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Microcalcifications can be one of the earliest signs of breast cancer. Unfortunately, their appearance in mammograms can be mimicked by dust and dirt entering the imaging process and this has been shown previously to lead to false positives. We use a model of the imaging process and, in particular, the blurring functions inherent within it to detect the film-screen artifacts caused by dust and dirt and, thus, reduce false-positives. A crucial facet of the work is the choice of the correct image representation upon which to perform the image processing. After extensive testing, our algorithm has identified no microcalcifications as being artifacts and has an artifact detection rate of approaching 96%.

Original publication

DOI

10.1109/42.811313

Type

Journal article

Journal

IEEE Trans Med Imaging

Publication Date

10/1999

Volume

18

Pages

1016 - 1024

Keywords

Algorithms, Artifacts, Breast Neoplasms, Calcinosis, Dust, False Positive Reactions, Female, Humans, Mammography, Models, Biological, Phantoms, Imaging, X-Ray Intensifying Screens