No abstract

To improve the interpretability or perception of information in images for human viewers is the main goal of image enhancement. Aiming at the problem that image edges are difficult to determine due to artefacts, plaques, and vascular branches in cardiovascular ultrasound, an edge ultrasound imaging detection algorithm based on spatial-frequency-domain image enhancement is proposed to improve the clarity of ultrasound images. Firstly, this paper uses the space-frequency-domain enhancement algorithm to enhance the image. This algorithm overcomes the problem of low contrast of conventional algorithms. The enhanced data matrix is used as the cost matrix, and then, the heuristic image search method is used to search the image of the cost matrix. The results show that the use of spatial-frequency-domain image ultrasound imaging algorithm can improve the contrast and sharpness of ultrasound images of cardiovascular disease, which can make the middle edge of the image clearer, the detection accuracy rate is increased to 92.76%, and the ultrasound of cardiovascular disease is improved. The edge of the image gets accuracy. The paper confirms that the ultrasound imaging algorithm based on spatial-frequency-domain image enhancement is worthy of application in clinical ultrasound image processing. The performance of the proposed technique is 32.54%, 75.30%, 21.19%, 21.26%, and 11.10% better than the existing technique in terms of edge energy, detail energy, sharpness, contrast, and information entropy, respectively.

Giardia duodenalis and Cryptosporidium spp. are common gastrointestinal protozoa in mammals. Many studies have been conducted on the distribution of G. duodenalis and Cryptosporidium spp. genotypes in sheep and cattle. However, in China, information about molecular characterization and genetic analysis of G. duodenalis and Cryptosporidium spp. in goats is limited. In this study, 342 fecal samples from adult goats were collected from 12 farms in Sichuan Province, China. The occurrence of G. duodenalis and Cryptosporidium spp. in adult goats was 14.9% (51/342) and 4.7% (16/342), respectively. All G. duodenalis were identified as assemblage E, with two novel genotypes (assemblages E17 and E18) being detected at the beta-giardin (bg) locus. Based on three loci—beta-giardin (bg), triose phosphate isomerase (tpi), and glutamate dehydrogenase (gdh)—multilocus sequence typing revealed three novel multilocus genotypes (MLGs) of assemblage E (MLG-E1, E2, E3 (sc)). Small Subunit (SSU) rRNA-based PCR identified two Cryptosporidium species, namely C. xiaoi (11/16) and C. suis (5/16). This study is not only the first to report C. suis infection in adult goats in China but is also the first to use the MLG approach to identify G. duodenalis in adult goats.