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Mammary gland is composed entirely of soft tissue with approximate density, therefore mammary gland CR medicine radiation image presents a low contrast, and slight difference changes may be a manifestation of tumor, so it is necessary to enhance mammary gland CR image to improve its visual quality in order to meet the demands of doctor's clinical diagnosis. However the general enhancement algorithms over enhance the contrast and noise, due to image details lost, aiming at the defects, a mammary gland CR medicine image adaptive enhancement arithmetic based on image gray entropy is put forward. The arithmetic adapts dizzy image to magnify selected spatial frequency response in order to enhance the edge details of mammary gland CR images. It can adjust weighted factor K according to image gray characteristics namely pixel gray entropy. Experiments results demonstrate that mammary gland CR image enhanced by the algorithm has abundant details and high signal-to-noise ratio, moreover, CR image enhanced has good visual effect. So the method is effective and fit for enhancing CR medical radiation image edge details.

Test suite reduction is necessary to reduce the testing cost and increase efficiency, therefore, test suite reduction model is proposed, and test suite reduction problem is converted into a standard optimization problem. Additionally, an improved e volutionary algorithm is also proposed, which encodes the chromosome with quantum bit as its basic information bit. It achieves the individual evolution by improving the quantum rotating gates using adaptive rotation, and its convergence speed and global optimization ability is superior to the traditional evolutionary algorithm. Motivated by this, we propose a novel test suite reduction method using quantum evolutionary. Finally, experiments validate the technology with higher efficiency.

The characteristic of digital CR medicine radiation image has wide dynamic range, abundant details and bad contrast, so it is necessary to enhance CR image to the need of doctor diagnosis. But the general enhancement algorithms don't consider human visual characteristics, so it puts forward CR medicine image adaptive enhancement algorithm combining the human visual property, which is more sensitive to smooth area noise compared with detail area noise, and makes image edge detail enhancement great in detail area, and detail enhancement little in smooth area, in which factor K is based on space change of image domain, accordingly gaining non-linear enhancement edge details of CR image. Experiment results demonstrate that the algorithm enhances CR image detail and CR image enhanced has good visual effect, so the method is fit for edge detail enhancement of CR medicine radiation image.