Detection and Localization of Early-Stage Lung Tumor Using K-Means Clustering and Object Counting

Lung tumor is a complex disease that occurs due to the abnormal growth of lung cells. For efficient treatment planning, earlier detection of tumor is necessary. Computer-Aided Determination (CAD) can be nearly as viable advertisement twofold perusing by giving a moment conclusion to the radiologist and offer assistance in expanding the affectability and exactness of discovery. The mechanized Division with earlier models or utilizing earlier information is troublesome to actualize. The flawless Division of inside structures of the lung is of incredible eagerness to ponder and treat tumors. The proposed Lung Tumor location calculation comprises four stages: Pre-processing, Division, Include extraction and Classification. Major steps in pre-processing are made strides colour based histogram equalization. A novel calculation for lung MRI division utilizing adjusted colour-based K-mean clustering proposed in this work.