A medical image bone segmentation method based on the combination of pspnet and hed
A medical image and combined technology, applied in the field of medical image bone segmentation, can solve the problems of only focusing on pixel grayscale features, not fully considering the spatial characteristics, and the effect of noise images is not ideal, so as to improve the segmentation effect and measure various performances. Value boost effect
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[0021] Below in conjunction with specific embodiment, further illustrate the present invention, should be understood that these embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention, after having read the present invention, those skilled in the art will understand various equivalent forms of the present invention All modifications fall within the scope defined by the appended claims of the present application.
[0022] Such as figure 1 As shown in (a), PSPNet uses the pre-trained ResNet model to generate the initial feature map, then integrates the context information through the pyramid pooling module, uses the four-layer pyramid structure to obtain global features, and then combines the global features with the original The feature maps are concatenated and passed through convolutional layers to generate the final prediction map.
[0023] Such as figure 1 As shown in (b), HED adds five side output lay...
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