IEEE Transactions on Pattern Analysis and Machine Intelligence
Toward Improved Ranking Metrics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Content-based query of image databases: inspirations from text retrieval
Pattern Recognition Letters - Selected papers from the 11th scandinavian conference on image analysis
Empirical evaluation of dissimilarity measures for color and texture
Computer Vision and Image Understanding - Special issue on empirical evaluation of computer vision algorithms
Measuring the performance of shape similarity retrieval methods
Computer Vision and Image Understanding - Special issue on empirical evaluation of computer vision algorithms
Digital Image Compression Techniques
Digital Image Compression Techniques
MEDIMAGE - A Multimedia Database Management System for Alzheimer's Disease Patients
VISUAL '02 Proceedings of the 5th International Conference on Recent Advances in Visual Information Systems
Content-Based and Metadata Retrieval in Medical Image Database
CBMS '02 Proceedings of the 15th IEEE Symposium on Computer-Based Medical Systems (CBMS'02)
Shape-Based Indexing in a Medical Image Database
WBIA '98 Proceedings of the IEEE Workshop on Biomedical Image Analysis
Alignment by maximization of mutual information
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Image segmentation and similarity of color-texture objects
IEEE Transactions on Multimedia
Content-based retrieval of dynamic PET functional images
IEEE Transactions on Information Technology in Biomedicine
Hierarchical color image region segmentation for content-based image retrieval system
IEEE Transactions on Image Processing
Optimization of mutual information for multiresolution image registration
IEEE Transactions on Image Processing
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We propose a similarity measure for comparing digital images. The technique is based on mutual information (MI), which is a measure of the degree of dependence between corresponding pixels in the images being compared. Although MI is widely used as a criterion in image registration, it is often based on image models that fail to take advantage of the spatial correlation between neighbouring pixels in an image. Our approach uses a segment-based model that incorporates the spatial relationship between a pixel and its causal neighbours. We apply the technique in a medical image retrieval problem, where items in a database of brain SPECT scans have to be ranked according to their similarities to a query scan. In our experiments, the resulting similarity ranking correlates well with visual inspection.