[Research progress on colorectal cancer identification based on convolutional neural network].

Colorectal cancer (CRC) is a common malignant tumor that seriously threatens human health. CRC presents a formidable challenge in terms of accurate identification due to its indistinct boundaries. With the widespread adoption of convolutional neural networks (CNNs) in image processing, leveraging CNNs for automatic classification and segmentation holds immense potential for enhancing the efficiency of colorectal cancer recognition and reducing treatment costs. This paper explores the imperative necessity for applying CNNs in clinical diagnosis of CRC. It provides an elaborate overview on research advancements pertaining to CNNs and their improved models in CRC classification and segmentation. Furthermore, this work summarizes the ideas and common methods for optimizing network performance and discusses the challenges faced by CNNs as well as future development trends in their application towards CRC classification and segmentation, thereby promoting their utilization within clinical diagnosis.

Effects of different removal methods of excess resin adhesive on the microleakage of alumina all-ceramic crowns.

BACKGROUND: Microleakage is a common problem that affects the quality and longevity of all-ceramic crowns. It is influenced by factors such as the resin cement, crown margin design and curing technique. However, few studies focus on the effect of different methods of removing excess resin adhesive on the microleakage of all-ceramic crowns. This study aimed to compare two methods of removing excess resin adhesive (the small brush and sickle methods) on the microleakage of all-ceramic crowns with different marginal clearances. METHODS: Forty extracted third molars were prepared with a 90° shoulder margin and randomly divided into four groups according to their marginal lift (30, 60, 90 or 0 µm). Procera alumina crowns were fabricated using computer-aided design/computer-aided modelling and cemented onto the teeth with 3 M RelyX Unicem (3 M Company, United States) resin cement. Excess resin cement was removed by either the small brush or the sickle scalpel method. The marginal adaptation was observed with a digital microscope. After thermal cycling of the teeth, microleakage was assessed using the dye penetration test under a stereomicroscope. The Mann-Whitney U test and Kruskal-Wallis H test were used to compare the microleakage scores among different groups. RESULTS: The small-brush group showed significantly better marginal adaptation and lower microleakage scores than the sickle group (p < 0.05). There was no significant difference in the microleakage score (grade 0) among different marginal clearances within each group (p > 0.05). CONCLUSION: The small-brush method was more effective than the sickle scalpel method in reducing the microleakage of all-ceramic crowns with different marginal clearances. This method can improve the marginal adaptation and sealability of all-ceramic crowns, thus preventing secondary caries and other complications.