Delineation of Intracerebral Hemorrhage from Clinical Non-Enhanced Computed Tomography Images

We delineated intracerebral hemorrhage (ICH) from clinical non-enhanced computed tomography (NCT) images through large grayscale, large grayscale asymmetry with respect to the midsagittal plane (MSP), and large grayscale local contrast. An adaptive approach is proposed to determine thresholds of the 3 features and adjust the window width for data conversion. The substantial grayscale variability of ICH for a subject is addressed by finding the bright portion followed by recovering. Those ICH voxels symmetrical to the MSP are recovered, partial volume effects are compensated and the non-ICH high grayscale regions are excluded. The algorithm is fast, and has been validated (37 cases) to yield a delineation accuracy of 0.915 and qualitatively (altogether 161 cases) with good results. The developed system could be a useful tool to aid quantifying ICH and enhancing stroke therapy.