A Brain Tissue Surface Deformation Estimation Method Based on Local Key Geometric Information

Abstract

The invention belongs to the technical field of medical image processing, in particular to a brain tissue surface deformation estimation method based on local key geometric information. The method of the invention includes: extracting target brain tissue from preoperative images and performing three-dimensional reconstruction, extracting the surface point set of the target brain tissue; obtaining the deformed brain tissue surface point set data and texture image through a three-dimensional scanner. The three-dimensional sulcus and gyri point set of the brain tissue surface point set was extracted, and the sulcus and gyri features on the two-dimensional texture image were extracted. Through the mapping relationship between the two-dimensional sulcus and gyri features and the corresponding three-dimensional sulcus and gyri features, the intraoperative three-dimensional sulcus and gyri point set was obtained. The rigid registration method is used to compensate the lateral displacement of the brain tissue surface during the operation, and the non-rigid registration method based on the feature enhancement of the sulcus gyrus is used to obtain the corresponding relationship between the three-dimensional point sets on the brain tissue surface before and after deformation, and calculate the brain tissue surface point set displacement field. The invention can be used for estimating the deformation degree of the brain tissue surface during the operation, and greatly improves the precision of the operation navigation.

Description

technical field [0001] The invention belongs to the technical field of medical image processing, and in particular relates to a brain tissue surface deformation estimation method based on local key geometric information. Background technique [0002] Studies have shown that brain tissue deformation often occurs during neurosurgery. Taking neurosurgical navigation as an example, after the dura mater is opened, the brain tissue will be deformed due to factors such as gravity, loss of cerebrospinal fluid, and brain tissue resection, resulting in the intraoperative position of the brain tissue structure being inconsistent with the previously determined position based on preoperative images. Intraoperative brain tissue deformation can cause navigation and positioning errors and reduce navigation accuracy. Methods to compensate for brain tissue deformation errors can be divided into intraoperative imaging-based methods and biomechanical model-based methods. Intraoperative imagin...

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Problems solved by technology

[0004] The main disadvantage of texture information-based methods is that preoperative texture image acquisition or generation is difficult, so this type of method can only be used to estimate brain tissue between two intraoperative time points (such as before and after resection) after the start of surgery. surface displacement, and the brain tissue surface displacement between these two time points preoperatively and intraoperatively could not be calculated

Due to the lack of registration constraints of local key geometric information, these methods are difficult to accurately find the correspondence between point pairs, especially when the brain tissue undergoes a large deformation, it is impossible to accurately track the brain tissue deformation.

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