pro...
We address the alignment of a group of images with simultaneous registration. Therefore, we provide ...
Multi-modal image registration is becoming an increasingly powerful tool for medical diagnosis and t...
Image registration is an important topic for many imaging systems and computer vision applications. ...
In this paper, we propose a novel approach for estimating image similarity. This measure is of impor...
Mutual information (MI) is one of the most popular and widely used similarity measures in image regi...
Measures of image similarity that inspect the intensity probability distribution of the images have ...
High-dimensional non-rigid registration of multi-modal data requires similarity measures with two im...
We propose a similarity measure for comparing digital images. The technique is based on mutual info...
Abstract Similarity measures for non-rigid multimodal registration are required to be local in order...
International audienceWe propose a new similarity measure for iconic medical image registration, an ...
In image-guided intervention, 2D/3D medical image registration is crucial to supply the clinician sp...
Mutual information (MI) is a popular entropy-based similarity measure used in the medical imaging fi...
Two new similarity measures for rigid image registration, based on the normalization of Jensen'...
Mutual information (MI) has been widely used as a similarity measure for rigid registration of multi...
Image registration is widely used in different areas, including medical image analysis and image pro...
We address the alignment of a group of images with simultaneous registration. Therefore, we provide ...
Multi-modal image registration is becoming an increasingly powerful tool for medical diagnosis and t...
Image registration is an important topic for many imaging systems and computer vision applications. ...