Current Volume 5
Lung tumor detection and classification is one of the challenging tasks in medical image processing because of large variation in density, size, location of tumor and low contrast in images. The accuracy of such segmentation system should be high because it directly affects the mortality of humans. Existing classifier yields poor accuracy when volume of input increases. Hence it is more important to derive an algorithm with higher accuracy in lung tumor detection. In the proposed system, the image obtained from CT scan is processed using median filtering to remove noise and artifacts caused during transmission and other environmental facts. Then the filtered image is segmented using watershed segmentation algorithm and pixels are grouped to extract useful information for analysis. Performance of this algorithm is evaluated based on various metrics and value of bit error rate is calculated about 0.0153%. The result of this segmentation algorithm is better than the existing algorithms and also it preserves the edges of an image with minimum error rate.
Lung, CT scan, Lung Tumour, Watershed transformation algorithm and Performance
Arun B. Mathews , Krishna Prasad K "Detection of Lung Tumor Using Watershed Transformation Algorithm-based Image Enhancement" Iconic Research And Engineering Journals Volume 5 Issue 11 2022 Page 34-38
Arun B. Mathews , Krishna Prasad K "Detection of Lung Tumor Using Watershed Transformation Algorithm-based Image Enhancement" Iconic Research And Engineering Journals, 5(11)