In this work, we propose to take advantage of improved contrast seen on magnetic resonance (MR) images of patients with acute spontaneous intracerebral haemorrhage (SICH), and introduce an automated algorithm for haematoma and oedema segmentation from these images. To our knowledge, there is no previously proposed segmentation technique for SICH that utilises MR images directly. The method is based on k-means clustering of image intensities for haematoma segmentation and voxel-wise dynamic thresholding of hyper-intensities for oedema segmentation. Preliminary results using the Dice score metric to measure segmentation overlaps between labellings yielded by the proposed algorithm and five different expert raters show that our technique has the potential to be an effective way to automatically delineate haematoma and perihaematoma oedema extent directly from MR images.
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