SURVEY ON LUNG NODULE CLASSIFICATIONS

Ravivarman.R, Sasirekha.N

Abstract: This paper proposes a survey on the classification techniques of lung nodules. We have the different classifications about the nodules in the lungs. It contains the different methods of classification, segmentation and detection techniques. Malignant cell presented in the lungs named , nodules are classified for the treatment processes. Thresholding and Robust segmentation techniques are used in the segmentation process and the feature set is used for classification. Low Dose CT(Computed Tomography) images are applied. This survey has the information about the efficient techniques which are all used for the nodule classification. In these days lung cancer is the dangerous dead disease in the world, So we need to have the knowledge of that cancer. In starting stages the micro nodules are then formed into a cancer cell. Among the cancer affected population about 20% of the people are dead due to lung cancer. If nodules are found in a starting stage, we can be extend the lifetime of the patient. The main process of this paper involves with the nodule classification and segmentation process of the lung nodules. Here we taken the different procedures involved with nodule detections. CT is the most appropriate imaging technique to obtain anatomical information about lung nodules and the surrounding structures. Here we taken the Low Dose CT(LDCT) images for operations. This paper has the various approaches of the nodule classification. In this survey different techniques are presented which are used for detection and classification of the nodules in the lungs. By differentiating the nodules from the anatomical parts of the lungs, the nodules are identified.

Keywords: PLSA, Robust Segmentation and Partitioning.

DOI: https://doi.org/10.15623/ijret.2015.0401056