Abstract
Organ segmentation and identification from computer tomography images is a time consuming process. Organ identifying is one of the crucial steps to give effective radiotherapy. Due to partial volume effects, gray-level similarities of adjacent organs, contrast media affect, and the relatively high variations of organ position and shape, repeatable feature values gives mismatched organs and gives wrong decision making. To overcome these difficulties, Feature based Organ Identification using Signature Quadratic Form Distance (SQFD) method is proposed to recognize the organs such as Lung, Liver, Heart, Abdominal Aorta, Spinal Cord, and Bones from CT image series. In our Analysis several features such as GLCM features, Region features, Wavelet features, Tamura Features, Histogram Intensity features were analyzed and found certain features are used to identify the organs to give effective radiation therapy. The proposed method of identifying organs has been successfully tested among 100 patients and comparing results with manually contouring by experts. Result gives 99% accuracy.
Keywords: Computer tomography, features, radiotherapy, segmentation, signature quadratic form distance.
Graphical Abstract
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