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Retrieval of intracranial hemorrhages in computed tomography brain images using binary coherent vector

We investigate the use of a new binary coherent vector approach, integrated in a proposed content-based medical retrieval (CBMIR) system, to retrieve computed tomography (CT) brain images. Five types of hemorrhages consisting of 150 plain axial CT brain images are queried from a database of 2500 normal and abnormal CT brain images. Possible combinations of shape features are portrayed as feature vectors and are evaluated based on precision-recall plots. Solidity, form factor, equivalent circular diameter (ECD), and Hu moment are proposed as identifying features of intracranial hemorrhages in CT brain images. In addition to identifying hemorrhages, the proposed approach significantly improves the CBMIR system performance. This retrieval system can be widely useful due to rapid development in computer vision and computer database management, both of which motivated this application of CBMIR.