State space approach to single molecule localization in fluorescence microscopy
State space approach to single molecule localization in fluorescence microscopy
Single molecule super-resolution microscopy enables imaging at sub-diffraction-limit resolution by producing images of subsets of stochastically photoactivated fluorophores over a sequence of frames. In each frame of the sequence, the fluorophores are accurately localized, and the estimated locations are used to construct a high-resolution image of the cellular structures labeled by the fluorophores. Many methods have been developed for localizing fluorophores from the images. The majority of these methods comprise two separate steps: detection and estimation. In the detection step, fluorophores are identified. In the estimation step, the locations of the identified fluorophores are estimated through an iterative approach. Here, we propose a non-iterative state space-based localization method which combines the detection and estimation steps. We demonstrate that the estimated locations obtained from the proposed method can be used as initial conditions in an estimation routine to potentially obtain improved location estimates. The proposed method models the given image as the frequency response of a multi-order system obtained with a balanced state space realization algorithm based on the singular value decomposition of a Hankel matrix. The locations of the poles of the resulting system determine the peak locations in the frequency domain, and the locations of the most significant peaks correspond to the single molecule locations in the original image. The performance of the method is validated using both simulated and experimental data.
And statistics, Fluorescence microscopy, Image analysis, Image reconstruction techniques, Probability theory, Stochastic processes, Superresolution
1332-1355
Vahid, Milad R.
6a1a88a4-9fcc-4ac5-84a4-0d4ee1088cc6
Chao, Jerry
550e20b0-8365-42e3-a6fc-1048eb8c2e47
Kim, Dongyoung
43a73b5c-3f2e-4ba9-8ffa-a7b454e2fd9f
Ward, E. Sally
b31c0877-8abe-485f-b800-244a9d3cd6cc
Ober, Raimund J.
31f4d47f-fb49-44f5-8ff6-87fc4aff3d36
1 March 2017
Vahid, Milad R.
6a1a88a4-9fcc-4ac5-84a4-0d4ee1088cc6
Chao, Jerry
550e20b0-8365-42e3-a6fc-1048eb8c2e47
Kim, Dongyoung
43a73b5c-3f2e-4ba9-8ffa-a7b454e2fd9f
Ward, E. Sally
b31c0877-8abe-485f-b800-244a9d3cd6cc
Ober, Raimund J.
31f4d47f-fb49-44f5-8ff6-87fc4aff3d36
Vahid, Milad R., Chao, Jerry, Kim, Dongyoung, Ward, E. Sally and Ober, Raimund J.
(2017)
State space approach to single molecule localization in fluorescence microscopy.
Biomedical Optics Express, 8 (3), , [#278546].
(doi:10.1364/BOE.8.001332).
Abstract
Single molecule super-resolution microscopy enables imaging at sub-diffraction-limit resolution by producing images of subsets of stochastically photoactivated fluorophores over a sequence of frames. In each frame of the sequence, the fluorophores are accurately localized, and the estimated locations are used to construct a high-resolution image of the cellular structures labeled by the fluorophores. Many methods have been developed for localizing fluorophores from the images. The majority of these methods comprise two separate steps: detection and estimation. In the detection step, fluorophores are identified. In the estimation step, the locations of the identified fluorophores are estimated through an iterative approach. Here, we propose a non-iterative state space-based localization method which combines the detection and estimation steps. We demonstrate that the estimated locations obtained from the proposed method can be used as initial conditions in an estimation routine to potentially obtain improved location estimates. The proposed method models the given image as the frequency response of a multi-order system obtained with a balanced state space realization algorithm based on the singular value decomposition of a Hankel matrix. The locations of the poles of the resulting system determine the peak locations in the frequency domain, and the locations of the most significant peaks correspond to the single molecule locations in the original image. The performance of the method is validated using both simulated and experimental data.
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More information
Accepted/In Press date: 30 January 2017
e-pub ahead of print date: 6 February 2017
Published date: 1 March 2017
Keywords:
And statistics, Fluorescence microscopy, Image analysis, Image reconstruction techniques, Probability theory, Stochastic processes, Superresolution
Identifiers
Local EPrints ID: 423682
URI: http://eprints.soton.ac.uk/id/eprint/423682
ISSN: 2156-7085
PURE UUID: 1111b8c7-1485-46fb-8644-48e1a37863e7
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Date deposited: 27 Sep 2018 16:30
Last modified: 18 Mar 2024 03:48
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Contributors
Author:
Milad R. Vahid
Author:
Jerry Chao
Author:
Dongyoung Kim
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