Comparison of the convergence properties of the It-W and OS-EM algorithms in SPECT

Rapid convergence of iterative algorithms is a prerequisite for their clinical use in single-photon emission computed tomography (SPECT). The rate of convergence of two accelerated methods, It-W (JNM 1993;34:1793) and ordered subset expectation-maximization (OS-EM, IEEE-TMI 1994;13:601) were compared using a resolution phantom containing objects of sizes ranging from 1.0 to 2.5 cm. Object contrast was used as a measure of convergence. Attenuation and depth-dependent blur were modeled in the 90 angle projections and during reconstruction. For both methods, convergence was most rapid at the periphery and slowest in the center, with larger (lower frequency) objects converging most rapidly. When assessed under noise-free conditions, It-W converged faster than both 6- and 15-subset OS-EM. In an ensemble of 25 noisy images both methods gave essentially identical reconstructions when compared at equivalent noise levels using kernel-sieve regularization, but It-W again converged faster than both 6- and 15-subset OS-EM. When assessed using clinical SPECT data, convergence of It-W was faster than 16-subset OS-EM, and similar to 32 subset OS-EM. Thus, the It-W method provides an alternate method of accelerating iterative reconstruction