Content Based Image Retrieval for Lung CT Slices using Texture Features
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2015, Vol 3, Issue 6
Abstract
Content Based Image Retrieval (CBIR) is used to retrieve the relevant CT slices from the database based on the query CT slice. In the proposed method, the database consists of diseased CT slices of Cavitary TB. The processes involved in the proposed method include preprocessing, segmentation, ROI extraction and slice retrieval. The lung CT slice is segmented using adaptive thresholding and the diseased regions are extracted from the segmented CT slice by Harris corner point detection. The combination of Block Difference of Inverse Probabilities (BDIP) and Tamura feature extraction methods are proposed for the extracted diseased region and the segmented lung. The Euclidean distance measures the similarity between the features of the query CT slice and the database CT slices. Depending on the distance measures, CT slices are retrieved from the database. The performance of the proposed feature extraction methods are calculated using precision and recall parameters for better retrieval of CT slices.
Authors and Affiliations
Anita Titus, M. Bruntha
Keywords
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