For segmenting the Region of interest and for analyzing each area separately to locate whether pathologies present in it or not, we use segmentation process as the first step to diagnose lung image using ComputerAided Diagnosis. In this paper, ROI is segmented by using supervised Contextual Clustering in addition to the Region growing algorithm. Accurate segmentation of the lungs from the chest volume is obtained from the Contextual clustering which is better than all other thresholding approaches that are simple. Initial Nodule Candidates can be detected and segmented effectively by contextual clustering which is considered to be the most effective approach when compared to the remaining approaches present.We combine rule-based filtering and a feature based support vector machine using which we can reduce the False-positives (FP) ,custom CNN, Alex net, neuro-fuzzy classifier.
Fast and Adaptive Detection of Pulmonary Nodules in Thoracic CT Images Using a Hierarchical Vector Quantization Scheme
