Computer aided diagnosis in digital pathology application: Review and perspective approach in lung cancer classification

This electronic document is a “live” template and already defines the components of your paper [title, text, heads, etc.] in its style sheet This paper provide a broad review for most important algorithms used in the CAD application for lung tissue diagnostics and highlighted the performance of each distinctive algorithm. Moreover, ROC characteristics have been made for each selected algorithms (support vector machine (SVM), Fuzzy C-mean (FCM), Conventional Neural network (CNN) and CAD-FCM). The features for each algorithm discussed and related performance in clinical aided diagnosis (CAD) discussed and explained. Moreover, comparison of different research groups has been made to spotlight each criterion for different algorithms and approach used in CAD platforms in lung cancer. Finally, limitation and constrains for these algorithms has been discussed in order to optimize performance for each of these algorithms.