Title :
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
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;
Conference_Titel :
Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE
Conference_Location :
Minneapolis, MN
Print_ISBN :
978-1-4244-3296-7
Electronic_ISBN :
1557-170X
DOI :
10.1109/IEMBS.2009.5334731
