Cancer lesion detection and diagnosis system for early esophageal squamous cell carcinoma of narrow-band endoscopic image
A technology for esophageal squamous cell carcinoma and diagnosis system, applied in the field of medical image processing, can solve the problems of insufficient doctor experience, fatigue, affecting the accuracy of diagnosis, etc., and achieve the effect of improving the efficiency of diagnosis, improving efficiency and accuracy, and reducing the amount of calculation.
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[0025] The embodiments of the present invention will be described in detail below, but the protection scope of the present invention is not limited to the examples.
[0026] The present invention adopts figure 1 The network framework shown is trained using 100 narrow-band imaging endoscopic images marked by multiple experienced doctors, so as to obtain a model that can automatically detect and diagnose esophageal squamous cell carcinoma foci on narrow-band imaging endoscopic images. The specific process is:
[0027] (1) Before training, initialize the network parameters with the pre-trained ResNet-50 model, and scale the images in the training set so that their resolution does not exceed 800×1333, and the corresponding bounding boxes are also scaled in the same proportion;
[0028] (2) During training, first normalize the three-channel (RGB) of the image according to mean = [0.485, 0.456, 0.406] and standard deviation = [0.229, 0.224, 0.225]. Using the stochastic gradient desc...
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