Agaian Sos, Almuntashri Ali
University of Texas at San Antonio, USA.
Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:3689-92. doi: 10.1109/IEMBS.2009.5334731.
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.
在本文中，我们介绍了一种用于脑部磁共振成像（MRI）图像的抗噪声边缘检测算法。此外，还提出了一种基于Canny边缘检测算法的改进边缘检测方法。计算机模拟表明，该算法对脉冲噪声具有抗性，弥补了Canny算法的不足，能够有效地检测出更多脑部MRI图像的边缘。同时，利用图像融合的概念进行有效的边缘检测。
