Cerebrovascular atlas construction method

A construction method and cerebrovascular technology, applied in neural architecture, image enhancement, image analysis, etc., can solve problems such as poor segmentation, influence of network model training, and heavy workload

Pending Publication Date: 2020-11-24
ZHEJIANG UNIV OF TECH
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Problems solved by technology

[0005] In order to overcome the shortcomings of the current cerebrovascular segmentation technology that relies too much on the operation of medical researchers and has strong subjectivity, the blood vessel segmentation based on deep learning in the present invention has a large workload in the process of data segmentation and patching, and cuts Poor points can easily have a great impact on network model training

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  • Cerebrovascular atlas construction method
  • Cerebrovascular atlas construction method
  • Cerebrovascular atlas construction method

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Embodiment Construction

[0040] specific implementation plan

[0041] The present invention will be further described below.

[0042] refer to Figure 1 ~ Figure 4 , a method for constructing a cerebrovascular atlas, comprising the following steps:

[0043] Step 1: Data preprocessing and labeling, the process is as follows:

[0044] First, denoise the MRA data, then use the BET tool in FSL to perform skull removal, then mark the processed data with a label, and finally divide the training set and test set according to the number of data;

[0045] Step 2: The image data is divided into image blocks, and the process is as follows:

[0046] Since the 3D MRA data is too large, it is necessary to select the appropriate patch size and stride to segment the data; then select the patch with a large proportion of vascular voxels in the patch as the main training data input network to ensure the reliability of the data and exclude vascular voxels The impact of patches with very low content on the network grea...

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Abstract

The invention discloses a cerebrovascular atlas construction method. The method comprises preprocessing and labeling the MRA data; screening required patches through an algorithm in the data segmentation process; inputting the data into a variant U-Net network for training and prediction; converting a data set of obtained prediction results into the same coordinate system through registration, calculating the similarity, and allocating the data set to a corresponding feature space, and constructing a cerebrovascular atlas. Blood vessels can be automatically segmented only by preprocessing thenew MRA blood vessel sample data and carrying out coordinate conversion on the atlas. According to the method, the calculated amount is greatly reduced in data segmentation, the blood vessel atlas making method is provided, the subjectivity of manual operation of a traditional method is solved, and rapid, simple, accurate and automatic segmentation of cerebral vessels is achieved.

Description

technical field [0001] The invention relates to medical image segmentation, in particular to a method for constructing a cerebrovascular atlas. Background technique [0002] Research data show that cerebrovascular disease has become the disease with the highest fatality rate. Cerebrovascular segmentation is an important topic in medical image analysis because cerebrovascular is crucial for diagnosis, treatment planning and execution, and evaluation of clinical outcomes in different fields such as neurosurgery and cardiovascular and cerebrovascular diseases. The importance and location specificity of cerebral vessels pose challenges to the accuracy of its segmentation and the reliability of the results. [0003] Even if the automatic or semi-automatic segmentation method saves a lot of manual operations, at least one clinician is still required to conduct preliminary segmentation or evaluate the segmentation results. With the rise of deep learning research, many researchers...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00G06T7/11G06N3/04G06K9/62
CPCG06T5/002G06T7/11G06T2207/30101G06T2207/30016G06N3/045G06F18/23G06F18/22G06F18/214
Inventor 冯远静谢雷陈余凯盛轩硕
Owner ZHEJIANG UNIV OF TECH
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