A fast CLSM undersampling image reconstruction framework with precise stage positioning for random measurements

Kuang Yao Chang, Yi Lin Liu, Da Wei Liu, Meng Hao Chou, Jim Wei Wu, Li Chen Fu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Confocal laser scanning microscopy (CLSM) is a powerful non-destructive optical measurement system. Recently, compressive sensing (CS) is applied to the field of CLSM for high speed scan by reducing the number of sampled data required to reconstruct an accurate imaging information. However, the CS recovery algorithm employed in CLSM applications is iteration-based optimization method of which computation complexity is relatively high. In this paper, we propose a non-iteration-based deep residual convolutional neural network compressive sensing reconstruction framework (DRCNN-CSR) in end-to-end manner. Both of the computation time and the quality of reconstructed image are largely improved with this novel model. The experiment results demonstrate that our proposed method outperforms other existing reconstruction algorithm under a wide range of undersampling rates with respect to reconstruction quality comparison. In addition, CS is based on predefined random location sampling; consequently, the fast and precise positioning of scanner is required. We design the adaptive control algorithm for a piezo-driven stage to implement the CS approach in CLSM imaging; the stability of our control system design is proved by Lyapunov theorem.

Original languageEnglish
Title of host publication2017 Asian Control Conference, ASCC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1122-1127
Number of pages6
ISBN (Electronic)9781509015733
DOIs
StatePublished - 7 Feb 2018
Event2017 11th Asian Control Conference, ASCC 2017 - Gold Coast, Australia
Duration: 17 Dec 201720 Dec 2017

Publication series

Name2017 Asian Control Conference, ASCC 2017
Volume2018-January

Conference

Conference2017 11th Asian Control Conference, ASCC 2017
Country/TerritoryAustralia
CityGold Coast
Period17/12/1720/12/17

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