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Segmentation of head CT-scan to calculate percentage of brain hemorrhage volume

机译:分割头部CT扫描以计算脑出血量的百分比

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Brain hemorrhage is a serious category of head injury that can have a fatal impact on brain function and performance. But sometimes the identification of cerebral hemorrhage can not be known immediately. So far, the identification of cerebral hemorrhage is done through CT Scan image observation that requires special skills. Therefore we need a certain method that can segment the CT Scan image quickly and automated. The goal is to obtain the image segmentation of brain bleeding more quickly and accurately. So patients with cerebral hemorrhage can immediately obtain medical treatment in accordance with the needs. The preprocessing process of CT Scan image starts from the preprocessing phase of the CT Scan image using color filtering, erosion and dilation methods. This stage is done to clarify the cerebral hemorrhage and eliminate the noise contained in the image. Then performed watershed and cropping segmentation to separate the skull bones of the skull with brain tissue. The next step is to improve the image quality using median filtering. Then the image is again segmented using the threshold method to separate the image of cerebral hemorrhage as the observed object. Last performed the calculation of area and volume percentage of bleeding in the brain. From the system test obtained the calculation of brain area has an average error of 1.13%. As for the test calculation of the area of bleeding has an average error of 11.17%.
机译:脑出血是严重的颅脑损伤,可能对脑功能和性能产生致命影响。但是有时无法立即知道脑出血的识别。到目前为止,脑出血的识别是通过需要特殊技能的CT扫描图像观察来完成的。因此,我们需要一种可以快速自动分割CT扫描图像的方法。目的是更快速,准确地获得脑出血的图像分割。因此脑出血患者可以根据需要立即就医。 CT扫描图像的预处理过程从CT扫描图像的预处理阶段开始,即使用彩色过滤,腐蚀和膨胀方法。进行此阶段是为了澄清脑出血并消除图像中包含的噪声。然后进行分水岭和裁剪分割,以将颅骨的颅骨与脑组织分开。下一步是使用中值滤波来改善图像质量。然后,再次使用阈值方法对图像进行分割,以分离出脑出血的图像作为观察对象。最后执行了脑出血面积和体积百分比的计算。从获得的系统测试中计算出的大脑区域的平均误差为1.13%。至于试验计算的出血面积,平均误差为11.17%。

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