A simple multi-feature based stereoscopic medical image retrieval system

What is it about?

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).

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Why is it important?

Stereoscopic image retrieval (SIR) is considered as one of the most challenging works since they involve the nature of imaging device, modality, and complexity, and comparatively few works have been reported. The main objective of this research work is to develop a novel stereoscopic medical image retrieval system which can be used to provide a vital clinical decision making support to radiologists.