Cancer Clumps Detection using Image Processing Based on Cell Counting and Artificial Neural Network Techniques
Suneetha Davuluri1, D. Rathna Kishore2
1Dr. Suneetha Davuluri, Associate Professor, Department of CSE, NRIIT, Vijayawada, (A.P) India.
2Dr. D. Rathna Kishore, Professor, Department of CSE, NRIIT, Vijayawada, (A.P) India.
Manuscript received on November 21, 2019. | Revised Manuscript received on December 30, 2019. | Manuscript published on December 30, 2019. | PP: 5124-5126 | Volume-9 Issue-2, December, 2019. | Retrieval Number: B3737129219/2019©BEIESP | DOI: 10.35940/ijeat.B3737.129219
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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: Cancer is one of the main reasons for death among humans. So much research has been done for detecting and diagnosing cancer using image processing and classification and techniques. But the disease remains as one of the deadeist disease. Thus early detection of the disease is only one of the reasons to cure the cancer. In this proposed technique identifying cancer cell by using Image Processing, Artificial Neural Network techniques using cell counting, area measurement and detection of clumps. With the help of proposed technique we detect the cancer traits of any CT image, mammography image of biopsy samples automatically. So many algorithms was proposed but there was a lack of flexibility and the level of accuracy is not consists. Before applying proposed algorithm, the system preprocesses the input images with various techniques like gray scaling, binarization, inversion and flood fill operation. The proposed method can be work on various images and fine tuned with a feedback system and if can effectively used for automatically detection of cancer cells in a unique way and lead to open up new dimension in detecting cancer cell in the field of medical sciences.
Keywords: Image Segmentation, Artificial Neural Network, Mammography Image, Image acquisition, Clusters