Ishaan Gupta
Vol. 7, Issue 1, Jan-Jun 2019
Abstract:
The growing and multiplying of abnormal cells and tumours cause lung cancer. Recently, it has been seen that image enhancement is widely used in the medical field for the early detection of diseases. Time plays an important role in extracting anomalies in testing pictures. These are highly associated with lung disease and breast cancer. In our recommended technique, in the initial phase, we detect lungs. Our proposed method follows some steps to make the image more readable by applying pre-processing, image enhancement, binarization, thresholding, and marker-controlled watershed extraction. In the main stage, the Binarization procedure changes over two-fold pictures and afterwards contrasts them and limited-esteems to detect lungs nodule disease. In the subsequent step, the marker-controlled watershed segmentation is performed to section the lung CT pictures. The presentation of the proposed framework shows satisfactory outcomes, and the proposed technique has an accuracy of 97%.
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