An automatic segmentation method for thyroid ultrasound images based on radial basis neural network
A technology based on neural network and ultrasound images, applied in the field of automatic segmentation of thyroid ultrasound images based on radial basis neural network, can solve the time-consuming training process and other problems, achieve good classification effect, high discrimination ability, and improve performance
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[0081] The following in conjunction with embodiments, the present invention will be further described in detail, but embodiments of the present invention is not limited thereto.
[0082] as Figure 1 As shown, the present embodiment of a radial base neural network based thyroid ultrasound image automatic segmentation method, comprising the following steps:
[0083] (1) Enter the original image, as shown in Figure 2(a);
[0084] (2) Pre-processing of the original image;
[0085] (2-1) The original image is noise-reduced using adaptive weight median filtering (AWMF), and the results of the filtering are as shown in Figure 2(b);
[0086] AWMF calculates the weight w for each pixel in the area by counting the local area i,j 。 For the region template of M×M, the point weight coefficient w at the position (i,j). i,j It can be defined as follows:
[0087]
[0088] μ of them x,y and The average of the pixel grayscale values and the variance within the template area, respectively, are th...
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