Automatic Detection and Classification of Lung Carcinoma using Image Processing Techniques in Lab VIEW
1M.Priya, Research Scholar, Department of Computer Applications, Alagappa University – Karaikudi.
2A. Nagarajan, Assistant Professor, Department of Computer Applications, Alagappa University – Karaikudi.
Manuscript received on January 02, 2020. | Revised Manuscript received on January 15, 2020. | Manuscript published on January 30, 2020. | PP: 1216-1219 | Volume-8 Issue-5, January 2020. | Retrieval Number: E5820018520/2020©BEIESP | DOI: 10.35940/ijrte.E5820.018520
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© The Authors. 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 screening saves human lives by detecting cancer earlier, when it may be treated more successfully. The most familiar methods for the diagnosis of lung cancer includes bronchoscope guided BronchoAlveolar Lavage (BAL) samples and the CT scan. In this paper, we propose a technique to automatically analyze the microscopic images of BAL samples and CT scan images in the same platform. This method will help in reducing the manual intervention and provides many useful parameters such as location, size and number of clusters present in the images. We have processed the images using the specialized software in LabVIEW, NI vision Assistance. The detection is done with the microscopic images of BAL and the stages are classified with the analysis of CT scan images. For this, separate algorithms have been developed using Vision Assistant and the common user interface has been designed using LabVIEW.
Keywords: Biopsy, Bronchoscope, Broncho Alveolar Lavage (BAL), Computed Tomography, vision Assistance, LabVIEW, User interface.
Scope of the Article: Classification.