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Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Vol. 43, Iss. 5 — Feb. 10, 2004
  • pp: 1053–1062

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, and Keith D. Paulsen  »View Author Affiliations


Applied Optics, Vol. 43, Issue 5, pp. 1053-1062 (2004)
http://dx.doi.org/10.1364/AO.43.001053


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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.

© 2004 Optical Society of America

OCIS Codes
(110.2960) Imaging systems : Image analysis
(110.3000) Imaging systems : Image quality assessment
(110.6960) Imaging systems : Tomography
(170.3830) Medical optics and biotechnology : Mammography
(170.6960) Medical optics and biotechnology : Tomography
(170.7050) Medical optics and biotechnology : Turbid media

Citation
Xiaomei Song, Brian W. Pogue, Shudong Jiang, Marvin M. Doyley, Hamid Dehghani, Tor D. Tosteson, and Keith D. Paulsen, "Automated region detection based on the contrast-to-noise ratio in near-infrared tomography," Appl. Opt. 43, 1053-1062 (2004)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-43-5-1053


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