Although volumetric assessment of intracerebral hemorrhage (ICH) plays a key role for clinicians to make optimal treatment decisions and predict prognosis of ICH patients, qualitative assessment of neuroradiologists in reading brain CT images is not accurate and has large interreader variability. To overcome this clinical challenge, this study develops and tests a new interactive computer-aided detection (ICAD) tool to quantitatively assess hemorrhage volumes. A retrospectively assembled dataset including 200 patients with ICH was collected for this study. After loading each case, the ICAD tool first segments intracranial brain volume, performs CT labelling of each voxel, then contour-guided image-thresholding techniques based on CT Hounsfield Unit is used to estimate and segment hemorrhage-associated voxels (ICH). Next, two experienced neurology residents examine and corrects the markings of ICH categorized into either intraparenchymal hemorrhage (IPH) or intraventricular hemorrhage (IVH) to obtain the true markings. Additionally, volumes and maximum two-dimensional diameter of each sub-type of hemorrhage were also computed for understanding ICH prognosis. The performance to segment hemorrhage regions between semi-automated ICAD and the verified neurology residents’ true markings was evaluated using dice similarity coefficient (DSC). Data analysis results show that median and [interquartile range] of DSC are 0.96 [0.91, 0.98], 0.97 [0.93, 0.99], 0.92 [0.83, 0.97] for ICH, IPH and IVH, respectively. Thus, this study demonstrates that the new ICAD tool enables to segment and quantify ICH and other hemorrhage volume with higher DSC, which has potential to quantify ICH in future clinical practice.
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