The intracranial hematoma

especially acute intracranial hematoma

is one of intracranial injuries which do harm to human life and health

so accurate segmentation of intracranial hematoma area has significant clinical value. Segmentation of hematoma regional medical images is a key technology to realize intracranial hematoma 3D reconstruction and volume calculation

and the problem with segmentation is how to improve the accuracy. It established a matter-element model for medical images of intracranial hematoma

and proposed a research method which combined extension detecting technology of focusing on matter with the fuzzy C-means (FCM) clustering algorithm

which prevents the FCM clustering algorithm from falling into local optimization in segmentation of intracranial hematoma medical images. Therefore

this method effectively improves the accuracy of segmentation.