英文摘要 |
Aiming at the poor effect of medical image feature recognition and detail judgment, three-dimensional visualization modeling of medical image is needed. A three-dimensional (3D) visualization modeling algorithm of medical image based on machine learning and edge contour feature detection is proposed. Firstly, the distribution matrix of three-dimensional visual grayscale pixels is constructed for medical images. According to the distribution of pixels, the blurred areas in medical images are de-noised and separated to extract their edge contour features and avoid noise interference. Secondly, the image edge contour features are visually decomposed to construct the three-dimensional contour of medical images. Finally, the machine learning method is used to reconstruct the three-dimensional contour visually, and the threedimensional visualization model of medical images is established to realize the threedimensional visualization modeling algorithm design of medical images based on machine learning. The simulation results show that the method has better feature resolution, higher accuracy of detail feature extraction and better effect of three-dimensional reconstruction, and improves the effect of feature recognition and detail judgment of medical images. |