Automating the analysis and cataloging of sky surveys
Advances in knowledge discovery and data mining
MultiMediaMiner: a system prototype for multimedia data mining
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Image mining in IRIS: integrated retinal information system
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Image Mining: Trends and Developments
Journal of Intelligent Information Systems
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
CASCON '98 Proceedings of the 1998 conference of the Centre for Advanced Studies on Collaborative research
Discovering Association Rules Based on Image Content
ADL '99 Proceedings of the IEEE Forum on Research and Technology Advances in Digital Libraries
FARMER: finding interesting rule groups in microarray datasets
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Data & Knowledge Engineering
Improving CBIR using feature extraction based on wavelet transform
Proceedings of the 14th Brazilian Symposium on Multimedia and the Web
Automation of the medical diagnosis process using semantic image interpretation
ADBIS'10 Proceedings of the 14th east European conference on Advances in databases and information systems
Association rule-based feature selection method for Alzheimer's disease diagnosis
Expert Systems with Applications: An International Journal
Inducing and storing generalised evidences using semantic web formalisms
HIKM '12 Proceedings of the Fifth Australasian Workshop on Health Informatics and Knowledge Management - Volume 129
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Image mining is more than just an extension of data mining to image domain but an interdisciplinary endeavor. Very few people have systematically investigated this field. Mining association rules in medical images is an important part in domain-specific application image mining because there are several technical aspects which make this problem challenging. In this paper, we extend the concept of association rule based on object and image in medical images, and propose two algorithms to discover frequent item-sets and mine interesting association rules from medical images. We describe how to incorporate the domain knowledge into the algorithms to enhance the interestingness. Some interesting results are obtained by our program and we believe many of the problems we come across are likely to appear in other domains.