  Proton computed tomography (pCT) is a novel imaging modality developed for
patients receiving proton radiation therapy. The purpose of this work was to
investigate hull-detection algorithms used for preconditioning of the large and
sparse linear system of equations that needs to be solved for pCT image
reconstruction. The hull-detection algorithms investigated here included
silhouette/space carving (SC), modified silhouette/space carving (MSC), and
space modeling (SM). Each was compared to the cone-beam version of filtered
backprojection (FBP) used for hull-detection. Data for testing these algorithms
included simulated data sets of a digital head phantom and an experimental data
set of a pediatric head phantom obtained with a pCT scanner prototype at Loma
Linda University Medical Center. SC was the fastest algorithm, exceeding the
speed of FBP by more than 100 times. FBP was most sensitive to the presence of
noise. Ongoing work will focus on optimizing threshold parameters in order to
define a fast and efficient method for hull-detection in pCT image
reconstruction.
