VDD-Net-based lung electrical impedance imaging method
A technology of electrical impedance imaging and lungs, applied in the generation of 2D images, neural learning methods, image data processing, etc., can solve the problems of limiting the generalization ability of EIT imaging technology and limiting large-scale clinical applications, and achieve strong robustness Enhanced performance and generalization ability, improved pixel resolution, and clear boundary effects
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[0032] The present invention will be further described in detail below through the specific examples, the following examples are only descriptive, not restrictive, and cannot limit the protection scope of the present invention with this.
[0033] The present invention proposes a new VDD-Net deep learning network model, which can complete high-resolution and high-precision lung EIT image reconstruction. The network uses the CG algorithm as a pre-reconstruction module to map the measured boundary voltage signal into an image describing the spatial distribution of the field, and then uses the deep convolutional neural network to fully extract the features in the sensitive field and reconstruct the image with clear boundaries and less artifacts. EIT image of lung area. In order to enhance the generalization performance of VDD-Net, a variety of lung simulation models were established as the training samples of VDD-Net using clinical CT images combined with prior information of huma...
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