Segmentation And Analysis Of Interstitial Lung Disease Pattern In HRCT Images And Disease Classification By K- Means

2017 International Journal of Recent Trends in Engineering and Research  
automated segmentation of pathological bearing region is the first step towards the development of lung CAD. Most of the work reported in the literature related to automated analysis of lung tissue aims towards classification of fixed sized block into one of the classes. This block level classification of lung tissues in the image never results in accurate or smooth boundaries between different regions. In this work, effort is taken to investigate the performance of the automated image
more » ... ion or clustering algorithm that results in smooth boundaries among lung tissue patterns commonly encountered in microscopic images of the thorax. A public database that consists of HRTC images taken from patients affected with Interstitial Lung Diseases (ILDs) is used for the evaluation. The K-means algorithm is used here to find the clusters. The performance of Kmeans algorithm is evaluated for varied value of K (number of clusters) and its effect is studied.
doi:10.23883/ijrter.2017.3148.zvbb7 fatcat:d24dakke3feubpuspwiaajpsda