Affiliation:
1. Ching Yun University, Taiwan
2. University of Warwick, UK
Abstract
As distributed mammogram databases at hospitals and breast screening centers are connected together through PACS, a mammogram retrieval system is needed to help medical professionals locate the mammograms they want to aid in medical diagnosis. This chapter presents a complete content-based mammogram retrieval system, seeking images that are pathologically similar to a given example. In the mammogram retrieval system, the pathological characteristics that have been defined in Breast Imaging Reporting and Data System (BI-RADSTM) are used as criteria to measure the similarity of the mammograms. A detailed description of those mammographic features is provided in this chapter. Since the user’s subjective perception should be taken into account in the image retrieval task, a relevance feedback function is also developed to learn individual users’ knowledge to improve the system performance.
Cited by
2 articles.
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1. Artificial Intelligence;Handbook of Research on Manufacturing Process Modeling and Optimization Strategies;2017
2. Mammogram retrieval through machine learning within BI-RADS standards;Journal of Biomedical Informatics;2011-08