Detection of low contrasted membranes in electron microscope images: statistical contour validation

A. Karathanou; J.-L. Buessler; H. Kihl; J.-P. Urban

doi:10.1117/12.805605

2 February 2009 Detection of low contrasted membranes in electron microscope images: statistical contour validation

A. Karathanou, J.-L. Buessler, H. Kihl, J.-P. Urban

Proceedings Volume 7251, Image Processing: Machine Vision Applications II; 72510D (2009) https://doi.org/10.1117/12.805605
Event: IS&T/SPIE Electronic Imaging, 2009, San Jose, California, United States

Abstract

Images of biological objects in transmission electron microscopy (TEM) are particularly noisy and low contrasted, making their processing a challenging task to accomplish. During these last years, several software tools were conceived for the automatic or semi-automatic acquisition of TEM images. However, tools for the automatic analysis of these images are still rare. Our study concerns in particular the automatic identification of artificial membranes at medium magnification for the control of an electron microscope. We recently proposed a segmentation strategy in order to detect the regions of interest. In this paper, we introduce a complementary technique to improve contour recognition by a statistical validation algorithm. Our technique explores the profile transition between two objects. A transition is validated if there exists a gradient orthogonal to the contour that is statistically significant.

Citation Download Citation

A. Karathanou, J.-L. Buessler, H. Kihl, and J.-P. Urban "Detection of low contrasted membranes in electron microscope images: statistical contour validation", Proc. SPIE 7251, Image Processing: Machine Vision Applications II, 72510D (2 February 2009); https://doi.org/10.1117/12.805605

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