Inspired by mussel bioadhesion in nature, dopamine is extensively used for biomaterial surface modification. In this study, we coated dopamine on demineralized enamel and dentin surfaces to evaluate the effect of polydopamine coating on dental remineralization. Dental slices containing enamel and dentin were first etched with 37% phosphoric acid for 2 min, followed by immersion in a 2 mg/mL freshly prepared solution of dopamine (10 mM Tris buffer, pH 8.5) for approximately 24 h at room temperature in the dark to obtain polydopamine coating. Then, the dental slices with and without polydopamine coating were immersed in the supersaturated solution of calcium and phosphate at 37 °C for 2 and 7 days. The supersaturated solution of calcium and phosphate was refreshed each day. The precipitates were characterized by SEM, XRD, FTIR, microhardness, and nanoscratch analyses. No significant difference was observed in the remineralization of enamel whether it was coated with polydopamine or not. However, a significant difference was found in dentin remineralization between dentin with and without polydopamine coating. Polydopamine coating remarkably promoted demineralized dentin remineralization, and all dentin tubules were occluded by densely packed hydroxyapatite crystals. Thus, coating polydopamine on dental tissue surface may be a simple universal technique to induce enamel and dentin remineralization simultaneously.
Organ segmentation is an important step in various medical image applications. In this paper, a presegmented atlas is incorporated into the fuzzy connectedness (FC) framework for automatic segmentation of abdominal organs. First, the atlas is registered onto the subject to provide an initial segmentation. Then, a novel method is applied to estimate the necessary FC parameters such as organ intensity features, seeds, and optimal FC threshold automatically and subject adaptively. In order to overcome the intensity overlapping between the neighboring organs, a shape modification approach based on Euclidean distance and watershed segmentation is used. This atlas-based segmentation method has been tested on some abdominal CT and MRI images from Chinese patients. Experimental results indicate the validity of this segmentation method for various image modalities.
A framework that combines atlas registration, fuzzy connectedness (FC) segmentation, and parametric bias field correction (PABIC) is proposed for the automatic segmentation of brain magnetic resonance imaging (MRI). First, the atlas is registered onto the MRI to initialize the following FC segmentation. Original techniques are proposed to estimate necessary initial parameters of FC segmentation. Further, the result of the FC segmentation is utilized to initialize a following PABIC algorithm. Finally, we re-apply the FC technique on the PABIC corrected MRI to get the final segmentation. Thus, we avoid expert human intervention and provide a fully automatic method for brain MRI segmentation. Experiments on both simulated and real MRI images demonstrate the validity of the method, as well as the limitation of the method. Being a fully automatic method, it is expected to find wide applications, such as three-dimensional visualization, radiation therapy planning, and medical database construction.
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