The Application of CUDA Technology in Biomedical Image Processing

Chen, Guannan; Xu, Dawen; Hu, Hengyan; Liu, Yao; Chen, Rong

doi:10.1007/978-3-642-34240-0_50

Cited by 1 publication

(1 citation statement)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Many techniques have been proposed in different knowledge areas like medical image processing [9]. We are interested in the area for diabetic retinopathy detection.…”

Section: Introductionmentioning

confidence: 99%

A GPU-based Evolution Strategy for Optic Disk Detection in Retinal Images

Sánchez-Torres

González-Calederón

2016

rev.ing.univ.Medellin

View full text Add to dashboard Cite

Parallel processing using graphic processing units (gpus) has attracted much research interest in recent years. Parallel computation can be applied to evolution strategy (es) for processing individuals in a population, but evolutionary strategies are time-consuming when used to solve large computational problems or complex fitness functions. In this paper, we describe the implementation of an improved es for optic disk detection in retinal images using the Compute Unified Device Architecture (cuda) environment. In the experimental results, we show that the computational time for optic disk detection task has a speedup factor of 5x and 7x compared to the implementation on a mainstream cpu. Key words:Compute Unified Device Architecture, optic disk, evolutionary strategy, retinal images. Revista Ingenierías Universidad de MedellínGermán Sanchez-Torres -Guillermo González-Calderón Estrategia evolutiva basada en GPU para la detección del disco óptico en imágenes de retina Resumen La ejecución paralela de aplicaciones usando unidades de procesamiento gráfico (gpu) ha ganado gran interés en la comunidad académica en los años recientes. La computación paralela puede ser aplicada a las estrategias evolutivas para procesar individuos dentro de una población, sin embargo, las estrategias evolutivas se caracterizan por un significativo consumo de recursos computacionales al resolver problemas de gran tamaño o aquellos que se modelan mediante funciones de aptitud complejas. Este artículo describe la implementación de una estrategia evolutiva para la detección del disco óptico en imágenes de retina usando Compute Unified Device Architecture (cuda). Los resultados experimentales muestran que el tiempo de ejecución para la detección del disco óptico logra una aceleración de 5 a 7 veces, comparado con la ejecución secuencial en una cpu convencional.Palabras clave: gpu, disco óptico, estrategias evolutivas, imágenes de retina.

show abstract

“…Many techniques have been proposed in different knowledge areas like medical image processing [9]. We are interested in the area for diabetic retinopathy detection.…”

Section: Introductionmentioning

confidence: 99%

A GPU-based Evolution Strategy for Optic Disk Detection in Retinal Images

Sánchez-Torres

González-Calederón

2016

rev.ing.univ.Medellin

View full text Add to dashboard Cite

show abstract

The Application of CUDA Technology in Biomedical Image Processing

Cited by 1 publication

References 0 publications

A GPU-based Evolution Strategy for Optic Disk Detection in Retinal Images

A GPU-based Evolution Strategy for Optic Disk Detection in Retinal Images

Contact Info

Product

Resources

About