Breast ultrasound image segmentation method based on FCN and iterative acoustic shadow correction

Abstract

The invention discloses a breast ultrasound image segmentation method based on FCN and iterative acoustic shadow correction. The method constructs a new deep neural network in series. The network usesthe initial segmentation result of the first FCN as the initial segmentation of the acoustic shadow correction, which can effectively initialize the determined cost function to acquire the acoustic shadow field of the image and thus complete the acoustic shadow correction of the ultrasonic image, eliminate the problems of blurring the edge of anatomical layer and the poor image quality of some anatomical layers, and improve the input image quality of the second fully convolutional connected network. Then the network inputs the equalized gray-level image after correction into the second FCN toachieve final anatomical layer segmentation and a more accurate anatomical layer segmentation result. The research on the breast ultrasound image segmentation method is helpful to solve some scientific problems of ultrasound image segmentation, offers great help for the subsequent computer-aided detection and diagnosis of lesions, and has important scientific significance.

Description

technical field [0001] The invention belongs to the technical field of breast ultrasound image segmentation, and in particular relates to a breast ultrasound image segmentation method based on FCN and iterative acoustic shadow correction. Background technique [0002] Due to the advantages of non-invasiveness, no radiation, low cost and real-time imaging, ultrasound imaging is currently the main means of routine clinical breast examination. Ultrasound breast images can be divided into four anatomical layers: fat layer (including skin layer), breast tissue layer, muscle layer, ribs and chest wall to support the following clinical applications: improving the efficiency of computer-aided detection of breast lesions; The cornerstone of computing; aids in breast surgery planning or interpretation and analysis of clinical images. [0003] Accurate segmentation of breast anatomical layers is extremely challenging, mainly as follows: (1) The thickness, shape, and appearance of each...

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Problems solved by technology

[0006] In view of the above-mentioned deficiencies in the prior art, the breast ultrasound image segmentation method based on FCN and iterative acoustic shadow correction provided by the present invention solves several scientific problems in the ultrasound image segmentation in the prior art, and is useful for subsequent computer-aided lesion detection and diagnosis. important help, of great scientific importance

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