  In the recent years image processing techniques are used as a tool to improve
detection and diagnostic capabilities in the medical applications. Medical
applications have been so much affected by these techniques which some of them
are embedded in medical instruments such as MRI, CT and other medical devices.
Among these techniques, medical image enhancement algorithms play an essential
role in removal of the noise which can be produced by medical instruments and
during image transfer. It has been proved that impulse noise is a major type of
noise, which is produced during medical operations, such as MRI, CT, and
angiography, by their image capturing devices. An embeddable hardware module
which is able to denoise medical images before and during surgical operations
could be very helpful. In this paper an accurate algorithm is proposed for
real-time removal of impulse noise in medical images. All image blocks are
divided into three categories of edge, smooth, and disordered areas. A
different reconstruction method is applied to each category of blocks for the
purpose of noise removal. The proposed method is tested on MR images.
Simulation results show acceptable denoising accuracy for various levels of
noise. Also an FPAG implementation of our denoising algorithm shows acceptable
hardware resource utilization. Hence, the algorithm is suitable for embedding
in medical hardware instruments such as radiosurgery devices.
