3D Image Reconstruction from Multi-Focus Microscope: Axial Super-Resolution and Multiple-Frame Processing

Seunghwan Yoo, Pablo Ruiz, Xiang Huang, Kuan He, Nicola J Ferrier, Mark Hereld, Alan Selewa, Matthew Daddysman, Norbert F. Scherer, Oliver Strides Cossairt, Aggelos K Katsaggelos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Multi-focus microscope (MFM) provides a way to obtain 3D information by simultaneously capturing multiple focal planes. The naive method for MFM reconstruction is to stack the sub-images with alignment. However, the resolution in the z-axis in this method is limited by the number of acquired focal planes. In this work we build on a recent reconstruction algorithm for MFM, using information from multiple frames to improve the reconstruction quality. We propose two multiple-frame MFM image reconstruction algorithms: batch and recursive approaches. In the batch approach, we take multiple MFM frames and jointly estimate the 3D image and the motion for each frame. In the recursive approach, we utilize the reconstructed image from the previous frame. Experimental results show that the proposed algorithms produce a sequence of 3D object reconstruction with high quality that enable reconstruction of dynamic extended objects.
Original languageEnglish (US)
Title of host publication2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
PublisherIEEE
DOIs
StatePublished - 2018

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Image reconstruction
Microscopes
Processing

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Yoo, S., Ruiz, P., Huang, X., He, K., Ferrier, N. J., Hereld, M., ... Katsaggelos, A. K. (2018). 3D Image Reconstruction from Multi-Focus Microscope: Axial Super-Resolution and Multiple-Frame Processing. In 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) IEEE. https://doi.org/10.1109/ICASSP.2018.8462234
Yoo, Seunghwan ; Ruiz, Pablo ; Huang, Xiang ; He, Kuan ; Ferrier, Nicola J ; Hereld, Mark ; Selewa, Alan ; Daddysman, Matthew ; Scherer, Norbert F. ; Cossairt, Oliver Strides ; Katsaggelos, Aggelos K. / 3D Image Reconstruction from Multi-Focus Microscope : Axial Super-Resolution and Multiple-Frame Processing. 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2018.
@inproceedings{17de577a0a6b4e3298424773213df2c7,
title = "3D Image Reconstruction from Multi-Focus Microscope: Axial Super-Resolution and Multiple-Frame Processing",
abstract = "Multi-focus microscope (MFM) provides a way to obtain 3D information by simultaneously capturing multiple focal planes. The naive method for MFM reconstruction is to stack the sub-images with alignment. However, the resolution in the z-axis in this method is limited by the number of acquired focal planes. In this work we build on a recent reconstruction algorithm for MFM, using information from multiple frames to improve the reconstruction quality. We propose two multiple-frame MFM image reconstruction algorithms: batch and recursive approaches. In the batch approach, we take multiple MFM frames and jointly estimate the 3D image and the motion for each frame. In the recursive approach, we utilize the reconstructed image from the previous frame. Experimental results show that the proposed algorithms produce a sequence of 3D object reconstruction with high quality that enable reconstruction of dynamic extended objects.",
author = "Seunghwan Yoo and Pablo Ruiz and Xiang Huang and Kuan He and Ferrier, {Nicola J} and Mark Hereld and Alan Selewa and Matthew Daddysman and Scherer, {Norbert F.} and Cossairt, {Oliver Strides} and Katsaggelos, {Aggelos K}",
year = "2018",
doi = "10.1109/ICASSP.2018.8462234",
language = "English (US)",
booktitle = "2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)",
publisher = "IEEE",

}

Yoo, S, Ruiz, P, Huang, X, He, K, Ferrier, NJ, Hereld, M, Selewa, A, Daddysman, M, Scherer, NF, Cossairt, OS & Katsaggelos, AK 2018, 3D Image Reconstruction from Multi-Focus Microscope: Axial Super-Resolution and Multiple-Frame Processing. in 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE. https://doi.org/10.1109/ICASSP.2018.8462234

3D Image Reconstruction from Multi-Focus Microscope : Axial Super-Resolution and Multiple-Frame Processing. / Yoo, Seunghwan; Ruiz, Pablo; Huang, Xiang; He, Kuan; Ferrier, Nicola J; Hereld, Mark; Selewa, Alan; Daddysman, Matthew; Scherer, Norbert F.; Cossairt, Oliver Strides; Katsaggelos, Aggelos K.

2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2018.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - 3D Image Reconstruction from Multi-Focus Microscope

T2 - Axial Super-Resolution and Multiple-Frame Processing

AU - Yoo, Seunghwan

AU - Ruiz, Pablo

AU - Huang, Xiang

AU - He, Kuan

AU - Ferrier, Nicola J

AU - Hereld, Mark

AU - Selewa, Alan

AU - Daddysman, Matthew

AU - Scherer, Norbert F.

AU - Cossairt, Oliver Strides

AU - Katsaggelos, Aggelos K

PY - 2018

Y1 - 2018

N2 - Multi-focus microscope (MFM) provides a way to obtain 3D information by simultaneously capturing multiple focal planes. The naive method for MFM reconstruction is to stack the sub-images with alignment. However, the resolution in the z-axis in this method is limited by the number of acquired focal planes. In this work we build on a recent reconstruction algorithm for MFM, using information from multiple frames to improve the reconstruction quality. We propose two multiple-frame MFM image reconstruction algorithms: batch and recursive approaches. In the batch approach, we take multiple MFM frames and jointly estimate the 3D image and the motion for each frame. In the recursive approach, we utilize the reconstructed image from the previous frame. Experimental results show that the proposed algorithms produce a sequence of 3D object reconstruction with high quality that enable reconstruction of dynamic extended objects.

AB - Multi-focus microscope (MFM) provides a way to obtain 3D information by simultaneously capturing multiple focal planes. The naive method for MFM reconstruction is to stack the sub-images with alignment. However, the resolution in the z-axis in this method is limited by the number of acquired focal planes. In this work we build on a recent reconstruction algorithm for MFM, using information from multiple frames to improve the reconstruction quality. We propose two multiple-frame MFM image reconstruction algorithms: batch and recursive approaches. In the batch approach, we take multiple MFM frames and jointly estimate the 3D image and the motion for each frame. In the recursive approach, we utilize the reconstructed image from the previous frame. Experimental results show that the proposed algorithms produce a sequence of 3D object reconstruction with high quality that enable reconstruction of dynamic extended objects.

U2 - 10.1109/ICASSP.2018.8462234

DO - 10.1109/ICASSP.2018.8462234

M3 - Conference contribution

BT - 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

PB - IEEE

ER -

Yoo S, Ruiz P, Huang X, He K, Ferrier NJ, Hereld M et al. 3D Image Reconstruction from Multi-Focus Microscope: Axial Super-Resolution and Multiple-Frame Processing. In 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE. 2018 https://doi.org/10.1109/ICASSP.2018.8462234