_:neb2e8e48f5bb4177bcb40fb8a05efbe6xb0
<http://schema.org/description>
"In the recent years image processing techniques are used as a tool to improve\ndetection and diagnostic capabilities in the medical applications. Medical\napplications have been so much affected by these techniques which some of them\nare embedded in medical instruments such as MRI, CT and other medical devices.\nAmong these techniques, medical image enhancement algorithms play an essential\nrole in removal of the noise which can be produced by medical instruments and\nduring image transfer. It has been proved that impulse noise is a major type of\nnoise, which is produced during medical operations, such as MRI, CT, and\nangiography, by their image capturing devices. An embeddable hardware module\nwhich is able to denoise medical images before and during surgical operations\ncould be very helpful. In this paper an accurate algorithm is proposed for\nreal-time removal of impulse noise in medical images. All image blocks are\ndivided into three categories of edge, smooth, and disordered areas. A\ndifferent reconstruction method is applied to each category of blocks for the\npurpose of noise removal. The proposed method is tested on MR images.\nSimulation results show acceptable denoising accuracy for various levels of\nnoise. Also an FPAG implementation of our denoising algorithm shows acceptable\nhardware resource utilization. Hence, the algorithm is suitable for embedding\nin medical hardware instruments such as radiosurgery devices."
<https://deepai.org/publication/real-time-impulse-noise-removal-from-mr-images-for-radiosurgery-applications>