Lung Nodule Detection in CT Images using Thresholding and Morphological Operations
Sudha. V1, Jayashree. P2
1Sudha.V Electronics and Instrumentation Engineering, Kongu Engineering College, Erode, India.
2Jayashree.P, Electronics and Instrumentation Engineering, Kongu Engineering College, Erode, India.
Manuscript received on December 01, 2012. | Revised Manuscript received on December 18, 2012. | Manuscript published on December 25, 2012. | PP: 17-21 | Volume-1 Issue-2, December 2012 | Retrieval Number: B0115121212/2012©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Lung cancer which is among the five main types of cancer is a leading one to overall cancer mortality contributing about 1.3 million deaths/year globally. Lung cancer is a disease and it is characterized by uncontrolled cell growth in tissues of the lung. Lung nodule is an abnormality that leads to lung cancer, characterized by a small round or oval shaped growth on the lung which appears as a white shadow in the CT scan. An effective computer aided lung nodule detection system can assist radiologists in detecting lung abnormalities at an early stage. If defective nodules are detected at an early stage, the survival rate can be increased up to 50%. This paper aims to develop an efficient lung nodule detection system by performing nodule segmentation through thresholding and morphological operations. The proposed method has two stages: lung region segmentation through thresholding and then segmenting the lung nodules through thresholding and morphological operations
Keywords: Computed Tomography, Morphological Operations, Segmentation, Thresholding.