Noise-resilient edge detection algorithm for brain MRI images

Author

Agaian, Sos ; Almuntashri, Ali

Author_Institution

Coll. of Eng., Univ. of Texas at San Antonio, San Antonio, TX, USA

fYear

2009

fDate

3-6 Sept. 2009

Firstpage

3689

Lastpage

3692

Abstract

In this paper we introduce a noise-resilient edge detection algorithm for brain MRI images. Also, an improved edge detection based on Canny edge detection algorithm is proposed. Computer simulations show that the proposed algorithm is resilient to impulsive noise which makes up for the disadvantages of Canny algorithm, and can detect more edges of MRI brain images effectively. Also, the concept of images fusion is utilized for effective edge detection.

Keywords

biomedical MRI; brain; edge detection; image denoising; medical image processing; Canny edge detection; MRI brain images; brain MRI images; image fusion; noise resilient edge detection; Canny operator; Noise resilient; edge detection; gradient vector; image fusion; medical image segmentation; Algorithms; Artifacts; Brain; Computer Simulation; Diagnostic Imaging; Humans; Image Enhancement; Image Processing, Computer-Assisted; Magnetic Resonance Imaging; Models, Statistical; Normal Distribution; Reproducibility of Results;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE

Conference_Location

Minneapolis, MN

ISSN

1557-170X

Print_ISBN

978-1-4244-3296-7

Electronic_ISBN

1557-170X

Type

conf

DOI

10.1109/IEMBS.2009.5334731

Filename

5334731