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Automatic segmentation method for highly-adhered and multi-size brain neurons based on point marking

A technology for automatic segmentation of brain neurons, applied in the fields of computer science and biomedicine, can solve the problem of inability to segment high-density and multi-size neurons, and achieve the effect of shortening the segmentation time

Pending Publication Date: 2021-08-10
XIAN UNIV OF TECH
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Problems solved by technology

[0003] The purpose of the present invention is to provide a highly cohesive and multi-size brain neuron automatic segmentation method based on point markers, which solves the problem of being unable to segment high-density and multi-size neurons in the whole brain in the prior art

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  • Automatic segmentation method for highly-adhered and multi-size brain neurons based on point marking
  • Automatic segmentation method for highly-adhered and multi-size brain neurons based on point marking
  • Automatic segmentation method for highly-adhered and multi-size brain neurons based on point marking

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Embodiment Construction

[0102] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0103] The database used in the present invention comes from the microscopic image of macaque brain tissue provided by the French Agency for Atomic Energy and Alternative Energy (CEA). The present invention uses 7200 images (each image size is 512×512 pixels) in the tissue microscopic image (about 145GB) of the 91st brain coronal slice.

[0104] The present invention is a highly cohesive and multi-size brain neuron automatic segmentation method based on point markers. The flow chart is as follows figure 1 As shown, the specific steps are as follows:

[0105] Step 1. Establish a database, randomly divide the database into a training set and a test set, and mark the position of the neuron centroid;

[0106] Step 1 is as follows:

[0107] Randomly select N images from the M images in the database as the training set, and use the remaining M-N...

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Abstract

The invention discloses an automatic segmentation method for highly-cohesive and multi-size brain neurons based on point marking, and the method comprises the following steps: establishing a database, randomly dividing the database into a training set and a test set, and marking the centroid positions of neurons; carrying out preprocessing to obtain a normalized training set image and a test set image, and taking the neuron centroid probability graph as a training set truth value graph and a test set truth value graph; constructing a parallel multi-receptive-field convolutional neural network, predicting the probability of the centroid of the neurons, detecting the centroid of the neurons, and finally segmenting the neurons. The problem that high-density and multi-size neurons cannot be segmented in the whole brain in the prior art is solved.

Description

technical field [0001] The invention belongs to the technical fields of computer science and biomedicine, and in particular relates to a method for automatic segmentation of highly cohesive and multi-sized brain neurons based on point markers. Background technique [0002] Accurate segmentation of neurons is very important for quantitative analysis of the number, shape, distribution and other information of neurons in high-resolution brain microscopic images. Currently, the gold standard - the stereological method - is used by neuroscientists to estimate the number of neurons in an anatomical region of interest. However, this manual operation is time-consuming and labor-intensive, and its accuracy is also affected by multiple factors such as the complex brain structure and the subjective experience of experts. Therefore, there is an urgent need for a method that can automatically and accurately segment neurons. At present, scholars at home and abroad have done a lot of res...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06T7/12G06K9/46G06K9/62G06N3/04G06N3/08
CPCG06T7/0012G06T7/12G06N3/08G06T2207/20081G06T2207/30016G06V10/44G06N3/048G06N3/045G06F18/213
Inventor 尤珍臻姜明石争浩石程都双丽梁继民
Owner XIAN UNIV OF TECH
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