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-RADS TM) 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.
Original language | English |
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Title of host publication | Artificial Intelligence for Maximizing Content Based Image Retrieval |
Publisher | IGI Global |
Pages | 315-341 |
Number of pages | 27 |
ISBN (Print) | 9781605661742 |
DOIs | |
Publication status | Published - 2009 |