Method for discriminating lung tumor CT image by adopting high-dimensional feature selection
A CT image and feature selection technology, applied in the field of image processing, can solve the problems that the segmentation method cannot completely segment out lung tumors, low precision, and cannot detect a single shape feature
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[0035] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be clear that the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of the present invention.
[0036] Specific embodiments of the present invention are given below to help the understanding of the present invention.
[0037] The present invention is based on the design of a threshold image segmentation model and a lung tumor classification model, and includes steps S101 to S103:
[0038] S101, image segmentation, the present invention uses the maximum between-class variance method (OTSU) to segment the preprocessed ROI region. Before image segmentation, the case image is preprocessed, and the sub-images ...
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