Physics Model Based Scatter Correction in Multi-source Interior Computed Tomography

Hao Gong, Bin Li, Xun Jia, Guohua Gao

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

Multi-source interior computed tomography (CT) has a great potential to provide ultra-fast and organ-oriented imaging at low radiation dose. However, X-ray cross scattering from multiple simultaneously activated X-ray imaging chains compromises imaging quality. Previously, we published two hardware based scatter correction methods for multi-source interior CT. Here, we propose a software based scatter correction method, with the benefit of no need for hardware modifications. The new method is based on a physics model and an iterative framework. The physics model was derived analytically, and was used to calculate X-ray scattering signals in both forward direction and cross directions in multi-source interior CT. The physics model was integrated to an iterative scatter correction framework to reduce scatter artifacts. The method was applied to phantom data from both Monte Carlo simulations and physical experimentation that were designed to emulate the image acquisition in a multi-source interior CT architecture recently proposed by our team. The proposed scatter correction method reduced scatter artifacts significantly, even with only one iteration. Within a few iterations, the reconstructed images fast converged toward the “scatter-free” reference images. After applying the scatter correction method, the maximum CT number error at the region-of-interests (ROIs) was reduced to 46 HU in numerical phantom dataset and 48 HU in physical phantom dataset respectively, and the contrast-noise-ratio (CNR) at those ROIs increased by up to 44.3% and up to 19.7% respectively. The proposed physics model based iterative scatter correction method could be useful for scatter correction in dual-source or multi-source CT.

Original languageEnglish (US)
JournalIEEE Transactions on Medical Imaging
DOIs
StateAccepted/In press - Aug 17 2017

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Keywords

  • Computed tomography
  • cross scattering
  • forward scattering
  • interior tomography
  • Monte Carlo methods
  • Multi-source
  • Phantoms
  • scatter correction
  • Scattering
  • X-ray imaging

ASJC Scopus subject areas

  • Software
  • Radiological and Ultrasound Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering

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