A Review on Parallel Medical Image Processing on GPU

An efficient implementation are necessary, as
most medical imaging methods are computational expensive,
and the amount of medical imaging data is growing .Graphic
processing units (GPUs) can solve large data parallel
problems at a higher speed than the traditional CPU, while
being more affordable and energy efficient than distributed
systems. This review investigates the use of GPUs to
accelerate medical imaging methods. A set of criteria for
efficient use of GPUs are defined. The review concludes that
most medical image processing methods may benefit from
GPU processing due to the methods’ data parallel structure
and high thread count. However, factors such as
synchronization, branch divergence and memory usage can
limit the speedup.