Brain Metastases Detection Algorithms in Magnetic Resonance Imaging


Early detection of brain metastases increases survival in patients with cancer, since image-guided radiosurgery is the most widely used treatment. As support for the qualitative diagnosis created by radiologists, Laptop Assisted Diagnosis provides a quantitative and reproducible analysis. This article reviews the methods for an automatic detection of brain metastases in distinction-enhanced T1-weighted magnetic resonance imaging. Model-based strategies detect metastases thanks to their high degree of similarity with models representing their morphology, mainly templates. On the other hand, strategies based on brain symmetry and intensity search intensity differences between both brain hemispheres with respect to the symmetry axis. Model-primarily based methods are a lot of commonly used as a result of they allow the detection of metastases of a wider range of measures.

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