Spotting Brain and Pancreatic Tumor using Fuzzy C-Mean Segmentation and SIFT Extraction Through Sparse Representation Method
Jithendra Reddy. D1, Arun Prasath. T2, Pallikonda Rajasekaran. M3, Vishnuvarthanan. G4
1D. Jithendra Reddy, Department of Instrumentation and Control Engineering, Kalasalingam Academy of Research and Education College, Krishnankoil (Tamil Nadu), India.
2T. Arun Prasath, Department of Biomedical Engineering, Kalasalingam Academy of Research and Education College, Krishnankoil (Tamil Nadu), India.
3M. Pallikonda Rajasekaran, Department of Electronics and Communication Engineering, Kalasalingam Academy of Research and Education College, Krishnankoil (Tamil Nadu), India.
4G. Vishnuvarthanan, Department of Biomedical Engineering, Kalasalingam Academy of Research and Education College, Krishnankoil (Tamil Nadu), India.
Manuscript received on 29 November 2019 | Revised Manuscript received on 18 December 2019 | Manuscript Published on 31 December 2019 | PP: 325-330 | Volume-8 Issue-4S2 December 2019 | Retrieval Number: D10731284S219/2019©BEIESP | DOI: 10.35940/ijrte.D1073.1284S219
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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: Diagnosis of Neoplasm is an utmost recurrent and lethal technique for detecting a malignant primary tumor. Imaging techniques empower researchers and medical practitioners to evaluate disorders and activities inside the human brain earlier than performing invasive surgery. Here presents the spotting and detection of brain tumor and pancreatic tumor segmentation and classification progression with several stages DBCWMF algorithm filter with histogram equation, Precise Fuzzy C-segmentation, and SIFT extraction and classification with Sparse representation. These techniques provide a better ability in clinical practices in terms of speed, accuracy, innovation. Experimental results were evaluated using TCIA database and hospital database, where the proposed approaches were verified simultaneously with data progression and incredibly effective for brain and pancreatic tumor in MR images and CT scan images both.
Keywords: Brain Tumor, DBCWMF, Fuzzy C-segmentation, SIFT, Sparse Representation, Pancreatic Tumor.
Scope of the Article: Fuzzy Logics