A Technique for the Detection of Cystic Focal Liver Lesions from Abdominal Images
Sreeja P1, Hariharan S2
1Sreeja P, Department of Electrical Engineering, College of Engineering, Trivandrum, University of Kerala, Thiruvananthapuram (Kerala), India.
2Dr. Hariharan S, Professor, Department of Electrical Engineering, College of Engineering, Trivandrum, University of Kerala, Thiruvananthapuram (Kerala), India.
Manuscript received on 15 August 2015 | Revised Manuscript received on 25 August 2015 | Manuscript Published on 30 August 2015 | PP: 70-75 | Volume-4 Issue-6, August 2015 | Retrieval Number: F4171084615/15©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Computer aided detection of cystic focal liver lesions (FLL) from Computed Tomography (CT), Magnetic Resonance (MR) or ultra sound (US) abdominal images is a challenging task in pattern recognition and image processing. Region of interest (ROI) is taken from unenhanced/enhanced images from different imaging modalities. A simple and novel algorithm is applied in MATLAB platform and the lesions are clearly identified and highlighted. The proposed algorithm is based on template matching, but it overcomes certain difficulties incurred while applying to biomedical images. The new algorithm progresses in a semiautomatic fashion and can be modified to a fully automatic system for the detection of liver lesions. The algorithm was evaluated on different CT, MR and US abdominal images. The results demonstrate the efficiency of the proposed technique for reliable detection of liver lesions from different imaging modalities.
Keywords: Imaging Modalities, Template Matching, Cystic Focal Liver Lesions And Correlation
Scope of the Article: Image Processing