Computer-aided detection of brain metastases using a three-dimensional template-based matching algorithm

The purpose of this work was to develop an algorithm for detecting brain metastases in magnetic resonance imaging (MRI), emphasizing the reduction of false positives. Firstly, three-dimensional templates were cross-correlated with the brain volume. Afterwards, each lesion candidate was segmented in the three orthogonal views as a previous step to remove elongated structures such as blood vessels. In a database containing 19 patients and 62 brain metastases, detection algorithm showed a sensitivity of 93.55%. After applying the method for false positive reduction, encouraging results were obtained: false positive rate per slice decreased from 0.64 to 0.15 and only one metastasis was removed, leading to a sensitivity of 91.94%.

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