ABSTRACT
The basis of Monte Carlo (MC) numerical techniques can be described as statistical methods where random number generators are used to perform more realistic simulations for specified situations. Thus computer science has been rapidly evolving by enabling high-performance computers, clusters and grids of central processing units, and lately graphical physical units that are extensively used for the acquisition of MC simulations. With the rise of small animal imaging, new instrumentation, data acquisition strategies, image processing, and reconstruction techniques are being developed and evaluated. As small animal imaging provides a noninvasive way of assaying biological information and function, the number of scientific studies rapidly increases. In radiation protection, radiological imaging, and radiotherapy research, a lot of effort is put into modeling the anatomy of the specimen. The field of preclinical targeted radionuclide therapy has raised the interest of the scientific community recently in individualized and accurate dosimetric schemes, which are of high priority and of great importance.
