An ultrasonic image super-resolution reconstruction method for improving contour definition based on an attention mechanism

Abstract

The invention discloses an ultrasonic image super-resolution reconstruction method for improving contour definition based on an attention mechanism. The ultrasonic image super-resolution reconstruction method comprises the steps of S1, data acquisition; S2, network construction; S3, initializing a network; S4, network training; S5: super-resolution image reconstruction. On the basis of an existingfeature extraction reconstruction network, the method builds another level of parallel codes-codes; according to the attention mechanism network of the decoding structure, utilizing common convolution and cavity convolution, better obtaining high-frequency information in an ultrasonic image, combining the two levels of network features, and extracting the final image features by using convolutionto form a super-resolution reconstruction network. Through the two-stage parallel network, the attention mechanism network is used for positioning the specific position of the high-frequency information, the tissue interface and the tissue area in the ultrasonic image can be effectively distinguished, the edge reconstruction definition of the tissue contact surface in the ultrasonic image is improved, and the problem that the contour of the reconstructed ultrasonic image is fuzzy is solved.

Description

technical field [0001] The invention belongs to the technical field of image super-resolution reconstruction and deep learning, and specifically relates to an ultrasonic image super-resolution reconstruction method based on an attention mechanism to improve contour definition. Background technique [0002] Ultrasound imaging uses ultrasonic beam scanning to obtain scanning images by receiving and processing reflected signals. Its coherent nature leads to the degradation effect of speckle noise in the ultrasound scan results, and the bandwidth-limited nature of ultrasound beamforming can cause the image spatial resolution to be reduced. These reasons lead to the decrease of contrast in ultrasound imaging and the blurring of contour information in ultrasound images . However, ultrasound imaging is widely used in medical auxiliary diagnosis, for example, in tumor detection, the blurring of tumor outline in ultrasound images easily leads to misdiagnosis. In order to improve th...

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Problems solved by technology

However, although these reconstruction algorithms effectively smooth the noise in the image, they lack the network module for locating high-frequency information, resulting in blurred tissue outlines in the reconstructed ultrasound image, which cannot achieve the expected effect of ultrasound image reconstruction.

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