We study the effect of anatomical backgrounds on the detection capability as quantified by the Hotelling observer. The imaging system is modeled by the diffusion approximation of the time-dependent radiative transfer equation, which typically describes NIR light propagation through clinically relevant tissue volumes. We introduce random structures in the background using lumpy object model. Varying intensities of the lumpy objects are introduced in order to evaluate their effect on the Hotelling signal-to-noise ratio (SNR). Large samples of image data sets are considered to generate sufficient statistical data in order to perform Hotelling observer studies. We find that the value of Hotelling SNR decreases as we increase the strength of the lumpy objects.
['Amit Sahu', 'Amit Joshi', 'Eva M. Sevick-Muraca']
Effect of random structured backgrounds on Hotelling SNR fluorescence imaging systems