American Journal of Computer Science and Engineering Survey Open Access

  • ISSN: 2349-7238
  • Journal h-index: 9
  • Journal CiteScore: 1.72
  • Journal Impact Factor: 1.11
  • Average acceptance to publication time (5-7 days)
  • Average article processing time (30-45 days) Less than 5 volumes 30 days
    8 - 9 volumes 40 days
    10 and more volumes 45 days

Abstract

Lung Nodule Retrieval by Integrating Local Binary Pattern with Template Matching

G. Deep, L. Kaur and S. Gupta

Lung Nodule Retrieval by Integrating Local Binary Pattern with Template Matching

This paper focuses on the use of local binary pattern (LBP) in template matching for nodule retrieval from CT lung images. Existing local binary pattern operators uses the features of LBP to train the classifiers for the classification of lung nodules, here LBP method is used for the extraction of features from lung nodule images. In this work, LBP method is applied on both the lung images as well as on nodule templates to extract LBP features. The resulting features are compared to extract the cancerous nodules. Experiments are performed on the lung data sets collected from LIDC database. The results show that use of LBP features in template matching yields better accuracy rate as compared to the literature.