RAMON ALFREDO MORENO
Índice h a partir de 2011
4
Projetos de Pesquisa
Unidades Organizacionais
Instituto do Coração, Hospital das Clínicas, Faculdade de Medicina
LIM/65, Hospital das Clínicas, Faculdade de Medicina
LIM/65, Hospital das Clínicas, Faculdade de Medicina
3 resultados
Resultados de Busca
Agora exibindo 1 - 3 de 3
- Description of patellar movement by 3D parameters obtained from dynamic CT acquisition(2014) REBELO, Marina de Sa; MORENO, Ramon Alfredo; GOBBI, Riccardo Gomes; CAMANHO, Gilberto Luis; AVILA, Luiz Francisco Rodrigues de; DEMANGE, Marco Kawamura; PECORA, Jose Ricardo; GUTIERREZ, Marco AntonioThe patellofemoral joint is critical in the biomechanics of the knee. The patellofemoral instability is one condition that generates pain, functional impairment and often requires surgery as part of orthopedic treatment. The analysis of the patellofemoral dynamics has been performed by several medical image modalities. The clinical parameters assessed are mainly based on 2D measurements, such as the patellar tilt angle and the lateral shift among others. Besides, the acquisition protocols are mostly performed with the leg laid static at fixed angles. The use of helical multi slice CT scanner can allow the capture and display of the joint's movement performed actively by the patient. However, the orthopedic applications of this scanner have not yet been standardized or widespread. In this work we present a method to evaluate the biomechanics of the patellofemoral joint during active contraction using multi slice CT images. This approach can greatly improve the analysis of patellar instability by displaying the physiology during muscle contraction. The movement was evaluated by computing its 3D displacements and rotations from different knee angles. The first processing step registered the images in both angles based on the femur's position. The transformation matrix of the patella from the images was then calculated, which provided the rotations and translations performed by the patella from its position in the first image to its position in the second image. Analysis of these parameters for all frames provided real 3D information about the patellar displacement.
- Estimation of 3D Biomechanics Parameters of Patellar Movement using Dynamic CT Images(2014) REBELO, Marina A.; MORENO, Ramon A.; GOBBI, Riccardo G.; CAMANHO, Gilberto L.; AVILA, Luiz F. R.; DEMANGE, Marco K.; PECORA, Jose R.; GUTIERREZ, Marco A.Multislice CT scanners have characteristics that offer advantages in clinical applications. The technology is particularly suited for medical applications that require high time performance and high spatial resolution. Patellofemoral tracking is one application that can benefit from multi slice CT characteristics. It is performed to study disturbances in the normal tracking mechanism of the patellar femoral joint. The patellofemoral instability is one condition that generates pain, functional impairment and often requires surgery as part of orthopedic treatment. The analysis of the patellofemoral dynamics has been performed by several medical image modalities. However, most of the methods are based on measurements in 2D images, such as the patellar tilt angle and the lateral shift. Besides, the acquisition protocols are mostly performed at fixed angles. The use of helical multislice CT scanner can allow the capture and display of the joint's movement performed actively by the patient. In this work we evaluate the use of multi slice high resolution CT technology to evaluate the biomechanics of the patellofemoral joint. The quantitative analysis of the movement is performed by extracting displacement parameters in 3D images between different knee positions. Analyses of these parameters for all frames provided real 3D information about the patellar displacement.
- Analysis of grid performance using an Optical Flow algorithm for Medical Image processing(2014) MORENO, Ramon A.; CUNHA, Rita de Cassio Porfirio; GUTIERREZ, Marco A.The development of bigger and faster computers has not yet provided the computing power for medical image processing required nowadays. This is the result of several factors, including: i) the increasing number of qualified medical image users requiring sophisticated tools; ii) the demand for more performance and quality of results; iii) researchers are addressing problems that were previously considered extremely difficult to achieve; iv) medical images are produced with higher resolution and on a larger number. These factors lead to the need of exploring computing techniques that can boost the computational power of Healthcare Institutions while maintaining a relative low cost. Parallel computing is one of the approaches that can help solving this problem. Parallel computing can be achieved using multi-core processors, multiple processors, Graphical Processing Units (GPU), clusters or Grids. In order to gain the maximum benefit of parallel computing it is necessary to write specific programs for each environment or divide the data in smaller subsets. In this article we evaluate the performance of the two parallel computing tools when dealing with a medical image processing application. We compared the performance of the EELA-2 (E-science grid facility for Europe and Latin-America) grid infrastructure with a small Cluster (3 nodes x 8 cores = 24 cores) and a regular PC (Intel i3 - 2 cores). As expected the grid had a better performance for a large number of processes, the cluster for a small to medium number of processes and the PC for few processes.