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Full-automatic dopamine transporter semi-quantitative value detection method based on image processing

An image processing and detection method technology is applied in the field of image processing to achieve the effects of convenient implementation, improved detection accuracy and high precision

Pending Publication Date: 2020-04-10
FUDAN UNIV
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  • Application Information

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Problems solved by technology

However, due to the differences in the resolution and imaging methods of the two imaging modalities, the fusion of images from different modalities is still an open problem

Method used

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  • Full-automatic dopamine transporter semi-quantitative value detection method based on image processing
  • Full-automatic dopamine transporter semi-quantitative value detection method based on image processing
  • Full-automatic dopamine transporter semi-quantitative value detection method based on image processing

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Embodiment

[0034] Such as figure 1 Shown, a kind of automatic dopamine transporter semi-quantitative value detection method based on image processing, this method comprises the following steps:

[0035] Step 1: Construct the MRI image segmentation network. The input of the network is the brain MRI image, and the output is the segmentation results of the caudate nucleus, putamen, and globus pallidum in the basal ganglia of the brain. Specifically, step (1) the MRI image segmentation network is a Unet convolutional neural network including an encoding path and a decoding path. The encoding path captures context information through residual modules and maximum pooling layers at different resolutions, and obtains high-dimensional features; the decoding path sequentially restores the spatial resolution and boundaries of the image through a series of deconvolution layers; at the same time, the features of different layers in the encoder will be connected through skip connections and upsampled ...

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Abstract

The invention relates to a full-automatic dopamine transporter semi-quantitative value detection method based on image processing. The method comprises the following steps: (1) constructing an MRI image segmentation network, and segmenting a caudal nucleus region, a shell nucleus region and a pale globe region in a brain MRI image; (2) registering the MRI image to a PET image to obtain a segmentation result of the PET image; (3) performing clustering fine segmentation on the segmentation result of the PET image to obtain a plurality of label structures; (4) acquiring the characteristic statistics of each label structure; (5) correspondingly acquiring characteristic statistics of a top pillow leaf area in the PET image, and standardizing the characteristic statistics in each label structureby taking the characteristic statistics of the top pillow leaf area as a reference to obtain a semi-quantitative value of each characteristic statistics; and (6) performing T test on the semi-quantitative value of each label structure to finish saliency sorting of the semi-quantitative values. Compared with the prior art, the method is high in detection precision, convenient to implement and flexible in application.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a fully automatic semi-quantitative value detection method for dopamine transporters based on image processing. Background technique [0002] The dopamine transporter (DAT) is a dopamine transporter located on the presynaptic membrane of dopamine neurons. Dopamine transporters can be used to evaluate the functional status of striatal presynaptic dopaminergic neuron terminals, and the reduction and activity of dopamine transporters are important manifestations of dopamine reduction. Therefore, semiquantitative detection of dopamine transporters can aid in the detection of neurodegenerative diseases. [0003] With the development of biomedical engineering and computer technology, medical imaging provides medical images of various modalities for clinical diagnosis, such as magnetic resonance imaging (MRI), positron emission tomography (PET), etc. Both structural analysis ...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06T7/10G06T7/33G06K9/62G06N3/04
CPCG06T7/0012G06T7/10G06T7/33G06T2207/10088G06T2207/20081G06T2207/30004G06N3/045G06F18/23213
Inventor 庄吓海徐佳杭左传涛吴平
Owner FUDAN UNIV
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