Abstract
This paper introduces an original algorithm for the labeling of the regions of a partitioned image according to the stacking level of membranes in transmission electron microscopy (TEM) images. Image analysis of membrane protein TEM images represents a particular challenging task because of the important noise and heterogeneity present in these images. The proposed algorithm adapts automatically to fluctuations and gray level ranges characterizing each membrane stacking level. Some information about the organization of the objects in the images is introduced as prior knowledge. Three types of qualitative and quantitative experiments have been specifically devised and implemented to assess the algorithm.
Highlights
Biological objects appear fairly transparent in electron microscopy images, as they are weakly scattered by the electron beam that crosses them
This paper introduces an estimation technique of the object stacking level of each region in a prior segmented transmission electron microscopy (TEM) image, based on the mean gray level and the neighborhood of the region
Several studies have been performed to develop the automation of each of the methods leading to the structural analysis of proteins: Wilson [2] proposed a method for the evaluation of 3D-crystallization experiments using a neural network classification from characteristics extracted with images tools; Zhu et al [3] contributed to the automatic selection of single particles in Transmission Electron Images; For the assessment of 2D-crystallization experiments, two software packages are suitable: First, Oostergetel et al [4] developed the GRACE package, a semiautomatic tool where Regions Of Interest (ROI) are selected manually by the user who targets the potentially crystallized membranes
Summary
Biological objects appear fairly transparent in electron microscopy images, as they are weakly scattered by the electron beam that crosses them. This paper introduces an estimation technique of the object stacking level of each region in a prior segmented TEM image, based on the mean gray level and the neighborhood of the region. An experimented microscopist can screen a grid for crystals in 15–20 minutes and give a quality grade During these concentrated moments he switches back and forth between the medium magnification mode to choose a region of interest and the high magnification mode to check the diffraction pattern. The original contribution is to select all the regions belonging, with high confidence, to stacking level L, based on two criteria: the region has a mean gray level weaker than the threshold at level L − 1, and the region is contiguous to at least one region at level L − 1 These criteria are justified by the nature of the analyzed samples.
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