English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

In the recent years image processing techniques are used as a tool to improvedetection and diagnostic capabilities in the medical applications. Medicalapplications have been so much affected by these techniques which some of themare embedded in medical instruments such as MRI, CT and other medical devices.Among these techniques, medical image enhancement algorithms play an essentialrole in removal of the noise which can be produced by medical instruments andduring image transfer. It has been proved that impulse noise is a major type ofnoise, which is produced during medical operations, such as MRI, CT, andangiography, by their image capturing devices. An embeddable hardware modulewhich is able to denoise medical images before and during surgical operationscould be very helpful. In this paper an accurate algorithm is proposed forreal-time removal of impulse noise in medical images. All image blocks aredivided into three categories of edge, smooth, and disordered areas. Adifferent reconstruction method is applied to each category of blocks for thepurpose of noise removal. The proposed method is tested on MR images.Simulation results show acceptable denoising accuracy for various levels ofnoise. Also an FPAG implementation of our denoising algorithm shows acceptablehardware resource utilization. Hence, the algorithm is suitable for embeddingin medical hardware instruments such as radiosurgery devices.

Real-Time Impulse Noise Removal from MR Images for Radiosurgery Applications