This technology is an algorithm that performs automatic segmentation and analysis of head computed tomography (CT) scans to evaluate brain injury following intracerebral hemorrhage.
Following intracerebral hemorrhage, the extent of neurological injury can be determined by measuring the edema of the affected brain regions. For these measurements, the segmentation of CT scans is often carried out manually, which is time-consuming and possibly inaccurate, preventing rapid and unbiased evaluation of brain hemorrhage.
This technology is a software that automatically analyzes head CT scans to evaluate the extent of intracerebral hemorrhage. Using a deep convolutional neural network, this algorithm performs unbiased segmentation and analysis of CT scans, allowing for rapid and accurate volumetric quantification of the hematoma and edema in the brain. As such, by eliminating the need for manual image analysis, this technology can greatly facilitate the diagnosis and treatment of patients with spontaneous intracerebral hemorrhage.
Natasha Tireni Louise Ironside
IR CU17284
Licensing Contact: Jerry Kokoshka