Andere Kunden interessierten sich auch für
![Erkennung und Klassifizierung von Lungentumoren]( "Erkennung und Klassifizierung von Lungentumoren")
Erkennung und Klassifizierung von Lungentumoren39,90 €![Automated Lung Cancer Detection System using Image Segmentation]( "Automated Lung Cancer Detection System using Image Segmentation")
Automated Lung Cancer Detection System using Image Segmentation23,99 €![Benign Malignant Classification of Lung Nodules using Machine Learning]( "Benign Malignant Classification of Lung Nodules using Machine Learning")
Benign Malignant Classification of Lung Nodules using Machine Learning67,99 €![Tumor Growth Prediction Using Parallel Computing]( "Tumor Growth Prediction Using Parallel Computing")
Tumor Growth Prediction Using Parallel Computing44,99 €![Brain Tumor Segmentation Methods]( "Brain Tumor Segmentation Methods")
Brain Tumor Segmentation Methods51,99 €![BRAIN TUMOR CLASSIFICATION INTO HIGH AND LOW GRADE GLIOMAS]( "BRAIN TUMOR CLASSIFICATION INTO HIGH AND LOW GRADE GLIOMAS")
BRAIN TUMOR CLASSIFICATION INTO HIGH AND LOW GRADE GLIOMAS33,99 €![LUNG DISEASES PREDICTION BY PATTERN CLASSIFICATION AND SEGMENTATION]( "LUNG DISEASES PREDICTION BY PATTERN CLASSIFICATION AND SEGMENTATION")
LUNG DISEASES PREDICTION BY PATTERN CLASSIFICATION AND SEGMENTATION30,99 €
Lung cancer is a leading reason of death worldwide it refers to the uncontrolled growth of abnormal cells in the lung. If not treated, this growth can spread past the lung by procedure of metastasis into close-by tissue and different parts of the body. The image processing methods are used commonly in various medical areas for improving prior detection and treatment stages, in which the time span or elapse is very important to identify the disease in the patient as possible as fast, especially in many tumors. The proposed method uses first detection of lung mass tissue uses segmentation with filtering, morphological operation etc. Geometrical features Extraction technique is used for calculating statistical features. At last classification and prediction is done by using the geometrical features are merged with Machine Learning classifier. Results of the classification gives, whether the CT Image is a normal Image or cancerous.