Background: The majority of de novo cancers are diagnosed in low and middle-income countries, which often lack the resources to provide adequate therapeutic options. None or minimally invasive therapies such as Photodynamic Therapy (PDT) or photothermal therapies could become part of the overall treatment options in these countries. However, widespread acceptance is hindered by the current empirical training of surgeons in these optical techniques and a lack of easily usable treatment optimizing tools. Methods: Based on image processing programs, ITK-SNAP, and the publicly available FullMonte light propagation software, a work plan is proposed that allows for personalized PDT treatment planning. Starting with, contoured clinical CT or MRI images, the generation of 3D tetrahedral models in silico, execution of the Monte Carlo simulation and presentation of the 3D fluence rate, Φ, [mWcm-2] distribution a treatment plan optimizing photon source placement is developed. Results: Permitting 1-2 days for the installation of the required programs, novices can generate their first fluence, H [Jcm-2] or Φ distribution in a matter of hours. This is reduced to 10th of minutes with some training. Executing the photon simulation calculations is rapid and not the performance limiting process. Largest sources of errors are uncertainties in the contouring and unknown tissue optical properties. Conclusions: The presented FullMonte simulation is the fastest tetrahedral based photon propagation program and provides the basis for PDT treatment planning processes, enabling a faster proliferation of low cost, minimal invasive personalized cancer therapies.