Proceedings Article10.1109/RELABIRA.2012.6235102
Breast segmentation using k-means algorithm with a mixture of gamma distributions
Abdu Gumaei,Ali El-Zaart,Muhamad Hussien,M.A. Berbar +3 more
- 28 May 2012
- pp 97-102
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TL;DR: Exploiting Gamma distribution for modeling the k-mean method, an efficient technique for the segmentation of mammograms showed improvement in the accuracy of breast segmentation for breast cancer detection.
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Abstract: Breast cancer is one of the main causes of death among women worldwide. Mammography is an effective imaging modality for early diagnosis of breast cancer. Understanding the nature of data in breast images is very important for developing a model that fits well the data. Gaussian distribution is widely used for modeling the data in breast images but due to the asymmetric nature of the distribution of gray levels in mammogram, Gamma distribution is more suitable. Exploiting Gamma distribution for modeling the k-mean method, we developed an efficient technique for the segmentation of mammograms. The approach was tested over several images taken from mini-MIAS (Mammogram Image Analysis Society, UK) database. The experimental results on mammogram images using this technique showed improvement in the accuracy of breast segmentation for breast cancer detection.
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TL;DR: The results from the tests confirm the effectiveness of the proposed method the determination number of clusters and detected of Regions of interest's (ROIs) in mammography images.
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TL;DR: The paper introduces the contrast sort methods, and introduces mainly the contrast limited adaptive histogram equalization, which enhance range by confining the height of local histogram, so limit noise magnification.
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Automatic Detection of Microcalcification in Mammograms– A Review
Kaja Mohideen
- 01 Jan 2005
TL;DR: The methods of automatic detection of microcalcifications in digitized mammograms used in various stages of the Computer Aided Detection systems (CAD) are summarized and compared.
77
Mammogram screening using multiresolution-based image segmentation
D. Brzakovic,M. Neskovic +1 more
TL;DR: In this article, a hierarchical region growing (HRG) method is proposed to detect cancerous changes in mammograms and can potentially aid medical experts in establishing the diagnosis of malignant nodules.
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