Wavelet energy-guided level set-based active contour: A segmentation method to segment highly similar regions

Authors:
Anusha Achuthan;Mandava Rajeswari;Dhanesh Ramachandram;Mohd Ezane Aziz;Ibrahim Lutfi Shuaib
Affiliations:
Computer Vision Lab, School of Computer Sciences, Universiti Sains Malaysia, 11900 Penang, Malaysia;Computer Vision Lab, School of Computer Sciences, Universiti Sains Malaysia, 11900 Penang, Malaysia;Computer Vision Lab, School of Computer Sciences, Universiti Sains Malaysia, 11900 Penang, Malaysia;Department of Radiology, Health Campus, Universiti Sains Malaysia, 16150 Kubang Kerian, Malaysia;Advanced Medical and Dental Institute, Universiti Sains Malaysia, 13200 Kepala Batas, Malaysia
Venue:
Computers in Biology and Medicine
Year:
2010

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Abstract

This paper introduces an approach to perform segmentation of regions in computed tomography (CT) images that exhibit intra-region intensity variations and at the same time have similar intensity distributions with surrounding/adjacent regions. In this work, we adapt a feature computed from wavelet transform called wavelet energy to represent the region information. The wavelet energy is embedded into a level set model to formulate the segmentation model called wavelet energy-guided level set-based active contour (WELSAC). The WELSAC model is evaluated using several synthetic and CT images focusing on tumour cases, which contain regions demonstrating the characteristics of intra-region intensity variations and having high similarity in intensity distributions with the adjacent regions. The obtained results show that the proposed WELSAC model is able to segment regions of interest in close correspondence with the manual delineation provided by the medical experts and to provide a solution for tumour detection.