The invention discloses a multi-
modal ultrasonic image intelligent analysis
system based on
deep learning, particularly relates to the field of ultrasonic image intelligent analysis, and is used for solving the problems of
speckle noise and displacement artifacts caused by sound beam attenuation during deep
abdomen scanning of a bedside ultrasonic person with a relatively high in-vivo quality index. Partition
noise reduction is guided through pixel
noise distribution associated with depth and attenuation, and deep micro-textures are reserved; the
color flow velocity and the elastic displacement are anchored through the
noise reduction gray scale edge, three-mode sub-pixel alignment is completed, and cross-channel deformation and drift are eliminated; the self-attention fusion network synchronously extracts texture, speed and
hardness features on the unified alignment surface to realize
coupling of a complete
biological structure and dynamic information; the texture residual error rate and the flow rate matching degree form complementary evaluation, noise distribution and alignment grid real-time self-adjustment are driven, frame-by-frame iteration convergence is achieved, and image definition and feature consistency are continuously improved.