Automatic selection method of optimal homogeneous region in ultrasound images based on quadtree decomposition

Abstract

The invention belongs to the technical field of image processing, and particularly provides an automatic selection method for an optimal homogenous region of an ultrasound image and based on quad-tree decomposition. According to the automatic selection method for the optimal homogenous region of the ultrasound image and based on the quad-tree decomposition, firstly, a threshold value determined through maximum between-cluster variance binarization is used as a consistency standard for the quad-tree decomposition of the ultrasound image; secondly, all current maximum blocks are sequentially taken out from decomposition results according to an order from large to small, and optimized selection is conducted according to the judgment basis of the blocks in the optimal homogenous region; and lastly, whether an automatic selection result of the optimal homogenous region is output or the initial binarized threshold value is adjusted to repeat the above steps is determined according to a judgment result. The automatic selection method for the optimal homogenous region of the ultrasound image and based on the quad-tree decomposition is high in efficiency and short in operation time; manual intervention is not needed, and only ultrasound image data are used for driving; and the automatic selection method is quite suitable for determination of homogenous regions at the time of handling noise reduction of ultrasound image spots, selection of an area-of-interest, boundary detection, target segmentation and the like, and has a remarkable actual using effect.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a method for automatically selecting an optimal homogeneous region of an ultrasonic image based on quadtree decomposition. Background technique [0002] Ultrasound imaging has become an irreplaceable and widely used imaging method in the field of medical imaging diagnosis due to its advantages of non-invasive, real-time, strong repeatability, and low cost of diagnosis and treatment. However, there is inevitably a large amount of speckle noise in ultrasound images, and the image contrast and resolution are relatively low, making speckle noise reduction, boundary detection, and target segmentation of ultrasound images a hot and difficult point in the field of medical image processing. . And all these works without exception need to use the selection of homogeneous regions on ultrasound images [1-3]. [0003] Taking the classic algorithm of speckle noise reduc...

AI Technical Summary

Problems solved by technology

[0004] In order to improve the accuracy of homogeneous region selection in ultrasound images, the traditional method is to directly let users manually select homogeneous regions during image processing. Facilitate subsequent quantitative analysis

For the speckle noise reduction of ultrasound sequence images that require batch processing, the method of relying on manual selection of homogeneous regions is even more infeasible.

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