Volume 12, Number 3
Using Distance Measure based Classification in Automatic Extraction
of Lungs Cancer Nodules for Computer Aided Diagnosis
Maan Ammar1, Muhammad Shamdeen2, MazenKasedeh2, Kinan Mansour3 and Waad Ammar3, 1AL Andalus University for Medical Sciences, Syria, 2Damascus University, Syria, 3Al Andalus University Hospital, Syria
We introduce in this paper a reliable method for automatic extraction of lungs nodules from CT chest images and shed the light on the details of using the Weighted Euclidean Distance (WED) for classifying lungs connected components into nodule and not-nodule. We explain also using Connected Component Labeling (CCL) in an effective and flexible method for extraction of lungs area from chest CT images with a wide variety of shapes and sizes. This lungs extraction method makes use of, as well as CCL, some morphological operations. Our tests have shown that the performance of the introduce method is high. Finally, in order to check whether the method works correctly or not for healthy and patient CT images, we tested the method by some images of healthy persons and demonstrated that the overall performance of the method is satisfactory.
Nodules classification, lungs cancer, morphological operators, weighted Euclidean distance, nodules extraction.