Aim:The study aims to evaluate and compare marginal microleakage in deep class II cavities restored with various techniques using different composites.Materials and Methods:Sixty freshly extracted teeth were divided into six groups of 10 teeth each. Standardized class II cavities were made and were restored using composites of different consistencies with different placement techniques. Group 1 with Microhybrid composite, Group 2 with Packable composite, Group 3 Microhybrid composite with a flowable composite liner, Group 4 Packable composite with a flowable composite liner, Group 5 Microhybrid composite with precured composite insert in second increment and Group 6 Packable composite with precured insert in second increment. Specimens then were stored in distilled water, thermocycled and immersed in 50% silver nitrate solution. These specimens were sectioned and evaluated for microleakage at the occlusal and cervical walls separately using stereomicroscope.Results:The results demonstrated that in the occlusal wall, packable composite, showed significantly more marginal microleakage than the other groups. In the cervical wall, teeth restored with a flowable composite liner showed less marginal microleakage when compared to all other groups.Conclusion:Based on the results of this study, the use of flowable composite as the first increment is recommended in deep class II cavities.

No abstract

No abstract

No abstract

Background: Skin lesion edge detection is a significant step in developing an automatized diagnostic system. The efficient diagnostic system leads to correct identification and detection of skin lesion diseases. In this paper, ant colony optimization (ACO) technique is used to improve the edge contour of skin lesion images. Material and Method:Firstly, a three-stage preprocessing methodology involving color space conversion, contrast enhancement, and filtering is applied to improve the skin lesion image quality. The edge map is obtained by applying three types of conventional edge detection methods namely Canny, Sobel, and Prewitt. Thereafter, ACO is applied on these images to produce an improved edge contour. Result: The improvement of the proposed methodology is quantitatively verified by analysis of the entropy of the final image obtained by conventional and proposed techniques. Conclusion: From the result analysis, we can conclude that introduction of ACO has increased the efficiency of the conventional edge detection method in skin lesion images. K E Y W O R D S Ant Colony Optimization, Canny, edge detection, Prewitt, skin lesions, Sobel How to cite this article: Sengupta S, Mittal N, Modi M. Improved skin lesion edge detection method using Ant Colony Optimization. Skin Res Technol. 2019;25:846-856.