Focus image recognition method and focus image recognition system based on deep learning model
A technology of image recognition and deep learning, applied in the field of lesion image recognition system, can solve the problem of not reducing the work intensity of doctors, and achieve the effect of avoiding treatment opportunities and reducing work intensity
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Embodiment 1
[0045] Such as figure 1 As shown, the lesion image recognition method based on the deep learning model provided in this embodiment includes the following steps S101-S104.
[0046] S101. Acquire a medical image to be detected.
[0047] In the step S101, the medical image to be detected can be specifically derived from an output interface (such as a USB interface or an HDMI interface) of an existing medical photography device. Specifically, the medical images to be detected may be, but not limited to, angiography images, cardiovascular angiography images, computerized tomography images, mammography images, positron emission tomography images, nuclear magnetic resonance imaging images, and medical ultrasound examination images.
[0048] S102. Perform image segmentation processing on the medical image to be detected to obtain several non-intersecting images of regions to be detected.
[0049] In the step S102, since images of multiple organs and tissues are generally included in...
Embodiment 2
[0063] Such as figure 2As shown, compared with Embodiment 1, this embodiment provides a lesion image recognition system based on the same inventive concept and based on a deep learning model, including an image acquisition module, an image segmentation module, an organ recognition module, a deep learning module, and a lesion image recognition system. A marking module and an image output module; the image acquisition module is used to acquire a medical image to be detected; the image segmentation module is communicatively connected to the image acquisition module, and is used to perform image segmentation processing on the acquired medical image to be detected to obtain Several disjoint images of the region to be detected; the organ identification module is connected to the image segmentation module in communication, and is used to extract the image contour features of the image of the region to be detected, and then identify the corresponding organ tissue according to the extr...
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