Abstract
In view of the problem of inaccurate segmentation of thyroid nodule ultrasound images, a method of thyroid nodule ultrasound image segmentation based on joint up-sampling is proposed. In order to solve the problem of serious speckle noise in the original ultrasound data, preprocessing is performed to enhance the contrast between the nodule area and the background area. In order to achieve accurate positioning of the nodule target area, a joint up-sampling module is designed to fuse the context information of ordinary standard convolution and expansion convolution with different expansion coefficients. Experimental results show that the proposed method achieves 93.19% accuracy and dice similarity coefficient is 0.8558, which is better than other existing thyroid nodule segmentation network models.
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