투과 컴퓨터 단층촬영을 위한 모델 기반 반복연산 재구성에서 투사선 구동 시스템 모델의 성능 비교
Performance Comparison of Ray-Driven System Models in Model-Based Iterative Reconstruction for Transmission Computed Tomography
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초록
The key to model-based iterative reconstruction (MBIR) algorithms for transmission computed tomographylies in the ability to accurately model the data formation process from the emitted photons produced in thetransmission source to the measured photons at the detector. Therefore, accurately modeling the system matrix thataccounts for the data formation process is a prerequisite for MBIR-based algorithms. In this work we compared quantitativeperformance of the three representative ray-driven methods for calculating the system matrix; the ray-tracingmethod (RTM), the distance-driven method (DDM), and the strip-area based method (SAM). We implemented theordered-subsets separable surrogates (OS-SPS) algorithm using the three different models and performed simulationstudies using a digital phantom. Our experimental results show that, in spite of the more advanced features in theSAM and DDM, the traditional RTM implemented in the OS-SPS algorithm with an edge-preserving regularizer outperformsthe SAM and DDM in restoring complex edges in the underlying object. The performance of the RTM insmooth regions was also comparable to that of the SAM or DDM.
Abstract
The key to model-based iterative reconstruction (MBIR) algorithms for transmission computed tomographylies in the ability to accurately model the data formation process from the emitted photons produced in thetransmission source to the measured photons at the detector. Therefore, accurately modeling the system matrix thataccounts for the data formation process is a prerequisite for MBIR-based algorithms. In this work we compared quantitativeperformance of the three representative ray-driven methods for calculating the system matrix; the ray-tracingmethod (RTM), the distance-driven method (DDM), and the strip-area based method (SAM). We implemented theordered-subsets separable surrogates (OS-SPS) algorithm using the three different models and performed simulationstudies using a digital phantom. Our experimental results show that, in spite of the more advanced features in theSAM and DDM, the traditional RTM implemented in the OS-SPS algorithm with an edge-preserving regularizer outperformsthe SAM and DDM in restoring complex edges in the underlying object. The performance of the RTM insmooth regions was also comparable to that of the SAM or DDM.
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