Brain tissue surface deformation estimation method based on local key geometrical information

Abstract

The invention belongs to the technical field of medical image processing, and particularly relates to a brain tissue surface deformation estimation method based on local key geometrical information. The method comprises the following steps: extracting a target brain tissue from a preoperative image, carrying out three-dimensional reconstruction, and extracting a target brain tissue surface point set; and obtaining deformed brain tissue surface point set data and a texture image through a three-dimensional scanner; extracting a three-dimensional channeling point set of the brain tissue surfacepoint set, extracting channeling features on the two-dimensional texture image, and obtaining an intraoperative three-dimensional channeling point set through a mapping relationship between the two-dimensional channeling features and the corresponding three-dimensional channeling features. A rigid registration method is used for compensating transverse displacement of the surface of brain tissue in an operation, a non-rigid registration method based on channeling feature enhancement is used for obtaining the corresponding relation of three-dimensional point sets of the surface of the brain tissue before and after deformation, and a displacement field of the point sets of the surface of the brain tissue is calculated. The method can be used for estimating the deformation degree of the braintissue surface in an operation, and the operation navigation precision is greatly improved.

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] Research has shown that deformation of brain tissue often occurs during neurosurgery. Taking neurosurgical navigation surgery 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 a discrepancy between the intraoperative position of the brain tissue structure and the position determined based on the preoperative image. Intraoperative brain tissue deformation will cause navigation positioning errors and reduce navigation accuracy. Methods to compensate for brain tissue deformation errors can be divided into methods based on intraoperative imaging and methods based on biomechanical models. The method b...

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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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