ArticleJournal of medical systems2019
Automatic Detection and Classification of Lung Nodules in CT Image Using Optimized Neuro Fuzzy Classifier with Cuckoo Search Algorithm.
Article in Journal of medical systems, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- A proposed methodology for detecting the malignant potential of pulmonary nodules in sarcoma using computed tomographic imaging and artificial intelligence-based models.Frontiers in oncology · 2023Article
- An Effective Approach for Automated Lung Node Detection using CT Scans.Journal of biomedical physics & engineering · 2022Article
- A Neural Network and Optimization Based Lung Cancer Detection System in CT Images.Frontiers in public health · 2022Article
- Application of Recurrent Neural Network Algorithm in Intelligent Detection of Clinical Ultrasound Images of Human Lungs.Computational intelligence and neuroscience · 2022Article
- Intelligence Classification Algorithm-Based Drug-Resistant Pulmonary Tuberculosis Computed Tomography Imaging Features and Influencing Factors.Computational intelligence and neuroscience · 2022Article
- Robust Keypoint Detection and Matching on Fisheye Images by Self-Supervised Learning.Computational intelligence and neuroscience · 2022Article
- HDEC: A Heterogeneous Dynamic Ensemble Classifier for Binary Datasets.Computational intelligence and neuroscience · 2020Article
- Classification of Lung Nodules Based on Deep Residual Networks and Migration Learning.Computational intelligence and neuroscience · 2020Article
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Authors and funding
2 authors.
Funding
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Abstract
The Lung nodules are very important to indicate the lung cancer, and its early detection enables timely treatment and increases the survival rate of patient. Even though lots of works are done in this area, still improvement in accuracy is required for improving the survival rate of the patient. The proposed method can classify the stages of lung cancer in addition to the detection of lung nodules. There are two parts in the proposed method, the first part is used for classifying normal/abnormal and second part is used for classifying stages of lung cancer. Totally 10 features from the lung region segmented image are considered for detection and classification. The first part of the proposed method classifies the input images with the aid of Naive Bayes classifier as normal or abnormal. The second part of the system classifies the four stages of lung cancer using Neuro Fuzzy classifier with Cuckoo Search algorithm. The results of proposed system show that the rate of accuracy of classification is improved and the results are compared with SVM, Neural Network and Neuro Fuzzy Classifiers.
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