Skip to Main content Skip to Navigation
Journal articles

A Biologically Inspired Algorithm for Microcalcification Cluster Detection

Abstract : The early detection of breast cancer greatly improves prognosis. One of the earliest signs of cancer is the formation of clusters of microcalcifications. We introduce a novel method for microcalcification detection based on a biologically inspired adaptive model of contrast detection. This model is used in conjunction with image filtering based on anisotropic diffusion and curvilinear structure removal using local energy and phase congruency. An important practical issue in automatic detection methods is the selection of parameters: we show that the parameter values for our algorithm can be estimated automatically from the image. This way, the method is made robust and essentially free of parameter tuning. We report results on mammograms from two databases and show that the detection performance can be improved by first including a normalisation scheme.
Complete list of metadata

Cited literature [35 references]  Display  Hide  Download

https://hal.inria.fr/inria-00614995
Contributor : Project-Team Asclepios <>
Submitted on : Wednesday, August 17, 2011 - 9:11:50 PM
Last modification on : Friday, November 13, 2020 - 1:42:04 PM
Long-term archiving on: : Friday, November 25, 2011 - 11:25:33 AM

File

Linguraru_MEDIA_2006.pdf
Files produced by the author(s)

Identifiers

Collections

Citation

Marius George Linguraru, Kostas Marias, Ruth English, Michael Brady. A Biologically Inspired Algorithm for Microcalcification Cluster Detection. Medical Image Analysis, Elsevier, 2006, 10 (6), pp.850-862. ⟨10.1016/j.media.2006.07.004⟩. ⟨inria-00614995⟩

Share

Metrics

Record views

210

Files downloads

795