Image processing method and device, training method and device, electronic terminal and storage medium
An image processing, image technology, applied in the field of image processing
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Embodiment 1
[0037] figure 1 It is a schematic flowchart of an image processing method provided in Embodiment 1 of the present invention. This embodiment is applicable to the case of using low-dose CT images to generate high-dose predicted CT images. The method can be executed by the image processing device provided by the embodiment of the present invention, the device is realized by software and / or hardware, and is preferably configured in an electronic terminal installed with image processing function software, such as a computer.
[0038] see figure 1 , the image processing method provided by the present embodiment includes the following steps:
[0039] S110. Receive a CT image of a first dose.
[0040] The radiation dose of a CT image is related to the tube current in the tube of the scanning device. Generally, the radiation dose of CT scanning can be reduced by reducing the magnitude of the tube current during scanning. As the tube current decreases, the number of photons reachi...
Embodiment 2
[0052] The image processing method provided in this embodiment can be combined with various optional solutions in the image processing method provided in the above embodiments. The raw image processing method provided in this embodiment optimizes the construction of the adversarial loss function and the cyclic loss function, and can train the generator and the discriminator in the preset generative adversarial network according to the adversarial loss function and the cyclic loss function.
[0053] figure 2 It is a schematic flowchart of an image processing method provided in Embodiment 2 of the present invention. see figure 2 , the image processing method provided by the present embodiment includes the following steps:
[0054] S210. Construct a preset generative adversarial network including a first generator, a second generator, a first discriminator, and a second discriminator.
[0055] In this embodiment, the preset generation confrontation network adopts the Cycle G...
Embodiment 3
[0073] The image processing method provided in this embodiment can be combined with various optional solutions in the image processing method provided in the above embodiments. The image processing method provided in this embodiment optimizes the training steps of the preset generative adversarial network, for example, while the first generator is trained with the preset generative adversarial network based on the adversarial loss function and the cyclic loss function, it also includes: the first A generator is trained with the preset generation confrontation network based on the identity loss function; and / or, for example, when the first generator is trained with the preset generation confrontation network based on the confrontation loss function and the loop loss function, it also includes: the first The generator is trained with a preset generative adversarial network based on a fully variational loss function.
[0074] By introducing an identity loss function in the traini...
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