Autoadaptive Algorithm for the Stacking-Level Estimation of Membranes in TEM Images

Gilles Hermann (1) , Nicolas Coudray (1) , Argyro Karathanou (1) , Jean-Luc Buessler (1) , Jean-Philippe Urban (1)

1 MIPS - Modélisation, Intelligence, Processus et Système

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.

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Gilles Hermann, Nicolas Coudray, Argyro Karathanou, Jean-Luc Buessler, Jean-Philippe Urban. Autoadaptive Algorithm for the Stacking-Level Estimation of Membranes in TEM Images. International Scholarly Research Network ISRN Signal Processing, 2011, pp.10. ⟨10.5402/2011/650546⟩. ⟨hal-00851865⟩