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3D image reconstruction with electron tomography holds problems due to the severely limited range of projection angles and low signal to noise ratio of the acquired projection images. The maximum a posteriori (MAP) reconstruction methods have been successful in compensating for the missing information and suppressing noise with their intrinsic regularization techniques. There are two major problems...
High density objects in the field of view (FOV) cause artifacts in medical imaging. In X-ray computed tomography (CT), there are several ways to eliminate the effects of these artifacts. This paper aims to evaluate the performance of a novel reconstruction algorithm which accurately segments the metallic regions and reconstruct sharp metal/tissue boundaries, while reducing the artifacts around the...
In the single particle reconstruction, the initial 3D structure often suffers from the limited angular sampling artifact. Selecting 2D class averages of particle images generally improves the accuracy and efficiency of the reference-free 3D angle estimation, but causes an insufficient angular sampling to fill the information of the target object in the 3D frequency space. Similarly, the initial 3D...
In this study, a Common Spatial Pattern (CSP) driven Artificial Neural Network (ANN) Classification strategy is presented to classify the mental tasks, namely, left-hand movement imagination, right-hand movement imagination, and word generation in EEG data. According to this strategy, first, electrode re-referencing and band-pass filtering are used to enhance the EEG signal. Then a multi-class extension...
Firearms leave special marks on the bullet while the bullet travels through the barrel. In this work, visual word codes obtained from interest points were used in bullet matching. Visual codebook was constructed by clustering Scale Invariant Feature Transform (SIFT) features using interest point orientation information as semi-supervised clustering constraint. The ratio of the number of visual words...
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