UCL Discovery

Abstract

We apply task-based assessment of image quality to optical tomography imaging systems. In particular, we studied the task of detecting a signal, specified as a change in scattering and absorption coefficients, when its shape and location were known. The detectability was quantified using the optimal linear (Hotelling) observer. The non-linearity of the problem was no impediment in computing the Hotelling observer using a hybrid approach that combines knowledge of the measurement statistics with sampling to account for anatomical variation. We compared the observer performance on the raw data in uniform and structured backgrounds for several data and signal types. Two of the data types studied were the total number of photons (total counts) collected for each source-detector pair and their respective mean time of arrival. Results show that the spatial variation of detectability was different for the total counts than for the mean time. The performance of the total counts and its relative performance to the mean time varied significantly with both signal type and background variations.