A review of automatic mass detection and segmentation in mammographic images.
review · Level V
Where this comes from
- Record sourced from PubMed, PMID 20071209.
- Also identified by DOI 10.1016/j.media.2009.12.005.
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Abstract
The aim of this paper is to review existing approaches to the automatic detection and segmentation of masses in mammographic images, highlighting the key-points and main differences between the used strategies. The key objective is to point out the advantages and disadvantages of the various approaches. In contrast with other reviews which only describe and compare different approaches qualitatively, this review also provides a quantitative comparison. The performance of seven mass detection methods is compared using two different mammographic databases: a public digitised database and a local full-field digital database. The results are given in terms of Receiver Operating Characteristic (ROC) and Free-response Receiver Operating Characteristic (FROC) analysis.
Medical subject headings
- Algorithms
- Artificial Intelligence
- Breast Neoplasms
- Mammography
- Pattern Recognition, Automated
- Radiographic Image Enhancement
- Radiographic Image Interpretation, Computer-Assisted