Automated region detection based on the contrast-to-noise ratio in near-infrared tomography

Xiaomei Song*, Brian W. Pogue, Shudong Jiang, Marvin M. Doyley, Hamid Dehghani, Tor D. Tosteson, Keith D. Paulsen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

The contrast-to-noise ratio (CNR) was used to determine the detectability of objects within reconstructed images from diffuse near-infrared tomography. It was concluded that there was a maximal value of CNR near the location of an object within the image and that the size of the true region could be estimated from the CNR. Experimental and simulation studies led to the conclusion that objects can be automatically detected with CNR analysis and that our current system has a spatial resolution limit near 4 mm and a contrast resolution limit near 1.4. A new linear convolution method of CNR calculation was developed for automated region of interest (ROI) detection.

Original languageEnglish
Pages (from-to)1053-1062
Number of pages10
JournalApplied Optics
Volume43
Issue number5
DOIs
Publication statusPublished - 10 Feb 2004

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Engineering (miscellaneous)
  • Electrical and Electronic Engineering

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