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Optics Express

Optics Express

  • Editor: Andrew M. Weiner
  • Vol. 22, Iss. 10 — May. 19, 2014
  • pp: 12160–12176

Superresolution microscope image reconstruction by spatiotemporal object decomposition and association: application in resolving t-tubule structure in skeletal muscle

Mingzhai Sun, Jiaqing Huang, Filiz Bunyak, Kristyn Gumpper, Gejing De, Matthew Sermersheim, George Liu, Pei-Hui Lin, Kannappan Palaniappan, and Jianjie Ma  »View Author Affiliations


Optics Express, Vol. 22, Issue 10, pp. 12160-12176 (2014)
http://dx.doi.org/10.1364/OE.22.012160


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Abstract

One key factor that limits resolution of single-molecule superresolution microscopy relates to the localization accuracy of the activated emitters, which is usually deteriorated by two factors. One originates from the background noise due to out-of-focus signals, sample auto-fluorescence, and camera acquisition noise; and the other is due to the low photon count of emitters at a single frame. With fast acquisition rate, the activated emitters can last multiple frames before they transiently switch off or permanently bleach. Effectively incorporating the temporal information of these emitters is critical to improve the spatial resolution. However, majority of the existing reconstruction algorithms locate the emitters frame by frame, discarding or underusing the temporal information. Here we present a new image reconstruction algorithm based on tracklets, short trajectories of the same objects. We improve the localization accuracy by associating the same emitters from multiple frames to form tracklets and by aggregating signals to enhance the signal to noise ratio. We also introduce a weighted mean-shift algorithm (WMS) to automatically detect the number of modes (emitters) in overlapping regions of tracklets so that not only well-separated single emitters but also individual emitters within multi-emitter groups can be identified and tracked. In combination with a maximum likelihood estimator method (MLE), we are able to resolve low to medium density of overlapping emitters with improved localization accuracy. We evaluate the performance of our method with both synthetic and experimental data, and show that the tracklet-based reconstruction is superior in localization accuracy, particularly for weak signals embedded in a strong background. Using this method, for the first time, we resolve the transverse tubule structure of the mammalian skeletal muscle.

© 2014 Optical Society of America

OCIS Codes
(000.1430) General : Biology and medicine
(100.0100) Image processing : Image processing
(100.6640) Image processing : Superresolution
(180.0180) Microscopy : Microscopy
(110.4155) Imaging systems : Multiframe image processing

ToC Category:
Image Processing

History
Original Manuscript: December 26, 2013
Revised Manuscript: March 5, 2014
Manuscript Accepted: April 1, 2014
Published: May 13, 2014

Virtual Issues
Vol. 9, Iss. 7 Virtual Journal for Biomedical Optics

Citation
Mingzhai Sun, Jiaqing Huang, Filiz Bunyak, Kristyn Gumpper, Gejing De, Matthew Sermersheim, George Liu, Pei-Hui Lin, Kannappan Palaniappan, and Jianjie Ma, "Superresolution microscope image reconstruction by spatiotemporal object decomposition and association: application in resolving t-tubule structure in skeletal muscle," Opt. Express 22, 12160-12176 (2014)
http://www.opticsinfobase.org/oe/abstract.cfm?URI=oe-22-10-12160


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