Lung cancer diagnosis from CT images using CAD system: a review. (2016)

• Record Type: Journal Article
• Authors: Nithila, Ezhil E.; Kumar, S.S.
• Is Part Of: International journal of biomedical engineering and technology. Volume 21:Number 4(2016)
• Page Start: 311
• Page End: 321
• Publication Date: 2016
• Subjects: computed tomography -- image segmentation -- nodule classification -- lung lesions -- computer-aided detection -- lung cancer -- cancer diagnosis -- CT images -- CAD -- medical imaging -- abnormal pulmonary CT -- image pre-processing -- early diagnosis; Biomedical engineering -- Periodicals; 610.28
• Languages: English
• ISSNs: 1752-6418

Abstract

In medical imaging, Computer-Aided Detection (CAD) aims to improve diagnostic decision, detection performance and nodule detection. Computed Tomography (CT) technology allows us to gain isotropic acquisition of complete chest within a single breath hold. Analysis of data becomes time consuming for manual interpretation. Hence, automation of data of the CT images is necessary. Lesions in lung are potential manifestations of lung cancer, and early detection helps to increase the chance of survival rate. This paper focuses the literature on computer analysis of abnormal pulmonary CT. All these work deals with three main steps: pre-processing, segmentation of nodule candidates and nodule classification. In addition, the challenges, limitations and future directions are discussed.