Segmentation of Multi-Tumor from PET/CT Images
K. Shruthi1, V. Vivekitha2, S. Syed Althaf3, G. Gnancy Subha4
1K. Shruthi, Assistant Professor, Department of Biomedical Engineering, St. Peter’s Institute of Higher Education and Research, Chennai (Tamil Nadu), India.
2V. Vivekitha, Assistant Professor, Department of Biomedical Engineering, Velalar College of Engineering and Technology, Erode (Tamil Nadu), India.
3S. Syed Althaf, Assistant Professor, Department of Biomedical Engineering, St. Peter’s Institute of Higher Education and Research, Chennai (Tamil Nadu), India.
4G. Gnancy Subha, Assistant Professor, Department of Biomedical Engineering, Salem College of Engineering and Technology, Salem (Tamil Nadu), India.
Manuscript received on 07 December 2019 | Revised Manuscript received on 21 December 2019 | Manuscript Published on 31 December 2019 | PP: 170-176 | Volume-8 Issue-12S2 October 2019 | Retrieval Number: L103010812S219/2019©BEIESP | DOI: 10.35940/ijitee.L1030.10812S219
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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: The aim of the project is to develop a methodology for automatic segmentation of multiple tumor from PET/CT images. Image pre-processing methods such as Contrast Limited Adaptive Histogram Equalization (CLAHE), image sharpening and Wiener filtering were performed to remove the artifacts due to contrast variations and noise. The image was segmented using K-means, Threshold segmentation, watershed segmentation, FCM clustering Segmentation, Mean shift Clustering Segmentation, Graph Cut Segmentation. Evaluation was made for the segmentation against the Ground Truth. Various Features was selected and extracted. Classification was made using SVM classifier and KNN classifier to classify the tumor as benign or malignant. The proposed method was carried out using PET/CT images of lung cancer patients and implemented using MATLAB.
Keywords: CLAHE, Graph Cut, MATLAB.
Scope of the Article: Image Security