Journal of Biomimetics, Biomaterials and Biomedical Engineering Vol. 58

Abstract: The effect of angle abutment on the stress distribution of bone tissue around implant is not clear. Using abutments with different gingival height (GH) may cause changes in the stress distribution of the implant and implant-bone interface. This study aims to investigate whether angled abutments with varied GH have a significant effect on stress distribution of surrounding bone and the biomechanical behavior of the implant system. Three implant-supported restoration models were designed by changing the angled abutment GH (1 mm, 3 mm and 5 mm). Force of 200N was applied on the crown surface at 45° to the long axis of the implants. The biomechanical performance of the restorations (including implants and angled abutments) and stress distribution pattern were evaluated by finite element analysis (FEA). Results showed that angled abutments with larger GH resulted in increased stresses on the implant and implant-bone interface.

Abstract: White blood cell image segmentation provides the opportunity for medical experts to objectively diagnose the medical conditions of patients suffering from Leukemia, for example. Due to the rigorous nature of cell image acquisition (staining process and non-uniform illumination) efficient tools must be deployed to achieve the desired segmentation result. In this paper, a deep learning model is proposed together with a grab cut. The developed deep learning model provides an initial coarse segmentation of white blood cell images. However, the objective of this segmentation is to localize or identify regions of interest from white blood cell images. A bounding is generated from the localized cell image and then used to initiate an automatic cell image segmentation using grab cut. Results of the two publicly available datasets of white blood cell images are considered satisfactory on the proposed model.