Uniformly Sampled Polar and Cylindrical Grid Approach for 2D, 3D Image Reconstruction using Algebraic Algorithm
Sudhir Kumar Chaudhary, Pankaj Wahi, Prabhat Munshi

TL;DR
This paper introduces a novel discretization scheme for algebraic image reconstruction that significantly speeds up processing and reduces memory requirements by leveraging symmetries in polar and cylindrical grids.
Contribution
The authors propose the USPG/USCG discretization scheme and an efficient USPG to Cartesian Grid transformation, enhancing algebraic reconstruction methods' speed and efficiency.
Findings
Reconstruction speed increased by a factor of 2.5.
Memory requirement reduced proportionally to the number of projections.
Validated with experimental data from frog and Cu-Lump images.
Abstract
Image reconstruction by Algebraic Methods (AM) outperforms the transform methods in situations where the data collection procedure is constrained by time, space, and radiation dose. AM algorithms can also be applied for the cases where these constraints are not present but their high computational and storage requirement prohibit their actual breakthrough in such cases. In the present work, we propose a novel Uniformly Sampled Polar/Cylindrical Grid (USPG/USCG) discretization scheme to reduce the computational and storage burden of algebraic methods. The symmetries of USPG/USCG are utilized to speed up the calculations of the projection coefficients. In addition, we also offer an efficient approach for USPG to Cartesian Grid (CG) transformation for the visualization. The Multiplicative Algebraic Reconstruction Technique (MART) has been used to determine the field function of the…
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Taxonomy
TopicsMedical Imaging Techniques and Applications · Mathematical Biology Tumor Growth · Advanced Radiotherapy Techniques
MethodsAttention Model · SPEED: Separable Pyramidal Pooling EncodEr-Decoder for Real-Time Monocular Depth Estimation on Low-Resource Settings
