Trabajo Colaborativo Computaicon Grafica

COMPUTACION GRAFICA
TRABAJO COLABORATIVO 1
Curso académico: 299210

Presentado por Maria Alejandra Marín
Código : 51860620

Presentado a: Tutor Oscar Javier Abaunza García

UNIVERSIDAD NACIONAL ABIERTA Y A DISTANCIA – UNAD
FACULTADA DE CIENCIAS BÁSICAS E INGENIERÍA DE SISTEMAS
Bogotá D.C., Octubre 4 de 2012

Introducción

El desarrollo presente trabajo consta de dos actividadesActividad 1:

Actividad 2: Cada estudiante debe elaborar tres (3) preguntas referentes a los
temas estudiados en la unidad 1 (Seguir los lineamientos proporcionados en el
anexo “Evaluaciones”).

Actividad 1:

Video gamers of computer graphics
Video gamers are generally the biggest consumers of computer graphics cards, using the devices to boost the speed and resolution of theirdigital quests to fend off invading extraterrestrials or outwit hostile dragons. But researchers at Rensselaer Polytechnic Institute seek to harness the power of these computer graphics cards to solve one of the world's most pressing health care technology challenges: radiation exposure from X-ray and CT imaging scans.
Rensselaer nuclear engineering expert X. George Xu is leading an interdisciplinaryteam of academic, medical, and industrial researchers to develop new techniques for quickly calculating the radiation dose a patient will receive from a CT scan. Funded by a $2.6 million grant from the National Institute of Biomedical Imaging and Bioengineering (NIBIB), the research team aims to use NVIDIA video cards and leading-edge parallel processing techniques to help reduce radiation dosecalculations from 10 hours to less than 60 seconds. The team also seeks to test this technology at Massachusetts General Hospital using General Electric's LightSpeed CT scanners.
"With this new study, we hope to bring massively parallel computing power—currently available only to national laboratories and major research universities such as Rensselaer—to busy and resource-limited hospitals," saidXu, professor in the Department of Mechanical, Aerospace, and Nuclear Engineering (MANE) and the Department of Biomedical Engineering at Rensselaer, who heads the university's Nuclear Engineering Program. "There is a high level of interest at the national level to quantify and reduce the amount of ionizing radiation involved in medical imaging. Our parallel computing method has the potential to beused in everyday clinical procedures, which would dramatically decrease the amount of radiation we receive from CT scans."
Three Rensselaer faculty members are partnering with Xu on this study: Wei Ji, assistant professor in MANE; Christopher Carothers, professor in the Department of Computer Science; and Mark Shephard, the Samuel A. Johnson '37 and Elisabeth C. Johnson Professor of Engineeringand director of the university's Scientific Computation Research Center. The Rensselaer team will collaborate with radiologist Mannudeep Kalra and medical physicist Bob Liu at Massachusetts General Hospital in Boston, and Paul Fitzgerald from GE Global Research. Additionally, Forrest Brown from Los Alamos National Lab will serve as a consultant to the project.
As part of the study, the researchteam will perform calculations using the Rensselaer supercomputing center, the Computational Center for Nanotechnology Innovations (CCNI).
Medical imaging scans can provide invaluable information to physicians, and the clinical benefits of a single X-ray or CT scan almost always outweigh the risks of radiation exposure from the procedure. But this radiation exposure risk accumulates over apatient's lifetime, and is a growing concern given the increased frequency with which CT scans are prescribed and performed.
A 2009 report by the National Council on Radiation Protection and Measurements (NCRP), of which Xu is a member, details how the U.S. population is now exposed to seven times more radiation every year from medical imaging exams than it was in 1980. While CT scans only account for...