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Intensified Computer Aided Detection System for Lung Cancer Detection using MEM algorithm
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| Author:
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SAJEEV RAM, K.KALAIVANI, ARUN SAHAYADHAS, SHYLAJA C S
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| Abstract:
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Medical image processing plays an important role in treatment planning, detection of disease and guidelines for surgical treatment. One of the mortal and life taking disease all around the world is lung cancer. Timely perception helps in declining the probity rate and improves the patient’s chance of endurance. However, Computed Tomography (CT) scan is used in medical field to envisage the point of tumour in the body; it is thorny for doctors to find the cancer cells from CT images. Therefore, Computer Aided Detection (CAD) system is used by the doctors to predict cancerous cells accurately. In the proposed method, image preprocessing techniques is used such as median filter for noise removal, MEM algorithm is used for image segmentation and then feature extraction extracts wary region of interest of lung nodule. Finally, SVM classification technique is used for detecting lung cancer.
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| Keyword:
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Lung Nodule, Adaptive Thresholding, Markov Random Field (MRF), SVM Classifier, Expectation Maximization (EM) algorithm.
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| EOI:
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-
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| DOI:
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https://doi.org/10.31838/ijpr/2020.12.02.0070
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| Download:
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