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 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.
Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire 03755, USA.
Xiaomei
X
Song
Brian W
BW
Pogue
Shudong
S
Jiang
Marvin M
MM
Doyley
Hamid
H
Dehghani
Tor D
TD
Tosteson
Keith D
KD
Paulsen
D016477:Artifacts; D003198:Computer Simulation; D004867:Equipment Design; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007259:Infrared Rays; D008962:Models, Theoretical; D019047:Phantoms, Imaging; D019265:Spectroscopy, Near-Infrared / Q000295:instrumentation; D014054:Tomography / Q000295:instrumentation