A simple multi-feature based stereoscopic medical image retrieval system

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This paper describes a method of retrieving stereoscopic medical images from the database that consists of feature extraction, similarity measure, and re-ranking of retrieved images. This method retrieves similar images of the query image from the database and re-ranks them according to the disparity map. The performance is evaluated using the metrics namely average retrieval precision (APR) and average retrieval rate (ARR). According to the performance outcomes, the multi-feature based image retrieval using Mahalanobis distance measure has produced better result compared to other distance measures namely Euclidean, Minkowski, the sum of absolute difference (SAD) and the sum of squared absolute difference (SSAD). Therefore, the stereo image retrieval systems presented has high potential in biomedical image storage and retrieval systems.

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Journal information
Impact Factor

CiteScore 2018: 0.38

ICV 2017 = 103.49

SCImago Journal Rank (SJR) 2018: 0.132
Source Normalized Impact per Paper (SNIP) 2018: 0.303

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