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

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...

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Bibliographic Details
Published in:Applied optics (2004) 2004-02, Vol.43 (5), p.1053-1062
Main Authors: Song, Xiaomei, Pogue, Brian W, Jiang, Shudong, Doyley, Marvin M, Dehghani, Hamid, Tosteson, Tor D, Paulsen, Keith D
Format: Article
Language:English
Subjects:
Computer Simulation
Equipment Design
Humans
Image Processing, Computer-Assisted
Infrared Rays
Models, Theoretical
Phantoms, Imaging
Spectroscopy, Near-Infrared - instrumentation
Tomography - instrumentation
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Summary: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.
ISSN:1559-128X
DOI:10.1364/ao.43.001053