@article {19299,
	title = {Utilizing Hierarchical Multiprocessing for Medical Image Registration},
	journal = {IEEE Signal Processing Magazine},
	volume = {27},
	year = {2010},
	month = {2010},
	pages = {61 - 68},
	abstract = {This work discusses an approach to utilize hierarchical multiprocessing in the context of medical image registration. By first organizing application parallelism into a domain-specific taxonomy, an algorithm is structured to target a set of multicore platforms.The approach on a cluster of graphics processing units (GPUs) requiring the use of two parallel programming environments to achieve fast execution times is demonstrated.There is negligible loss in accuracy for rigid registration when employing GPU acceleration, but it does adversely effect our nonrigid registration implementation due to our usage of a gradient descent approach.},
	keywords = {Acceleration, application parallelism, Biomedical imaging, domain-specific taxonomy, GPU acceleration, gradient descent approach, Graphics processing unit, hierarchical multiprocessing, image registration, Magnetic resonance imaging, Medical diagnostic imaging, medical image processing, medical image registration, multicore platform set, Multicore processing, PARALLEL PROCESSING, parallel programming, Robustness, Signal processing algorithms, Ultrasonic imaging},
	isbn = {1053-5888},
	author = {Plishker,W. and Dandekar,O. and Bhattacharyya, Shuvra S. and Shekhar,R.}
}
