Medical image focus detection modeling method, device and system based on federated learning
A medical imaging and lesion technology, applied in the field of computer vision and deep learning, can solve the problems that affect the accuracy of the model, the centralized collection of multi-party sharing of patient information is not feasible, and the medical privacy protection cannot be realized.
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[0041] In order to make the above solutions and beneficial effects of the present invention more comprehensible, the following will be described in detail through the examples and accompanying drawings.
[0042] This embodiment provides a federated learning method for detecting and modeling medical imaging lesions and a device for implementing the method. The device includes a global server S, a local lesion identification client C k . The local lesion recognition client includes a feature extractor F, a semantic integrator T and a multi-scale detection head D.
[0043] Pre-prepare the training data sets of N institutions N>2; each data set D k It consists of M real detected data samples. Generally speaking, the sample size M of each data set is several thousand; each sample contains a medical image I m and a tag T m .
[0044] Train the global server S, such as figure 1 , as follows:
[0045] The server randomly initializes the global network parameters to ω 0 , and...
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