2011
Discrete modeling of human body using preprocessing and segmentation techniques of medical images
G. Gavidia, E.Soudah, M.Martín-Landrove, M.Cerrolaza
Rev. int.métodosnumér.cálc.diseñoing.2011;27(3):200–226 [article in spanish]
The generation of anatomical models is one the most important concern to biomedical researchers as well as to medical doctors, due to needed to understand the human tissues. Is know that the soft tissues like heart, brain, prostate and hard tissues lik ejaw, bones, skull, etc are structures of complex morphologies, so, the anatomical models generation is not an easy and trivial task. Currently, this task has benefited of advances of imaging diagnostic, which permit obtain cross and longitudinal sections of human body. In this research, we describe a method to obtain 3D discrete models of human body given by a data set of medical images. Five main modules were implemented in prototype software: (1) Reading and 3D reconstruction of Computerized Axial Tomography and Magnetic Resonance Images. (2) Preprocessing techniques for improve the low medical images quality by using enhancement algorithmst or educe image noise and to increase structures contrast. (3) Combined segmentation techniques for tissue identification, which were applied through a multi-stage approach. (4) Postprocessing techniques to improve segmented volumes and (5) Exportation task of volumes to readable formats by Computer Aided Design (CAD) tools to be later analyzed by numerical methods. The performance of our method is shown on several medical examples and the techniques were validated using statistical descriptors to compare our models with models from free databases. Results showed that the implemented techniques generate precise and useful models for numerical analysis and medical survey, planning and surgery in a short processing time.
Radiobiological model for evaluation of targeted radionuclide therapeutic potential in metastases control
R Martin-Landrove
Medical Physics, Vol. 38, No.6, SU-E-T-13, June 2011
Purpose: To provide a rabiobiological evaluation tool based on a mathematical model for control of metastases during treatment with the use of FDG beta emissions as therapeutic agent. Methods: Analytical and numerical solution of a nonlinear set of equations in order to describe the interaction between beta radiation and clonogenic transformed cells which are part of a primary tumor and related metastases. Under the consideration that beta emissions in this particular case can be taken as high LET radiation, the critical time and fraction number for local minima in the transformed cell population and can be found in closed form. Results: This theory can explain the observed behavior for the primary tumor and particularly for metastases in a mice-melanoma experimental model, where 3 out of 7 of the treated animals showed no metastases. This result suggests the possibility of a fractionation scheme for total dose which can produce the same effect when repeated intravenous inoculations are provided at the proper critical time intervals. Conclusions: For metastases control with radionuclides, which are beta emitters like FDG as therapeutic agents, a treatment planning and follow up is possible from a quantitative point of view using a radiobiological kinetic model based on DNA damage mechanisms.
Between developable surfaces and circular cone splines-curved slices of 3D volumes
Marco Paluszny
Medical Imaging 2011: Visualization, Image Guided Procedures, and Modeling, Kenneth H. Wong, David R. Holmes III (Eds.) Proc. of SPIE Vol. 7964, 796435
Public visualization of high quality medical information has been wildly available since the creation of the Visible Human Project in the late 90´s. We discuss the extraction of information from 3D volumes along curved slices with emphasis on those that can be displayed on the plane without deformation. Special attention is given to a dental volume containing the sixteen teeth of the upper human jaw. We review several approaches to display information along curved slices contained within the 3D data set.
The statistical mechanics of a polygenic character under stabilizing selection, mutation and drift
Harold P. de Vladar, Nick H. Barton
J R Soc Interface. 2011 May 6;8(58):720-39.
By exploiting an analogy between population genetics and statistical mechanics, we study the evolution of a polygenic trait under stabilizing selection, mutation, and genetic drift. This requires us to track only four macroscopic variables, instead of the distribution of all the allele frequencies that in uence the trait. These macroscopic variables are the expectations of: the trait mean and its square, the genetic variance, and of a measure of heterozygosity, and are derived from a generating function that is in turn derived by maximizing an entropy measure. These four macroscopics are enough to accurately describe the dynamics of the trait mean and of its genetic variance (and in principle of any other quantity). Unlike previous approaches that were based on an innite series of moments or cumulants, which had to be truncated arbitrarily, our calculations provide a well-dened approximation procedure. We apply the framework to abrupt and gradual changes in the optimum, as well as to changes in the strength of stabilizing selection. Our approximations are surprisingly accurate, even for systems with as few as 5 loci. We nd that when the eects of drift are included, the expected genetic variance is hardly altered by directional selection, even though it uctuates in any particular instance. We also nd hysteresis, showing that even after averaging over the microscopic variables, the macroscopic trajectories retain a memory of the underlying genetic states.
The contribution of statistical physics to evolutionary biology
Harold P. de Vladar, Nicholas H. Barton
Trends in Ecology & Evolution, Volume 26, Issue 8, p424–432, August 2011
Evolutionary biology shares many concepts with statistical physics: both deal with populations, whether of molecules or organisms, and both seek to simplify evolution in very many dimensions. Often, methodologies have undergone parallel and independent development, as with stochastic methods in population genetics. We discuss aspects of population genetics that have embraced methods from physics: amongst others, non-equilibrium statistical mechanics, travelling waves, and Monte-Carlo methods have been used to study polygenic evolution, rates of adaptation, and range expansions. These applications indicate that evolutionary biology can further benefit from interactions with other areas of statistical physics, for example, by following the distribution of paths taken by a population through time.
