Computer Aided Diagnosis Model for Lung Cancer Prediction using Gabor Filtering with Artificial Neural Networks
| Main Author: | Shankar, K |
|---|---|
| Format: | Article Journal |
| Bahasa: | aig |
| Terbitan: |
, 2020
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/4743812 |
Daftar Isi:
- Lung cancer becomes a critical disease in human nowadays, and it leads to mortality in many cases. However, the early diagnosis can save the life and increases the patient’s life significantly. Thus, the CT scan is one of the techniques which are used in vital field of imaging in medical areas. This paper provides the novel computer aided diagnosis (CAD) method for finding the lung cancer in the early stages both in male and female. The presented model undergoes Gabor filtering (GF) technique to preprocess the input images to remove the noise exist in it. In addition, watershed based segmentation technique is employed to determine the harmful areas of the lungs from the CT images. At last, gray level co-occurrence matrix (GLCM) is used for feature extraction and artificial neural networks (ANN) is utilized as a classification. The proposed method is tested and implemented by the use of CT scans image of lungs and it shows the Gabor filter shows the better results and the GLCM-ANN model has led to enhanced diagnostic outcome with higher accuracy of 92.89%.