Saeed Seyyedi

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Digital breast tomosynthesis (DBT) is an innovative imaging modality that provides 3D reconstructed images of breast to detect the breast cancer. Projections obtained with an X-ray source moving in a limited angle interval are used to reconstruct 3D image of breast. Several reconstruction algorithms are available for DBT imaging. Filtered back projection(More)
We present an object-oriented simulator for 3D digital breast tomosynthesis (DBT) system using C++ programming language. The simulator is capable of implementing different iterative reconstruction and total variation (TV) regularization methods on the real world phantom models. A user friendly graphical user interface (GUI) helps users to select and run the(More)
In tomosynthesis imaging, out-of-focus slice blur problem arises due to incomplete sampling problem. Several approaches have been proposed to deal with this problem. Algebraic reconstruction technique (ART) is one of the most commonly used methods. Total variation (TV) minimization has recently been applied to improve performance of the classical(More)
Reinforcement - Learning methods are widely used in routing problems. These methods interact with the network changes, so are called Adaptive routing methods. Q - Learning algorithms has some quantities which are labeled Q, and are known as headers in routing methods which apply this algorithm. As a result, if we add forward exploration to backward One,(More)
This paper presents a compressed sensing based reconstruction method for 3D digital breast tomosynthesis (DBT) imaging. Algebraic reconstruction technique (ART) has been in use in DBT imaging by minimizing the isotropic total variation (TV) of the reconstructed image. The resolution in DBT differs in sagittal and axial directions which should be encountered(More)
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