The aim of this work is to show that a computer program, called digital image processing (DIP), can be used as an alternative method for breast diagnosis in hospitals and clinics that have not yet computerized mammography service. The image of mammogram obtained in reference is used to demonstrate the usefulness of some techniques of the DIP computer program involving contrast enhancement, smoothing of noise and segmentation. These techniques were used to calculate the area of soft tissue that is being occupied by certain tumor. To implement the DIP techniques the mammography department needs to have a high-resolution scanner, a computer and the DIP software, which is an application, developed by the Grupo de Dosimetria Numérica (GDN). The images can be organized and stored into stacks of images in the standard format for 3D image on DIP and then processed to obtain an improvement. In this work, we used the nonlinear median filter to remove noise or artifacts of the original image. Linear functions have also been used to improve contrast and sharpest of the image. Using segmentation and logical operations the area where the tumor is located in the image will be treated and correspond to the shades of gray. Then, the pixels are computed aiming to calculate the percentage of soft tissue that is occupied by the tumor

Radiotherapy uses various techniques and equipment for local treatment of cancer. The equipment most often used in radiotherapy to the patient irradiation is linear accelerator (Linac). Among the many algorithms developed for evaluation of dose distributions in radiotherapy planning, the algorithms based on Monte Carlo (MC) methods have proven to be very promising in terms of accuracy by providing more realistic results. The MC simulations for applications in radiotherapy are divided into two parts. In the first, the simulation of the production of the radiation beam by the Linac is performed and then the phase-space is generated. In the second part the simulation of the transport of particles (sampled phase-space) in certain configurations of irradiation field is performed to assess the dose distribution. Accurate modeling of the Linac head is of particular interest in the calculation of dose distributions for intensity modulated radiation therapy (IMRT), where complex intensity distributions are delivered using a multileaf collimator (MLC). The objective of this work is to describe a methodology for modeling MC of MLCs using code Geant4. To exemplify this methodology, the Varian Millennium 120-leaf MLC was modeled. The dosimetric characteristics (i.e., penumbra, leakage, and tongue-and-groove effect) of this MLC were evaluated. The results agreed with data published in the literature concerning the same MLC.

Among the many algorithms developed for evaluation of dose distributions in radiotherapy, the Monte Carlo methods provide more realistic results. In intensity modulated radiation therapy, significant differences in dose distributions within the fields defined by multileaf collimator (MLC) could have significant radiobiology effects. Thus, it is important to model thoroughly the MLC to allow more accurate radiotherapy delivery. The objective of this work is to describe and to validate a methodology for modeling of MLCs using code Geant4. The Varian Millennium 120-leaf MLC was modeled using this methodology and it was experimentally verified. The leaves of the MLC were built using three types of solid (G4Box, G4Tubs and G4ExtrudeSolid) and the Boolean operation of subtraction (G4SubtractionSolid). Based on this methodology, it is possible to simulate other Varian MLC models and MLCs with similar design.

The level of natural radiation in some regions of Brazil, and the world, have become high. One of the places that have these high levels are underground mines. At these locations, the radiation may come from the ground, the walls, and the environment in the form of gases. The Group of Numerical Dosimetry (GDN), already developed, and utilizes various of Computational Models Exposure (MCE) to simulate situations where people are exposed to ionizing radiation. In one study, the GDN utilized the MCEs to to simulate the soil contamination by natural elements. This work aims to continue the study of contamination by natural elements, taking into account the energy interval range of gaseous natural elements. For this, the algorithm developed by GDN in 2004, was upgraded to simulate the irradiation of a person in the standing position, where its craniocaudal axis coincides with the axis of a cylinder circumscribing the body, where they emerge, isotropically, photons This update was done in the model MSTA (Mash Standard) To describe this situation we used a MCE composed of the font algorithm described by Vieira the phantom MASH and the MC code EGSnrc The simulation results were organized in formats absorbed dose / air Kerma. These data may be used for other situations where the user that knows the energies, and their abundances, can interpolate the data to obtain new results without the need to conduct new simulations.

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