text: Electronic microscopy has been used for morphology evaluation of different materials structures. However, microscopy results may be affected by several factors. Image processing methods can be used to correct and improve the quality of these results. In this paper we propose an algorithm based on starlets to perform the segmentation of scanning electron microscopy images. An application is presented in order to locate gold nanoparticles in natural rubber membranes. In this application, our method showed accuracy greater than 85 for all test images. Results given by this method will be used in future studies, to computationally estimate the density distribution of gold nanoparticles in natural rubber samples and to predict reduction kinetics of gold nanoparticles at different time periods.
  @cite_18: Summary Cell loss and addition is an important biological event in pathology, and it usually provides central information to the changes of biological activity in the histological sections. To develop a reliable and accurate cell counting tools in tissue section, in this paper, we proposed a novel cell nuclei detecting method based on the sliding band filter which is a member of convergence index family. We evaluated the accuracy and performance of our method on density packed retinal outer nuclear layer cell confocal multivariate fluorescence microscopy image datasets. The results show our proposed method exhibited an excellent performance with its accuracy compared with human manual counting. It is worth noting that the proposed cell counting method can clearly benefit for retinal detachment and reattachment visual diagnostics close related to cell loss and addition.
  @cite_14: Small animal magnetic resonance microscopy (MRM) has been widely used today in computational neuroanatomy. Accurate identification of brain tissue in a mouse MRM is a critical fundamental step in neuroimaging processing, which is given less attention. This study presents an automatic skull-stripping technique based on template models and histogram analysis. Results were evaluated by calculating the Jaccard similarity index (JSI) and boundary concordance ratio (BCR) between the automatically segmented and manually traced brain volumes. Results demonstrate that this technique accurately extracts the brain volume (mean JSI = 97.1 , BC = 94.4 ). The brain extraction method presented in this study will greatly facilitate analysis of neuroimaging studies of rodent animals in neurodegenerative diseases. Microsc. Res. Tech. 2013. © 2012 Wiley Periodicals, Inc.
  @cite_7: In this paper, we present a procedure to separate aggregates of overlapped particles in digital holograms, based on a focus plane analysis applied to each particle. The method can be applied either on phase or on amplitude objects, according that each object has a border in one focus plane. Numerical simulations are performed to quantify the robustness of the process by increasing the overlapping areas between the particles. The separation algorithm is successfully demonstrated experimentally on different types of aggregates.
summary: Image segmentation is often used in microscopy images that are currently segmented to obtain features such as number of cells @cite_18 , separation of overlapped particles @cite_7 and skull-stripping of mouse brain @cite_14 .