Abstract
This paper proposes a method for detection of abnormalities in mammograms that could be integrated into a computer-aided diagnosis system. The method is based on segmentation using a clustering method, elimination of small regions, blobs and contour detection and a density analysis. The method was tested on images from screening mammography databases and the results are compared with the selections realized by specialists. The tests show that the method offers good results on images that present well defined abnormalities and by adjusting some parameters it can even detect distortions difficult to be noticed by physicians.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Breast Cancer Statistics (2016), http://www.breastcancer.org,
Yadollahpour A, Shoghi H, (2015), Early Breast Cancer Detection using Mammogram Images: A Review of Image Processing Techniques, Biosciences Biotechnology Research Asia, Vol. 12, pp. 225-234
Zheng L, A.K. Chan (2001), IEEE Trans. Med. Imaging 20, 559
Li H., Shih-Chung B L, Wang Z, Kinnand L, Freedman M T, (2002), IEEE Trans. Med. Imaging 21, 139
Chan H P, Petrick N, Sahiner B, (2000) Computer-aided breast cancer diagnosis, in Artificial Intelligence Techniques in Breast Cancer Diagnosis and Prognosis, Series in Machine Perception and Artificial Intelligence, vol. 39 (World Scientific Publishing Co. Pte. Ltd., Singapore, pp. 179–264
Guzmán-Cabrera R, Guzmán-Sepúlveda J R, Torres-Cisneros M, May-Arrioja D. A., et al., (2013), Digital Image Processing Technique for Breast Cancer Detection, Int J Thermophys 34:1519–1531
Mussarat Y, Muhammad S, Sajjad M, (2013), Survey Paper on Diagnosis of Breast Cancer Using Image Processing Techniques, Research Journal of Recent Sciences, Vol. 2(10), 88-98
Mazurowski M A, Lo J Y, Harrawood B P, Tourassi G D, (2011) Mutual information-based template matching scheme for detection of breast masses: from mammography to digital breast tomosynthesis, J Biomed Inform, 44(5): 815–823
Ramani R., Suthanthira Vanitha N., Valarmathy S., (2013), The Pre-Processing Techniques for Breast Cancer Detection in Mammography Images, I.J. Image, Graphics and Signal Processing 5, pp. 47-54
Shrestha S, (2014), Image Denoising Using New Adaptive Based Median Filter, Signal & Image Processing (SIPIJ), Vol.5, No.4, 2014
Kanungo T, Mount D M, Netanyahu N S, et al. (2000), An Efficient k-Means Clustering Algorithm: Analysis and Implementation, Proceedings of the Sixteenth ACM Symposium on Computational Geometry, June 2000, pp. 100-109
OpenCV Common Interfaces of Feature Detectors (2016), http://docs.opencv.org/2.4/modules/features2d/doc/common_interfaces_of_feature_detectors.html
Wibmer A., Hricak H, Gondo T, Matsumoto K, et al., (2015), Haralick texture analysis of prostate MRI: utility for differentiating non-cancerous prostate from prostate cancer and differentiating prostate cancers with different Gleason scores, Eur Radiol. 2015 Oct; 25(10):2840-50.
DDSM (2016),http://marathon.csee.usf.edu/Mammography/Database.html
MIAS (2016), http://peipa.essex.ac.uk/info/mias.html
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Chiorean, L.D., Vaida, M.F., Striletchi, C. (2017). Abnormalities Identification in Mammograms. In: Vlad, S., Roman, N. (eds) International Conference on Advancements of Medicine and Health Care through Technology; 12th - 15th October 2016, Cluj-Napoca, Romania. IFMBE Proceedings, vol 59. Springer, Cham. https://doi.org/10.1007/978-3-319-52875-5_44
Download citation
DOI: https://doi.org/10.1007/978-3-319-52875-5_44
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-52874-8
Online ISBN: 978-3-319-52875-5
eBook Packages: EngineeringEngineering (R0)