Global Canny algorithm based on Canny edge detector framework in magnetic resonance imaging

Authors

  • Tengku Ahmad Iskandar Tengku Alang Universiti Teknologi Malaysia
  • Tan Tian Swee Universiti Teknologi Malaysia
  • Tan Jia Hou Universiti Teknologi Malaysia
  • Leong Kah Meng Universiti Teknologi Malaysia
  • Sameen Ahmed Malik Universiti Teknologi Malaysia
  • Muhammad Amir Asari Universiti Teknologi Malaysia
  • Adil Hussein HOSPITAL UNIVERSITI SAINS MALAYSIA
  • Azhany Yaakub Hospital Universiti Sains Malaysia
  • Hum Yan Chai Universiti Tunku Abdul Rahman
  • Juhara Haron Hospital Universiti Sains Malaysia

DOI:

https://doi.org/10.11113/mjfas.v13n4-2.761

Keywords:

Edge detection, Non-local means, Canny edge detector, Magnetic resonance images, Segmentation

Abstract

Magnetic resonance imaging is an important modality in the diagnosis and pathology detection. Edge detection is used for image segmentation and feature extraction as part of the medical image analysis. There is no ideal and universal algorithm which performs perfectly under all conditions. Conventional Canny edge detector is not suitable to be used in Magnetic resonance images that contaminated by Rician noise. In this paper, we propose the use of customized non-local means into the Canny edge detector instead of Gaussian smoothing in the conventional Canny edge detector to effectively remove Rician noise while preserving edges in Magnetic resonance image of an internal organ. The result shows that our method can yield better edge detection than conventional method, with minimal false edge detection. The proposed method undergoes several attempts of parameter adjustment to detect true edges successfully using optimal parameter setting.

Author Biographies

Tengku Ahmad Iskandar Tengku Alang, Universiti Teknologi Malaysia

Department of Biotechnology and Medical Engineering, Faculty of Biosciences and Medical Engineering

Tan Tian Swee, Universiti Teknologi Malaysia

Tan Tian Swee is working as Senior Lecturer and Program Manager in the Faculty of Biomedical Engineering, UTM. He received both his M.Sc. degree and Doctorate degree back in the year 2004 and 2008 respectively from the Universiti Teknologi Malaysia.  His research area encompasses the area of Digital Signal Processing and has published numerous high impact factor journals. He is a member of the Medical Device and Technology Group (MediTEG) and Frontier Materials research alliances

Tan Jia Hou, Universiti Teknologi Malaysia

Department of Biotechnology and Medical Engineering, Faculty of Biosciences and Medical Engineering

Leong Kah Meng, Universiti Teknologi Malaysia

Department of Biotechnology and Medical Engineering, Faculty of Biosciences and Medical Engineering

Sameen Ahmed Malik, Universiti Teknologi Malaysia

Sameen Ahmed Malik is currently undertaking PhD Biomedical Engineering in the Faculty of Biomedical Engineering, Universiti Teknologi Malaysia (UTM). He received his BEng (Honours) Electrical & Electronics degree from University of South Wales-UK in 2012 followed by MSc degree in Biomedical Engineering from UTM in 2016. His research is on biosciences and biomedical engineering with focus on ultraviolet light disinfection.

Muhammad Amir Asari, Universiti Teknologi Malaysia

Department of Biotechnology and Medical Engineering, Faculty of Biosciences and Medical Engineering

Adil Hussein, HOSPITAL UNIVERSITI SAINS MALAYSIA

ASSOC. PROF. DR. ADIL HUSSEIN

DEPARTMENT OF OPHTHALMOLOGY

HUSM KUBANG KERIAN,

KELANTAN, MALAYSIA

Azhany Yaakub, Hospital Universiti Sains Malaysia

Department of Ophthalmology

 

Hum Yan Chai, Universiti Tunku Abdul Rahman

Lee Kong Chiang Faculty of Engineering And Science

 

Juhara Haron, Hospital Universiti Sains Malaysia

Department of Radiology

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Published

17-12-2017

Issue

Special Issue on Medical Device and Technology (IMEDITECH 2017)

Section

Article