Automatic acoustic neurinoma operation path planning method based on full-automatic three-dimensional imaging

An acoustic neuroma and surgical path technology, applied in the computer field, can solve problems such as time-consuming, incomplete, quantitative analysis of the optimal surgical trajectory, and complex assessment of expected treatment risks, so as to relieve surgical pressure, reduce preparation time, and reduce The Effect of Surgical Risk

Pending Publication Date: 2021-09-07
ZHEJIANG UNIV OF TECH
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  • Claims
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Problems solved by technology

In some cases, empirical manual correction and optimization of the surgical plan under aseptic conditions and under pressure during the procedure itself, without thorough and quantitative analysi

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  • Automatic acoustic neurinoma operation path planning method based on full-automatic three-dimensional imaging
  • Automatic acoustic neurinoma operation path planning method based on full-automatic three-dimensional imaging
  • Automatic acoustic neurinoma operation path planning method based on full-automatic three-dimensional imaging

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Embodiment Construction

[0023] The present invention will be further described below.

[0024] An automatic planning method for acoustic neuroma surgery path based on fully automatic three-dimensional imaging, comprising the following steps:

[0025] Step 1. Image acquisition and preprocessing: acquire CT, T1, T2, T1 enhanced, MRA, and diffusion MRI sequence images of the patient, and undergo denoising correction;

[0026] Step 2, image registration: take the CT image as a reference, register other images into the CT image, and obtain the transformation matrix of each image;

[0027] Step 3. Tumor extraction and region segmentation: use the data obtained in step 1 to extract the acoustic neuroma using an automated method, and segment the functional areas, skull base vessels, and skull regions inside the brain;

[0028] Step 4, fiber tracking and automatic identification: use the nerve fiber atlas to track and automatically identify fibers;

[0029] Step 5, data fusion: according to the transformati...

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Abstract

The invention relates to an automatic acoustic neurinoma operation path planning method based on full-automatic three-dimensional imaging. The method comprises the following steps of 1) obtaining CT, T1, T2, T1 enhancement, MRA, diffusion MRI sequence images and the like of a patient, performing denoising correction, and registering the images into the same coordinate system; 2) realizing tumor extraction, region segmentation and fiber tracking and automatic identification by using deep learning and a nerve fiber map; 3) estimating a risk value of voxel; 4) generating a candidate path and estimating a path risk value; and 5) optimizing the path and generating a risk map. According to the invention, the preoperative preparation time is reduced, the operation risk is reduced, and the surgical pressure of doctors is relieved.

Description

technical field [0001] The invention relates to the field of computer technology, in particular to an automatic planning method for acoustic neuroma surgery path based on fully automatic three-dimensional imaging. Background technique [0002] Today, precise targeting of tumors, lesions, and anatomical structures with intracerebral probes, needles, catheters, or electrodes based on preoperative CT / MRI scans has become a standard surgical task in stereotaxic neurosurgery. Common stereotaxic neurosurgery procedures may include stereotaxic brain biopsy, treatment of hydrocephalus, aspiration and emptying of deep cerebral hematomas, Ommay catheterization, deep brain stimulation, deep electrode insertion for epilepsy, endoscopic ventricles Internal surgery. In all surgeries, incorrect placement of surgical tools can lead to adverse outcomes such as ineffective treatment, intracranial haemorrhage complications, albeit less frequent, potentially serious neurological sequelae and t...

Claims

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Application Information

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IPC IPC(8): A61B34/10A61B34/20G06T5/00G06T7/00G06T7/11G06T7/33G16H20/40G16H50/30
CPCA61B34/10A61B34/20G16H20/40G16H50/30G06T5/002G06T5/006G06T7/0012G06T7/11G06T7/33A61B2034/107A61B2034/108A61B2034/2065A61B2034/105G06T2207/10081G06T2207/30016G06T2207/30096
Inventor 冯远静潘显波洪晖航曾庆润袁少楠陈升炜蔡正洲蒋陈盛盛轩硕
Owner ZHEJIANG UNIV OF TECH
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