A Noval Algorithm For Denoising and Segmentation of Brain MRI using Rough Set Theory

Authors

  • Vijendar amgothu Dept.of Computer Science and Engineering University College of Engineering Osmania University Hyderabad, Telangana
  • Prof.P.Ram Kumar Dept.of Computer Science and Engineering University College of Engineering Osmania University Hyderabad, Telangana

Keywords:

Roush set Theory, Edge detection, Magnetic Resonance Images(MRI), Segmentation

Abstract

Rough set Theory have been used as a module of hybrid solutions in data mining and machine learning
domain. The main aim of proposed method is to develop a novel algorithm for object based edge detection and
segmentation of Magnetic Resonance Images (MRI) using Rough set theory. In this work, pixel intensity value is
considered as an attribute to discriminate objects within the image. The intensity thresholds, is obtained from image
histogram. Where histogram serves as feature of an object. The performance is validated using Jaccard Similarity Index
(JSI) and Peak Signal to noise Ratio (PSNR).The proposed method better performance than Active Contour and CLICK
methods.

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Published

2018-02-25

How to Cite

Vijendar amgothu, & Prof.P.Ram Kumar. (2018). A Noval Algorithm For Denoising and Segmentation of Brain MRI using Rough Set Theory. International Journal of Advance Engineering and Research Development (IJAERD), 5(2), 888–893. Retrieved from https://ijaerd.org/index.php/IJAERD/article/view/2517

Issue

Vol. 5 No. 2 (2018): Volume 5 Issue 2 February 2018

Section

Articles