Towards monitored tomographic reconstruction: algorithm-dependence and convergence

Author:

Bulatov K.B., ,Ingacheva A.S.,Gilmanov M.I.,Kutukova K.,Soldatova Z.V.,Buzmakov A.V.,Chukalina M.V.,Zschech E.,Arlazarov V.V., , , , , , , , , , , , , ,

Abstract

The monitored tomographic reconstruction (MTR) with optimized photon flux technique is a pioneering method for X-ray computed tomography (XCT) that reduces the time for data acquisition and the radiation dose. The capturing of the projections in the MTR technique is guided by a scanning protocol built on similar experiments to reach the predetermined quality of the reconstruction. This method allows achieving a similar average reconstruction quality as in ordinary tomography while using lower mean numbers of projections. In this paper, we, for the first time, systematically study the MTR technique under several conditions: reconstruction algorithm (FBP, SIRT, SIRT-TV, and others), type of tomography setup (micro-XCT and nano-XCT), and objects with different morphology. It was shown that a mean dose reduction for reconstruction with a given quality only slightlyvaries with choice of reconstruction algorithm, and reach up to 12.5 % in case of micro-XCT and 8.5 % for nano-XCT. The obtained results allow to conclude that the monitored tomographic reconstruction approach can be universally combined with an algorithm of choice to perform a controlled trade-off between radiation dose and image quality. Validation of the protocol on independent common ground truth demonstrated a good convergence of all reconstruction algorithms within the MTR protocol.

Publisher

Samara National Research University

Subject

Electrical and Electronic Engineering,Computer Science Applications,Atomic and Molecular Physics, and Optics

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Applicability and potential of monitored reconstruction in computed tomography;PLOS ONE;2024-07-22

2. Determining the directions of information flow between populations of spiking neurons;2024 X International Conference on Information Technology and Nanotechnology (ITNT);2024-05-20

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