• Naveena Karunakaran
• Nishy Reshmi.S

Abstract— Lung cancer is a disease of abnormal cells multiplying and growing into a tumor. Recently, image processing techniques are widely used in several medical areas for image improvement in earlier detection and treatment stages, where the time factor is very important to discover the abnormality issues in target images, especially in various cancer tumors such as lung cancer. The main aim is to detect nodules that overlap with ribs and/or clavicles and to reduce the frequent false positives (FPs) caused by ribs. Thus image quality and accuracy are also the core factors of this research. In CXRs the ribs and clavicles are suppressed with massive-training artificial neural networks (MTANNs). To reduce rib-induced FPs and detect nodules overlapping with ribs, we incorporated the VDE technology. The VDE technology suppressed rib and clavicle opacities in CXRs while maintaining soft-tissue opacity by use of the MTANN technique that had been trained with real dual-energy imaging. Our scheme detected nodule candidates on VDE images by use of a morphologic filtering technique. Therefore, by use of VDE technology, the sensitivity and specificity for detection of nodules, especially subtle nodules, in CXRs were improved substantially.

Cancer detection, CADe scheme, suppressing ribs, MTANN

"Survey on Computerized Lung Segmentation and Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.2, Issue 7, page no.3203-3205, July-2015, Available :http://www.jetir.org/papers/JETIR1507038.pdf

"Survey on Computerized Lung Segmentation and Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.2, Issue 7, page no. pp3203-3205, July-2015, Available at : http://www.jetir.org/papers/JETIR1507038.pdf