Applying Color Doppler Image based Virtual Surgery in Placenta Previa Cesarean Section

Abstract Objective: To study the application of image processing technology in cesarean section of placenta previa, thereby reducing the occurrence of high-risk pregnancy. Methods: First, the method of gray image enhancement is analyzed. This method enhances the gray difference between the target and the background, highlights useful information, summarizes the source and type of noise, and proposes common filtering and noise reduction methods to suppress the noise. For edge detection, pixel-level edge detection operators and sub-pixel-level edge detection operators are summarized. The Canny edge detection operator and the Gaussian fitting sub-pixel edge detection operator are introduced in detail, and innovative improvements are carried out for resolving the deficiencies of the algorithm. Results: The improved adaptive iterative segmentation thresholding method results in a threshold of T = 98 and 11 iterations. The image segmentation quality of the improved Otsu method has been greatly enhanced. After the second segmentation, the improved Otsu method finds the optimal threshold T = 76. Conclusion: Color Doppler ultrasound image processing technology has excellent application in placenta previa cesarean section.