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ICISP
2010
Springer
15 years 2 months ago
A New Preprocessing Filter for Digital Mammograms
This paper presents a computer-aided approach to enhancing suspicious lesions in digital mammograms. The developed algorithm improves on a well-known preprocessor filter named cont...
Peyman Rahmati, Ghassan Hamarneh, Doron Nussbaum, ...
CVPR
2006
IEEE
15 years 11 months ago
Modeling and Classifying Breast Tissue Density in Mammograms
We present a new approach to model and classify breast parenchymal tissue. Given a mammogram, first, we will discover the distribution of the different tissue densities in an unsu...
Anna Bosch, Arnau Oliver, Joan Martí, Xavie...

Publication
204views
14 years 6 months ago
Maximum Likelihood Active Contours Specialized for Mammography Segmentation
We present a region-based active contour approach to segmenting masses in digital mammograms. The algorithm developed in a Maximum Likelihood approach is based on the calculation o...
Peyman Rahmati, A. Ayatollahi
ICIP
2003
IEEE
15 years 11 months ago
Unsupervised Bayesian image segmentation using wavelet-domain hidden Markov models
In this paper, we study unsupervised image segmentation using wavelet-domain hidden Markov models (HMMs). We first review recent supervised Bayesian image segmentation algorithms ...
X. Song, G. Fan
73
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ISBI
2002
IEEE
15 years 10 months ago
Automatic segmentation of mammographic masses using fuzzy shadow and maximum-likelihood analysis
This study attempted to accurately segment tumors in mammograms. Although this task is considered to be a preprocessing step in a computer analysis program, it plays an important ...
Lisa Kinnard, Shih-Chung Ben Lo, Paul C. Wang, Mat...