Cancer Recognition in Medical Image Processing using Watershed Algorithm
Sugumar V1, Aravindasamy R2, Jeffrin Rajan M3, P. Kavitha4
1Sugumar V, Student, Department of IT, Bharath Institute of Higher Education and Research, Tambaram, Tamil Nadu. India.
2Aravindasamy R, Student, Department of CSE, Bharath Institute of Higher Education and Research, Tambaram, Tamil Nadu. India.
3Jeffrin Rajan M, Student, Department of CSE, Bharath Institute of Higher Education and Research, Tambaram, Tamil Nadu. India.
4P. Kavitha, Department of IT, Bharath Institute of Higher Education and Research, Tambaram, Tamil Nadu. India.
Manuscript received on 09 July 2019 | Revised Manuscript received on 21 July 2019 | Manuscript Published on 23 August 2019 | PP: 1172-1175 | Volume-8 Issue-9S3 August 2019 | Retrieval Number: I32560789S319/2019©BEIESP | DOI: 10.35940/ijitee.I3256.0789S319
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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 tumor is by all accounts the basic reason for death among individuals all through the world. Survival from lung tumor is straightforwardly identified with its development at its discovery time. The prior the identification is, the higher the odds of fruitful treatment.. To upgrade malignancy location the radiologists, utilizes CT check pictures for reviewing the insides of the body.Image handling methods give a decent quality apparatus to enhancing the manual examination. Henceforth, a lung malignancy recognition framework utilizing picture handling is utilized to arrange the present of lung disease in a CT-pictures. A programmed growth discovery framework is proposed to recognize malignant tumor from the CT check pictures. The tumor discovery conspire comprises of four phases. They are preprocessing, division, include extraction and characterization. These four levels are utilized as a part of picture handling to upgrade the tumor recognizable proof exactness. The ultimate result of this paper is to discover malignancy identification.
Keywords: Lung Cancer, CT filter, preprocessing division, highlights extraction and grouping.
Scope of the Article: Algorithm Engineering