Liver tumor image segmentation method of dense connection network based on high and low layer feature fusion
A feature fusion and liver tumor technology, applied in the field of liver tumor image segmentation, can solve the problem of not considering the correlation between high-level and low-level features, and achieve the effect of improving segmentation accuracy
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[0025] In order to make the purpose, technical solutions and advantages of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the present invention Examples, not all examples. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.
[0026] Such as figure 1 As shown, the embodiment of the present invention provides a liver tumor image segmentation method based on a densely connected network based on high-level and low-level feature fusion, including:
[0027] S101: collecting nuclear magnetic images of liver tumor patients to form a data set, and dividing the data set into a training set and a test set;
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