CAD system plays a major role in assisting the radiologists in diagnosing the lung cancer nodules. However, the existing detection and extraction algorithms in CAD systems endure accuracy issues as it yields more number of false positives. Thus, comprehending the importance of CAD systems, algorithms for efficiently isolating the INC and extraction with high accuracy are of great interest. Automated detection of lung nodules includes detection of isolated nodules, juxta-pleural nodules, juxta-vascular nodules, and pleural-tail. The existing algorithms [1, 2] fail to detect lung nodules attached to lung walls and blood vessels more accurately. Hence, there is need to design an automated system for accurate identification of nodules. In this direction, a new automated algorithm method is proposed to detect lung nodules based on boundary estimation and surface analysis.