Current systems for computer-aided detection have been introduced as complementary tools that draw the radiologists' attention to certain image areas that need further evaluation. CAD is being applied widely in the detection and differential diagnosis of many different types of abnormalities in medical images obtained in various examinations by use of different imaging modalities. In fact, CAD has become one of the major research subjects in medical imaging and diagnostic radiology. In this book a Computer Aided Diagnosis tool for identification of lung nodules in DICOM Lung CT images is designed primarily based on morphological approaches that are validated in the presence of different types of noise. The Morphology based approach helps in reducing the computational complexity and thus reduces the processing time. The tool provides seamless integration of identification, detection, and quantification of Lung Nodules by providing a simple and effective Graphical User Interface.