Lung Cancer Detection on Computed Tomography Images Using Digital Image Processing Techniques

Maruthi Rohit Ayyagari and Gulshan Kumar

Image processing is a vast technology, which can be adopted in various fields. It is also widely used in medical areas because it is extremely important for practitioners to identify the disease in its early stages to get the treatment done. In this paper, we have presented an automated detection system that performed over CT (Computed Tomography) scanned images to discover the specific Lung Cancer stage in patients. Lung cancer is one of the deadliest and known cancers around the world. The nodules are classified into small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC). Our system is capable of detecting the tumour in its early and advanced stages; also, our system is designed in a way in which it can also identify the particular stage of cancer and can detect small cell and non-small cell lung tumours. The system works in four phases; namely, pre-processing, image enhancement, image segmentation and classification. Our system has been experimented and tested over 258 images from a public dataset of 12,645 images, a dataset of 50 patients provided by VIA and I-ELCAP. 94.92% sensitivity and zero false positive acceptances have been achieved with the proposed system.

Volume 11 | 04-Special Issue

Pages: 677-689