The prerequisite for doctors to diagnose and treat patients is to be able to accurately determine the patient's physical condition, which requires the help of some medical image data to help doctors to judge. At p...The prerequisite for doctors to diagnose and treat patients is to be able to accurately determine the patient's physical condition, which requires the help of some medical image data to help doctors to judge. At present, many hospitals in China are equipped with more advanced and complete imaging equipment. The normal operation of these equipment is closely related to computer image processing technology. This technology is a new technology based on computer technology and biomedical technology. Its key role is to provide convenient conditions for doctors to carry out treatment scientifically and efficiently, and improve the comprehensive service level of the hospital. This paper analyzes and studies the progress and application of computer image processing technology in medical imaging.展开更多
To preserve the sharp features and details of the synthetic aperture radar （SAR） image effectively when despeckling, a despeckling algorithm with edge detection in nonsubsampled second generation bandelet transform ...To preserve the sharp features and details of the synthetic aperture radar （SAR） image effectively when despeckling, a despeckling algorithm with edge detection in nonsubsampled second generation bandelet transform （NSBT） domain is proposed. First, the Canny operator is utilized to detect and remove edges from the SAR image. Then the NSBT which has an optimal approximation to the edges of images and a hard thresholding rule are used to approximate the details while despeckling the edge-removed image. Finally, the removed edges are added to the reconstructed image. As the edges axe detected and protected, and the NSBT is used, the proposed algorithm reaches the state-of-the-art effect which realizes both despeckling and preserving edges and details simultaneously. Experimental results show that both the subjective visual effect and the mainly objective performance indexes of the proposed algorithm outperform that of both Bayesian wavelet shrinkage with edge detection and Bayesian least square-Gaussian scale mixture （BLS-GSM）.展开更多
文摘The prerequisite for doctors to diagnose and treat patients is to be able to accurately determine the patient's physical condition, which requires the help of some medical image data to help doctors to judge. At present, many hospitals in China are equipped with more advanced and complete imaging equipment. The normal operation of these equipment is closely related to computer image processing technology. This technology is a new technology based on computer technology and biomedical technology. Its key role is to provide convenient conditions for doctors to carry out treatment scientifically and efficiently, and improve the comprehensive service level of the hospital. This paper analyzes and studies the progress and application of computer image processing technology in medical imaging.
基金supported by the National Natural Science Foundation of China(6067309760702062)+3 种基金the National HighTechnology Research and Development Program of China(863 Program)(2008AA01Z1252007AA12Z136)the National ResearchFoundation for the Doctoral Program of Higher Education of China(20060701007)the Program for Cheung Kong Scholarsand Innovative Research Team in University(IRT 0645).
文摘To preserve the sharp features and details of the synthetic aperture radar （SAR） image effectively when despeckling, a despeckling algorithm with edge detection in nonsubsampled second generation bandelet transform （NSBT） domain is proposed. First, the Canny operator is utilized to detect and remove edges from the SAR image. Then the NSBT which has an optimal approximation to the edges of images and a hard thresholding rule are used to approximate the details while despeckling the edge-removed image. Finally, the removed edges are added to the reconstructed image. As the edges axe detected and protected, and the NSBT is used, the proposed algorithm reaches the state-of-the-art effect which realizes both despeckling and preserving edges and details simultaneously. Experimental results show that both the subjective visual effect and the mainly objective performance indexes of the proposed algorithm outperform that of both Bayesian wavelet shrinkage with edge detection and Bayesian least square-Gaussian scale mixture （BLS-GSM）.
