Method, system, device and storage medium for image recognition of liver and bile ducts and stones

Abstract

The invention discloses an image recognition system for hepatic bile ducts and calculi, comprising: an input module, used to acquire images to be tested and input them into a trained sparse convolutional neural network; a sparse convolutional neural network, used to obtain images to be tested Carry out image recognition, and segment the position contours of the hepatic bile duct and gallstones in the image to be tested from the recognition results; each convolution layer in the first encoder in the sparse convolutional neural network uses a small convolution kernel, and the rest Each convolutional layer in the encoder and each decoder uses a sparse convolution kernel; in the first encoding process, the feature maps at different scales are output to the subsequent encoders and decoders, and the corresponding resolution The following feature maps are fused. By applying the solution of the present application, image recognition of hepatic bile ducts and stones can be performed more effectively to assist doctors in treatment. The present application also provides an image recognition system, equipment and storage medium for hepatic bile ducts and stones, which have corresponding effects.

Description

technical field [0001] The invention relates to the technical field of medical image segmentation, in particular to an image recognition method, system, device and storage medium for hepatic bile ducts and stones. Background technique [0002] At present, the surgical treatment of hepatolithiasis is facing many difficulties and challenges, including difficulty in removing hepatolithiasis, unclean stone removal, and easy recurrence after operation. The general plan of stone removal surgery is to perform enhanced CT scan before the operation to obtain two-dimensional image information, and then abstract it into a 3D model in the doctor's mind based on experience. The requirements for the doctor's clinical experience and professional knowledge are very high, and deviations may also occur. In order to make better use of digital imaging technology to assist physicians, medical image segmentation technologies specifically targeting specific organ regions and corresponding lesion a...

AI Technical Summary

Problems solved by technology

For highly deformable stones, as well as bile ducts with small pixel areas and variable shapes, the effect is not particularly ideal

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