CT lung image classification systems - a systematic review

P.B.Edwin Prabhakar¹, Sivasubramanian¹, N. Kalyana Sundaram¹, S.Subburam¹, N. Sundara Rajulu²

¹ Department of .Computer Science And Engineering, New Prince Shri Bhavani College of Engineering & Technology, Chennai, Tamil Nadu, India

² Department of Information Technology, Excel Engineering college Coimbatore Highways,Namakkal, Tamil Nadu, India

Abstract

Computer Aided Detection (CAD) and diagnostic technologies and their application have emerged in the last decade. CAD applications have concentrated on identification of the region of interest, for example nodules in the lung in the images, and analysis of the characteristics of objects. CAD technologies take advantages of computer systems as well as image processing and analysis techniques to overcome perceptual and interpretive errors caused by radiologists in the process of image observation and interpretation. This fact is inevitable in the context of medical practice since experience of image readers may vary and each observer (such as a radiologist) has a unique visual search on an image. Furthermore, there are always inter and intra observer variability for interpretation of an image. To overcome these difficulties, different CAD systems are developed for medical image analysis. This paper presents a systematic review on different CAD systems for lung cancer classification using computed tomography images.

Imprint

P.B.Edwin Prabhakar, Sivasubramanian, N. Kalyana Sundaram, S.Subburam, N. Sundara Rajulu. CT LUNG IMAGE CLASSIFICATION SYSTEMS - A SYSTEMATIC REVIEW. Cardiometry; Issue 25; December 2022; p.1113-1117; DOI: 10.18137/cardiometry.2022.25.11131117; Available from: https://www.cardiometry.net/issues/no25-december-2022/lung-image

Keywords

Lung cancer, Computer aided diagnosis, Computed tomography images, Medical image analysis

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