Algorithm-enabled low-dose micro-CT imaging

Xiao Han, Junguo Bian, Diane R. Eaker, Timothy L. Kline, Emil Y. Sidky, Erik L. Ritman, Xiaochuan Pan

Research output: Contribution to journalArticlepeer-review

114 Scopus citations

Abstract

Micro-computed tomography (micro-CT) is an important tool in biomedical research and preclinical applications that can provide visual inspection of and quantitative information about imaged small animals and biological samples such as vasculature specimens. Currently, micro-CT imaging uses projection data acquired at a large number (3001000) of views, which can limit system throughput and potentially degrade image quality due to radiation-induced deformation or damage to the small animal or specimen. In this work, we have investigated low-dose micro-CT and its application to specimen imaging from substantially reduced projection data by using a recently developed algorithm, referred to as the adaptive-steepest-descent-projection-onto-convex-sets (ASD-POCS) algorithm, which reconstructs an image through minimizing the image total-variation and enforcing data constraints. To validate and evaluate the performance of the ASD-POCS algorithm, we carried out quantitative evaluation studies in a number of tasks of practical interest in imaging of specimens of real animal organs. The results show that the ASD-POCS algorithm can yield images with quality comparable to that obtained with existing algorithms, while using one-sixth to one quarter of the 361-view data currently used in typical micro-CT specimen imaging.

Original languageEnglish (US)
Article number5609203
Pages (from-to)606-620
Number of pages15
JournalIEEE transactions on medical imaging
Volume30
Issue number3
DOIs
StatePublished - Mar 2011

Keywords

  • Compressed sensing
  • image reconstruction
  • iterative algorithms
  • low-dose computed tomography

ASJC Scopus subject areas

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

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