Volume 12, Number 3

Using Distance Measure based Classification in Automatic Extraction
of Lungs Cancer Nodules for Computer Aided Diagnosis

  Authors

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

  Abstract

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.

  Keywords

Nodules classification, lungs cancer, morphological operators, weighted Euclidean distance, nodules extraction.