Reference Hub2
Content-Based Retrieval for Mammograms

Content-Based Retrieval for Mammograms

Chia-Hung Wei, Chang-Tsun Li, Yue Li
ISBN13: 9781605661742|ISBN10: 1605661740|EISBN13: 9781605661759
DOI: 10.4018/978-1-60566-174-2.ch014
Cite Chapter Cite Chapter

MLA

Wei, Chia-Hung, et al. "Content-Based Retrieval for Mammograms." Artificial Intelligence for Maximizing Content Based Image Retrieval, edited by Zongmin Ma, IGI Global, 2009, pp. 315-341. https://doi.org/10.4018/978-1-60566-174-2.ch014

APA

Wei, C., Li, C., & Li, Y. (2009). Content-Based Retrieval for Mammograms. In Z. Ma (Ed.), Artificial Intelligence for Maximizing Content Based Image Retrieval (pp. 315-341). IGI Global. https://doi.org/10.4018/978-1-60566-174-2.ch014

Chicago

Wei, Chia-Hung, Chang-Tsun Li, and Yue Li. "Content-Based Retrieval for Mammograms." In Artificial Intelligence for Maximizing Content Based Image Retrieval, edited by Zongmin Ma, 315-341. Hershey, PA: IGI Global, 2009. https://doi.org/10.4018/978-1-60566-174-2.ch014

Export Reference

Mendeley
Favorite

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.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.