Wavelet energy-guided level set-based active contour: a segmentation method to segment highly similar regions.
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.
Achuthan
Anusha
A
Computer Vision Lab, School of Computer Sciences, Universiti Sains Malaysia, 11900 Penang, Malaysia. anusha@cs.usm.my
Rajeswari
Mandava
M
Ramachandram
Dhanesh
D
Aziz
Mohd Ezane
ME
Shuaib
Ibrahim Lutfi
IL
D000465:Algorithms; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016011:Normal Distribution; D012680:Sensitivity and Specificity; D013964:Thyroid Neoplasms / Q000000981:diagnostic imaging / Q000473:pathology; D014057:Tomography, X-Ray Computed / Q000379:methods*; D001749:Urinary Bladder Neoplasms / Q000000981:diagnostic imaging / Q000473:pathology