RESUMEN
Thanks to an experimental study based on simulated and physical phantoms, the propagation of the stochastic noise in slices reconstructed using the conjugate gradient algorithm has been analysed versus iterations. After a first increase corresponding to the reconstruction of the signal, the noise stabilises before increasing linearly with iterations. The level of the plateau as well as the slope of the subsequent linear increase depends on the noise in the projection data.
Asunto(s)
Algoritmos , Procesamiento de Imagen Asistido por Computador , Tomografía Computarizada de Emisión de Fotón Único , Simulación por Computador , Humanos , Fantasmas de Imagen , Distribución de Poisson , Procesos EstocásticosRESUMEN
Multimodal images registration can be very helpful for diagnostic applications. However, even if a lot of registration algorithms exist, only a few really work in clinical routines. We developed a method based on surface matching and compared two minimization algorithms: Powell's and Downhill Simplex. We studied the influence of some factors (chamfer map computation, number and order of parameters to determine, minimization criteria) on the final accuracy of the algorithm. Using this comparison, we improved some processing steps to allow a clinical use, and selected the simplex algorithm which presented the best results.
