RESUMO
Changing the human being's lifestyle, has caused, or exacerbated many diseases. One of these diseases is cancer, and among all kind of cancers like, brain and pulmonary; lungs cancer is fatal. The cancers could be detected early to save lives using Computer Aided Diagnosis (CAD) systems. CT scans medical images are one the best images in detecting these tumors in lung that are especially accepted among doctors. However, location and random shape of tumors, and the poor quality of CT scans images are one the biggest challenges for physicians in identifying these tumors. Therefore, deep learning algorithms have been highly regarded by researchers. This paper presents a new method for identifying tumors and pulmonary nodules in CT scans images based on convolution neural network algorithm with which tumor is accurately identified. The active counter algorithm will show the detected tumor. The proposed method is qualitatively measured by the sensitivity assessment criteria and dice similarity criteria. The obtained results with 98.33% accuracy 99.25% validity and 98.18% dice similarity criterion show the superiority of the proposed method.
