Optimization of Brain Cancer Images with Some Noise Models
DOI:
https://doi.org/10.31449/inf.v47i9.4566Abstract
Diagnosis of brain cancer based on magnetic resonance images (MRI) is affected by many conditions, such as the movement of the patient during capture, which leads to the occurrence of noise associated with these images. In order to improve the corner detection methods, many corner detection methods were adopted according to the many noise models. Experimental results showed the effect of magnetic resonance imaging capabilities on both Corner detection methods, noise model. It is possible to rely on other medical images such as Doppler images and neural network algorithms to use image features in diagnosing cancer.
Downloads
Published
How to Cite
Issue
Section
License
I assign to Informatica, An International Journal of Computing and Informatics ("Journal") the copyright in the manuscript identified above and any additional material (figures, tables, illustrations, software or other information intended for publication) submitted as part of or as a supplement to the manuscript ("Paper") in all forms and media throughout the world, in all languages, for the full term of copyright, effective when and if the article is accepted for publication. This transfer includes the right to reproduce and/or to distribute the Paper to other journals or digital libraries in electronic and online forms and systems.
I understand that I retain the rights to use the pre-prints, off-prints, accepted manuscript and published journal Paper for personal use, scholarly purposes and internal institutional use.
In certain cases, I can ask for retaining the publishing rights of the Paper. The Journal can permit or deny the request for publishing rights, to which I fully agree.
I declare that the submitted Paper is original, has been written by the stated authors and has not been published elsewhere nor is currently being considered for publication by any other journal and will not be submitted for such review while under review by this Journal. The Paper contains no material that violates proprietary rights of any other person or entity. I have obtained written permission from copyright owners for any excerpts from copyrighted works that are included and have credited the sources in my article. I have informed the co-author(s) of the terms of this publishing agreement.
Copyright © Slovenian Society Informatika
