Date of Original Version

5-2014

Type

Conference Proceeding

Rights Management

© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Abstract or Description

Localization-based super-resolution techniques are revolutionizing biological research by breaking the diffraction limit of fluorescence microscopy. Each super-resolution image is reconstructed from a time series of images of randomly activated fluorophores. Here, a fundamental question is to determine the minimal imaging length so that the reconstructed image faithfully reflects the biological structures under observation. So far, proposed methods focus entirely on image resolution, which reflects localizationuncertainty and fluorophore density, without taking into account the fact that images of biological structures are structured rather than random patterns. Here, we propose a different approach to determine imaging length based on direct quantification of image structural information using Gabor filters. Experimental results show that this approach is superior over approaches that only account forimage-intensity distribution, confirming the importance of using structural information. In contrast toresolution-based methods, our method does not require an artificial selection of image resolution and provides a statistically rigorous strategy for determining imaging length based on image structural information.

DOI

10.1109/ISBI.2014.6868039

Share

COinS
 

Published In

Proceedings of the IEEE International Symposium on Biomedical Imaging, 2014, 991-994.