Cancer image prediction and discrimination method and system based on transfer learning
A technology of transfer learning and discrimination method, applied in the field of medical image data processing, can solve problems such as low efficiency, more manpower and material resources, and achieve the effect of improving accuracy and efficiency, reducing workload, and efficient and accurate medical auxiliary diagnosis.
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[0034] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.
[0035] Such as figure 1 As shown, the cancer image prediction and discrimination method based on migration learning provided by the present invention specifically includes the following steps:
[0036] Step 1: Construction of a migration learning model, migration of a trained convolutional neural network model, preferably, the migration learning model is Inception-v3, consisting of 11 Inception modules, each of which is composed of many small-sized convolutions Merging joint composition enables learning more image features in the same receptive field, reducing computational complexity and avoiding over-fitting problems. Adjust the parameters and structure of the convolutional neural network model in combination with the medical colonoscopy detection image classification task, connect the bottleneck of the deep learning model Inception-v3 to a new fully...
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Abstract
Description
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Application Information
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