Search

According to the infrared patch image (IPI) model theory, the infrared image background has a low rank and the target is sparse. The low-rank model can be used to separate the background and identify the target. However, in a noisy environment, the recognition effect will be affected. The higher the noise, the harder it would be to detect a small target. The residual strong fault and background edges could reduce the detection rate and increase false alarms. The traditional IPI model is adaptable to the background with the lower noise. This paper combines weighted nuclear norm minimization (WNNM) optimization with sparse representation based on the local IPI model. The background details are described more prominently by improving the nuclear norm weighting factor. The target is much easier to detect under the specific bright clouds and ground buildings background with high noise. At the same time, post-processing with image local contrast analysis is performed to compare traditional spatial filtering and local infrared patch image model algorithms. Our method has a good suppression effect on complex noise backgrounds and achieves a higher signal to clutter ratio gain (SCRG). It could also improve the target detection rate and reduce false alarms.

Objective: To investigate the expression of matrix metalloproteinase-9 (MMP-9) and nuclear factor κappa-B (NF-κB) in different ovarian tissue and explore the relationship between their expression and clinicopathological features of epithelial ovarian cancer. Methods: The expression of NF-κB and MMP-9 in 15 cases of normal ovarian tissue and 80 cases of epithelial ovarian cancer were detected by mmunohistochemistry PV method. Results: Expression of MMP-9 and NF-κB in epithelial ovarian cancer was significantly higher than those in normal ovarian, and the difference was statistically significant (P < 0.05). The expression of MMP-9 protein was not related to histology classification and differentiation degree, but it was significantly related with lymphatic metastasis and clinical stage (P < 0.05). The expression of NF-κB protein was significantly associated with histology classification, lymphatic metastasis, clinical stage, and differentiation degree (P < 0.05). In epithelial ovarian cancer tissue, the expression of MMP-9 and NF-κB proteins showed a significant positive correlation (P < 0.01). Conclusion: The expression MMP-9 and NF-κB proteins are closely related to pathological features of epithelial ovarian cancer and there are important significance to the development, invasion and metastasis of epithelial ovarian cancer. So they might become useful prognostic indicator for diagnosis and prognosis of epithelial ovarian cancer.