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Part of book or chapter of book
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Image and Vision Computing
Article . 1992 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
https://doi.org/10.5244/c.5.33...
Article . 1991 . Peer-reviewed
Data sources: Crossref
https://doi.org/10.1007/978-1-...
Part of book or chapter of book . 1991 . Peer-reviewed
Data sources: Crossref
DBLP
Conference object
Data sources: DBLP
DBLP
Article . 1992
Data sources: DBLP
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Classification of Breast Tissue by Texture Analysis

Authors: Peter I. Miller; Susan M. Astley;

Classification of Breast Tissue by Texture Analysis

Abstract

The identification of glandular tissue in breast X-rays (mammograms) is important both in assessing asymmetry between left and right breasts, and in estimating the radiation risk associated with mammographic screening. The appearance of glandular tissue in mammograms is highly variable, ranging from sparse streaks to dense blobs. Fatty regions are generally smooth and dark. Texture analysis provides a flexible approach to discriminating between glandular and fatty regions. We have performed a series of experiments investigating the use of granulometry and texture energy to classify breast tissue. Results of automatic classifications have been compared with a consensus annotation provided by two expert breast radiologists. On a set of 40 mammograms, a correct classification rate of 80% has been achieved using texture energy analysis.

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    103
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
103
Top 10%
Top 1%
Average
bronze