Ultrasonic image sequence segmentation method based on sparse characteristics and shape correlation

Abstract

The invention discloses an ultrasonic image sequence segmentation method based on sparse characteristics and shape correlation. The method comprises steps that firstly, a sparse expression theory is utilized to construct an over-complete characteristic dictionary based on a target and the background, reconstruction errors of the target relative to a target and background characteristic dictionary are utilized to construct an active contour search strategy based on sparse characteristic competition; secondly, for inputted to-be-segmented ultrasonic image sequences, non-monitoring learning of change of target shapes between the ultrasonic image sequences is carried out to acquire a matrix forming an image sequence shape, the matrix is consistent with low rank attributes, the low rank attributes are taken as prior knowledge of target shape change to constraint active contour evolution; and lastly, the active contour search strategy based on sparse characteristic competition and the target shape prior knowledge are integrated into an active contour segmentation framework. The method is advantaged in that the segmentation result is more accurate and robust, and computer auxiliary treatment efficiency and the effect are improved.

Description

technical field [0001] The invention belongs to the technical field of medical image processing and machine learning, and in particular relates to an ultrasonic image sequence segmentation method based on sparse features and shape correlation. Background technique [0002] High Intensity Ultrasound Focus (HIFU), as a computer-aided therapy based on ultrasound image guidance, has achieved good therapeutic effects [References 1, 2]. Such as figure 1 As shown, it is of great significance to accurately segment the lesion area from the ultrasound image sequence to improve the effect of HIFU treatment. At present, this work is performed by clinicians to segment the target area on each frame image, which is obviously a boring and inefficient process. [0003] Therefore, an accurate and efficient segmentation method of ultrasound image sequences has important clinical value and research significance for improving the effect and efficiency of HIFU treatment. However, effective ult...

AI Technical Summary

Problems solved by technology

[0012] In order to solve the blurring of the target edge, uneven gray distribution and misleading features of the target edge caused by the inherent shortcomings of the ultrasonic image, it is difficult to accurately search for the target edge by the traditional ultrasonic image segmentation method.

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