Abstract:
: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%.
journal_name
IEEE Trans Med Imagingjournal_title
IEEE transactions on medical imagingauthors
Highnam R,Brady M,English Rdoi
10.1109/42.811313subject
Has Abstractpub_date
1999-10-01 00:00:00pages
1016-24issue
10eissn
0278-0062issn
1558-254Xjournal_volume
18pub_type
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journal_title:IEEE transactions on medical imaging
pub_type: 杂志文章
doi:10.1109/TMI.2003.819293
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journal_title:IEEE transactions on medical imaging
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journal_title:IEEE transactions on medical imaging
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journal_title:IEEE transactions on medical imaging
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journal_title:IEEE transactions on medical imaging
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journal_title:IEEE transactions on medical imaging
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