The following information was submitted:
Transactions: WSEAS Transactions
Transactions ID Number: 18-103
Full Name: Lai Khin Wee
Position: Researcher
Age: ON
Sex: Male
Address: Max Planck Ring-9
Country: GERMANY
Tel:
Tel prefix:
Fax:
E-mail address: khin-wee.lai@tu-ilmenau.de
Other E-mails: eko@utm.my, kwlai2@live.utm.my, ychum2@live.utm.my
Title of the Paper: Ultrasound Images Edge Detection using Anisotropic Diffusion in Canny Edge Detector Framework
Authors as they appear in the Paper: Hum Yan Chai, Lai Khin Wee, Eko Supriyanto
Email addresses of all the authors: khin-wee.lai@tu-ilmenau,de, eko@utm.my, ychum2@live.utm.my
Number of paper pages: 10
Abstract: Conventional Canny edge detector can detect edges in image with additive noise effectively but not ultrasound image that are corrupted by multiplicative speckle noise which alleviates image resolution resulting in inaccurate characterization of object features. In this paper, we proposed to incorporate the modified SRAD into the Canny edge detector to replace the Gaussian blurring in the conventional Canny edge detector in order to suppress the multiplicative noise effectively while preserving the edge of the object in ultrasound image. The result shows that the proposed method can provide better result than conventional method in a much wider range of parameter values. The proposed method through experimental result indicates that it is capable of producing promising edge detection result in ultrasound image.
Keywords: edge detection, speckle reducing anisotropic diffusion, ultrasound image enhancement, noise filtering
EXTENSION of the file: .pdf
Special (Invited) Session: Edge Detection in Ultrasound Images Using Speckle Reducing Anisotropic Diffusion in Canny Edge Detector Framework
Organizer of the Session: 659-425
How Did you learn about congress:
IP ADDRESS: 141.24.50.39
