Factor analysis has been pursued as a means to decompose dynamic cardiac PET images into different tissue types based on their unique physiology. Each tissue is represented by a time-activity profile (factor) and an associated spatial distribution (structure). Decomposition is based on non-negative constraints of both the factors and structures; however, additional constraints are required to achieve a unique solution. In this work we present a novel method (minimal factor overlap - MFO) and compare its performance to a previously published constraint (minimal spatial overlap - MSO). We compared both methods using simulated data and on a canine model with variable 82Rb infusion profiles. Biasing of factors due to spillover is reduced with MFO compared to MSO, while the robustness and reproducibility of MSO is maintained.

Additional Metadata
Persistent URL dx.doi.org/10.1109/NSSMIC.2007.4436835
Conference 2007 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS-MIC
Citation
Klein, R. (Ran), Bentourkia, M. (M'hamed), Beanlands, R.S. (Rob S.), Adler, A, & DeKemp, R.A. (Robert A.). (2007). A minimal factor overlap method for resolving ambiguity in factor analysis of dynamic cardiac PET. Presented at the 2007 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS-MIC. doi:10.1109/NSSMIC.2007.4436835