Peyman Rahmati

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We present a computer-aided approach to segmenting suspicious lesions in digital mammograms, based on a novel maximum likelihood active contour model using level sets (MLACMLS). The algorithm estimates the segmentation contour that best separates the lesion from the background using the Gamma distribution to model the intensity of both regions (foreground(More)
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 contrast-limited adaptive histogram equalization (CLAHE) to remove noise and intensity inhomogeneities. The proposed preprocessing filter, called fuzzy contrast-limited adaptive(More)
A major challenge for E-commerce and contentbased businesses is the possibility of altering identity documents or other digital data. This paper shows a watermark-based approach to protect digital identity documents against a PrintScan (PS) attack. We propose a secure ID card authentication system based on watermarking. For authentication purposes, a(More)
We show the first clinical results using the level-set-based reconstruction algorithm for electrical impedance tomography (EIT) data. The level-set-based reconstruction method (LSRM) allows the reconstruction of non-smooth interfaces between image regions, which are typically smoothed by traditional voxel-based reconstruction methods (VBRMs). We develop a(More)
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 of the statistics of the inner and the outer regions (defined by the contour). The Poisson distribution that has been deemed in the past adequate for modeling mammograms is applied(More)
We show that electrical impedance tomography (EIT) image reconstruction algorithms based on the Level Set (LS) method are suitable for real data, which is breathing data in our application. The LS based reconstruction method (LSRM) helps track fast topologically changing interfaces, which are typically smoothed by traditional voxel based reconstruction(More)
Breast cancer is ranked second among the leading causes of death affecting females. Statistics have shown that one out of eight (12 %) women are affected by breast cancer in their lifetime. Mammography is the most effective strategy for breast cancer screening and can be used for the early detection of masses or abnormalities. Small clusters of micro(More)
We present a readily portable, memory-efficient performance test system (PTS) for Tasers. The proposed PTS has been de-velopped for the most widely used Conducted Energy Weapons (CEW), Taser X26. The PTS is designed in accordance with the CEW Test Procedure, recently adopted and published by a group of experts. This work is an advancement of our earlier(More)
The common Level set based reconstruction method (LSRM) is applied to solve a piecewise constant inverse problem using one level set function and considers two different conductivity quantities for the background and the inclusion (two phases inclusion). The more the number of the piecewise constant conductivities in the medium, the higher the calculation(More)
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