Sparse photoacoustic image reconstruction method and system combined with target detection

Abstract

The invention provides a sparse photoacoustic image reconstruction method combined with target detection. The method comprises the following steps: constructing a first training data set; constructing a target detection network; training a target detection network by using the first training data set; processing the original photoacoustic data set by using a target detection network to obtain a cut image group data set; constructing a second training data set; constructing an image reconstruction network; training the image reconstruction network by using the second training data set; processing the sparse photoacoustic image by using a target detection network to obtain a coordinate vector group data set of the region of interest; and reconstructing and outputting a final photoacoustic image by using the image reconstruction network. According to the method, the target detection network based on the Twood-stage network and the Transformers model and the image reconstruction network based on the GAN network and the patchGan network are combined to process the sparse photoacoustic image sampled at intervals, so that the problem of poor image restoration effect caused by sparse photoacoustic image information and excessive background invalid information is solved.

Description

technical field [0001] The invention relates to an image reconstruction method, in particular to a sparse photoacoustic image reconstruction method and system combined with target detection. Background technique [0002] Photoacoustic imaging is a new type of biomedical photon imaging method. Its basic principle is the photoacoustic effect of biological tissue, that is, when biological tissue is irradiated by light, the biological tissue will absorb light energy to cause changes in internal temperature, and then due to thermal expansion. acoustic signal. Because the light absorption coefficient and scattering coefficient of the substance itself are different, the acoustic signals produced by different substances are different. If the short-pulse laser scanning irradiation of the same frequency is used for biological tissue, and then the ultrasonic detector is used to receive the ultrasonic wave generated by the tissue, and then Using an appropriate inversion algorithm to so...

AI Technical Summary

Problems solved by technology

[0005] In order to solve the problems in the prior art, the present invention provides a sparse photoacoustic image reconstruction method and system combined with target detection, by combining the target detection network based on Two-stage network and Transformers model and the image based on GAN network and patchGan network Reconstruct the network to process the sparse photoacoustic image sampled at intervals, obtain the coordinate vector group data set of the region of interest, and then reconstruct and output the final photoacoustic image, which not only saves a lot of computing overhead, but also has good image restoration effect and fast image reconstruction speed , which solves the problem of poor image restoration effect due to sparse photoacoustic image information and too much background invalid information

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