A study on the computerized fractal analysis of architectural distortion in screening mammograms
- PMID: 16481695
- DOI: 10.1088/0031-9155/51/5/018
A study on the computerized fractal analysis of architectural distortion in screening mammograms
Abstract
Architectural distortion (AD) is a sign of malignancy often missed during mammographic interpretation. The purpose of this study was to explore the application of fractal analysis to the investigation of AD in screening mammograms. The study was performed using mammograms from the Digital Database for Screening Mammography (DDSM). The fractal dimension (FD) of mammographic regions of interest (ROIs) was calculated using the circular average power spectrum technique. Initially, the variability of the FD estimates depending on ROI location, mammographic view and breast side was studied on normal mammograms. Then, the estimated FD was evaluated using receiver operating characteristics (ROC) analysis to determine if it can discriminate ROIs depicting AD from those depicting normal breast parenchyma. The effect of several factors such as ROI size, image subsampling and breast density was studied in detail. Overall, the average FD of the normal ROIs was statistically significantly higher than that of the ROIs with AD. This result was consistent across all factors studied. For the studied set of implementation parameters, the best ROC performance achieved was 0.89 +/- 0.02. The generalizability of these conclusions across different digitizers was also demonstrated.
Similar articles
-
Characterization and classification of tumor lesions using computerized fractal-based texture analysis and support vector machines in digital mammograms.Int J Comput Assist Radiol Surg. 2009 Jan;4(1):11-25. doi: 10.1007/s11548-008-0276-8. Epub 2008 Oct 28. Int J Comput Assist Radiol Surg. 2009. PMID: 20033598
-
A computer-aided detection of the architectural distortion in digital mammograms using the fractal dimension measurements of BEMD.Comput Med Imaging Graph. 2018 Dec;70:173-184. doi: 10.1016/j.compmedimag.2018.04.001. Epub 2018 Apr 3. Comput Med Imaging Graph. 2018. PMID: 29691123
-
A new approach for the detection of architectural distortions using textural analysis of surrounding tissue.Annu Int Conf IEEE Eng Med Biol Soc. 2016 Aug;2016:3965-3968. doi: 10.1109/EMBC.2016.7591595. Annu Int Conf IEEE Eng Med Biol Soc. 2016. PMID: 28269153
-
Computer-aided detection of architectural distortion in prior mammograms of interval cancer.J Digit Imaging. 2010 Oct;23(5):611-31. doi: 10.1007/s10278-009-9257-x. Epub 2010 Feb 2. J Digit Imaging. 2010. PMID: 20127270 Free PMC article.
-
Detection of architectural distortion in prior mammograms of interval-cancer cases with neural networks.Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:6667-70. doi: 10.1109/IEMBS.2009.5334517. Annu Int Conf IEEE Eng Med Biol Soc. 2009. PMID: 19964909
Cited by
-
Characterization and classification of tumor lesions using computerized fractal-based texture analysis and support vector machines in digital mammograms.Int J Comput Assist Radiol Surg. 2009 Jan;4(1):11-25. doi: 10.1007/s11548-008-0276-8. Epub 2008 Oct 28. Int J Comput Assist Radiol Surg. 2009. PMID: 20033598
-
Three-dimensional in silico breast phantoms for multimodal image simulations.IEEE Trans Med Imaging. 2012 Mar;31(3):689-97. doi: 10.1109/TMI.2011.2175401. Epub 2011 Nov 9. IEEE Trans Med Imaging. 2012. PMID: 22084047 Free PMC article.
-
Detection of architectural distortion in prior mammograms via analysis of oriented patterns.J Vis Exp. 2013 Aug 30;(78):50341. doi: 10.3791/50341. J Vis Exp. 2013. PMID: 24022326 Free PMC article.
-
Evaluation of an improved algorithm for producing realistic 3D breast software phantoms: application for mammography.Med Phys. 2010 Nov;37(11):5604-17. doi: 10.1118/1.3491812. Med Phys. 2010. PMID: 21158272 Free PMC article.
-
Characterizing Architectural Distortion in Mammograms by Linear Saliency.J Med Syst. 2017 Feb;41(2):26. doi: 10.1007/s10916-016-0672-5. Epub 2016 Dec 22. J Med Syst. 2017. PMID: 28005248
MeSH terms
LinkOut - more resources
Full Text Sources
Medical