Segmentation and morphological analysis of amyloid fibrils from cryo-EM image data.

Autor:	Weber, Matthias, Neumann, Matthias, Schmidt, Matthias, Pfeiffer, Peter Benedikt, Bansal, Akanksha, Fändrich, Marcus, Schmidt, Volker
Předmět:	CONVOLUTIONAL neural networks AMYLOID AMYLOID beta-protein IMAGE analysis TRAINING manuals
Zdroj:	Journal of Mathematics in Industry; 2/7/2023, Vol. 13 Issue 1, p1-11, 11p
Abstrakt:	Fast assessment of the composition of amyloid fibril samples from cryo-EM data poses a serious challenge to existing image analysis tools. We develop a method for automated segmentation of single fibrils requiring only little user input during the training process. This is achieved by combining a binary segmentation based on a convolutional neural network with preprocessing steps to allow for easy manual generation of training data. Subsequent skeletonization turns the binary segmentation into a single-object segmentation. Then, we compute properties of shape and texture of each segmented fibril, including an estimation of the fibril width. We discuss the composition of the sample based on the distributions of these computed properties and outline how a classification of fibril morphologies might be performed using these properties. [ABSTRACT FROM AUTHOR]
Databáze:	Complementary Index
Externí odkaz:	Zobrazit plný text záznamu Plný text ve formátu HTML
Nepřihlášeným uživatelům se plný text nezobrazuje	K zobrazení výsledku je třeba se přihlásit.