Loading…

Detection of stellate distortions in mammograms

Malignant densities in mammograms have an irregular appearance and frequently are surrounded by a radiating pattern of linear spicules. In this paper a method is described to detect such stellate patterns. This method is based on statistical analysis of a map of pixel orientations. If an increase of...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on medical imaging 1996-10, Vol.15 (5), p.611-619
Main Authors: Karssemeijer, N., te Brake, G.M.
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Malignant densities in mammograms have an irregular appearance and frequently are surrounded by a radiating pattern of linear spicules. In this paper a method is described to detect such stellate patterns. This method is based on statistical analysis of a map of pixel orientations. If an increase of pixels pointing to a region is found, this region is marked as suspicious, especially if such an increase is found in many directions. Orientations of the image intensity map are determined at each pixel using a multiscale approach. At a given scale, accurate line-based orientation estimates are obtained from the output of three-directional, second-order, Gaussian derivative operators. The orientation at the scale at which these operators have maximum response is selected. If a line-like structure is present at a given site, this method provides an estimate of the orientation of this structure, whereas in other cases the image noise will generate a random orientation. The pixel orientation map is used to construct two operators which are sensitive to radial patterns of straight lines. Combination of the output of these operators using a classifier allows for detection of stellate patterns. Different classification methods have been compared and results obtained on a common database are presented. Around 90% of the malignant cases were detected at rate of one false positive (FP) per image.
ISSN:0278-0062
1558-254X
DOI:10.1109/42.538938