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Compressed sensing in fluorescence microscopy. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2022; 168:66-80. [PMID: 34153330 DOI: 10.1016/j.pbiomolbio.2021.06.004] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Revised: 05/29/2021] [Accepted: 06/07/2021] [Indexed: 12/30/2022]
Abstract
Compressed sensing (CS) is a signal processing approach that solves ill-posed inverse problems, from under-sampled data with respect to the Nyquist criterium. CS exploits sparsity constraints based on the knowledge of prior information, relative to the structure of the object in the spatial or other domains. It is commonly used in image and video compression as well as in scientific and medical applications, including computed tomography and magnetic resonance imaging. In the field of fluorescence microscopy, it has been demonstrated to be valuable for fast and high-resolution imaging, from single-molecule localization, super-resolution to light-sheet microscopy. Furthermore, CS has found remarkable applications in the field of mesoscopic imaging, facilitating the study of small animals' organs and entire organisms. This review article illustrates the working principles of CS, its implementations in optical imaging and discusses several relevant uses of CS in the field of fluorescence imaging from super-resolution microscopy to mesoscopy.
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Ghezzi A, Farina A, Bassi A, Valentini G, Labanca I, Acconcia G, Rech I, D'Andrea C. Multispectral compressive fluorescence lifetime imaging microscopy with a SPAD array detector. OPTICS LETTERS 2021; 46:1353-1356. [PMID: 33720185 DOI: 10.1364/ol.419381] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Accepted: 02/06/2021] [Indexed: 05/22/2023]
Abstract
Multispectral/hyperspectral fluorescence lifetime imaging microscopy (λFLIM) is a promising tool for studying functional and structural biological processes. The rich information content provided by a multidimensional dataset is often in contrast with the acquisition speed. In this work, we develop and experimentally demonstrate a wide-field λFLIM setup, based on a novel time-resolved 18×1 single-photon avalanche diode array detector working in a single-pixel camera scheme, which parallelizes the spectral detection, reducing measurement time. The proposed system, which implements a single-pixel camera with a compressive sensing scheme, represents an optimal microscopy framework towards the design of λFLIM setups.
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Mozumder M, Tarvainen T. Evaluation of temporal moments and Fourier transformed data in time-domain diffuse optical tomography. JOURNAL OF THE OPTICAL SOCIETY OF AMERICA. A, OPTICS, IMAGE SCIENCE, AND VISION 2020; 37:1845-1856. [PMID: 33362126 DOI: 10.1364/josaa.405541] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Accepted: 10/03/2020] [Indexed: 06/12/2023]
Abstract
Time-domain diffuse optical tomography (TD-DOT) uses near-infrared pulsed lasers as light sources to measure time-varying exitance on the boundary of the target. These are used to estimate optical properties of the imaged target. Several integral-transform-based moments of the time-resolved data have been utilized in TD-DOT, the most common being the mean time of flight and variance. Recently, it has been shown that Fourier transforming the time-domain data to frequency domain enables utilization of these data at one or several frequencies, producing equally as good estimates as the whole time-domain data. In this work, we present a systematic comparison of the usage of the temporal moments and Fourier transformed data in TD-DOT. Both absolute and difference imaging are evaluated using numerical simulations. The simulations show that utilizing temporal moments and Fourier transformed data in TD-DOT provides good quality reconstructions with a good estimation accuracy. These estimates are improved if more than one data type is used. Furthermore, the simulations show that the frequency-domain computations enable computationally cheaper and straightforward implementation of the inverse solver when compared to the temporal moments.
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Mellors BOL, Bentley A, Spear AM, Howle CR, Dehghani H. Applications of compressive sensing in spatial frequency domain imaging. JOURNAL OF BIOMEDICAL OPTICS 2020; 25:JBO-200205SSR. [PMID: 33179460 PMCID: PMC7657414 DOI: 10.1117/1.jbo.25.11.112904] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Accepted: 10/19/2020] [Indexed: 06/11/2023]
Abstract
SIGNIFICANCE Spatial frequency domain imaging (SFDI) is an imaging modality that projects spatially modulated light patterns to determine optical property maps for absorption and reduced scattering of biological tissue via a pixel-by-pixel data acquisition and analysis procedure. Compressive sensing (CS) is a signal processing methodology which aims to reproduce the original signal with a reduced number of measurements, addressing the pixel-wise nature of SFDI. These methodologies have been combined for complex heterogenous data in both the image detection and data analysis stage in a compressive sensing SFDI (cs-SFDI) approach, showing reduction in both the data acquisition and overall computational time. AIM Application of CS in SFDI data acquisition and image reconstruction significantly improves data collection and image recovery time without loss of quantitative accuracy. APPROACH cs-SFDI has been applied to an increased heterogenic sample from the AppSFDI data set (back of the hand), highlighting the increased number of CS measurements required as compared to simple phantoms to accurately obtain optical property maps. A novel application of CS to the parameter recovery stage of image analysis has also been developed and validated. RESULTS Dimensionality reduction has been demonstrated using the increased heterogenic sample at both the acquisition and analysis stages. A data reduction of 30% for the cs-SFDI and up to 80% for the parameter recover was achieved as compared to traditional SFDI, while maintaining an error of <10 % for the recovered optical property maps. CONCLUSION The application of data reduction through CS demonstrates additional capabilities for multi- and hyperspectral SFDI, providing advanced optical and physiological property maps.
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Affiliation(s)
- Ben O. L. Mellors
- University of Birmingham, College of Engineering and Physical Sciences, Physical Sciences for Health Doctoral Training Centre, Birmingham, United Kingdom
- University of Birmingham, College of Engineering and Physical Sciences, School of Computer Science, Birmingham, United Kingdom
| | - Alexander Bentley
- University of Birmingham, College of Engineering and Physical Sciences, Physical Sciences for Health Doctoral Training Centre, Birmingham, United Kingdom
- University of Birmingham, College of Engineering and Physical Sciences, School of Computer Science, Birmingham, United Kingdom
| | - Abigail M. Spear
- Defence Science and Technology Laboratory, Salisbury, United Kingdom
| | | | - Hamid Dehghani
- University of Birmingham, College of Engineering and Physical Sciences, School of Computer Science, Birmingham, United Kingdom
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Algarawi M, Erkol H, Luk A, Ha S, Ünlü MB, Gulsen G, Nouizi F. Resolving tissue chromophore concentration at MRI resolution using multi-wavelength photo-magnetic imaging. BIOMEDICAL OPTICS EXPRESS 2020; 11:4244-4254. [PMID: 32923039 PMCID: PMC7449711 DOI: 10.1364/boe.397538] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Revised: 06/24/2020] [Accepted: 06/30/2020] [Indexed: 06/11/2023]
Abstract
Photo-magnetic imaging (PMI) is an emerging optical imaging modality that showed great performance on providing absorption maps with high resolution and quantitative accuracy. As a multi-modality technology, PMI warms up the imaged object using a near infrared laser while temperature variation is measured using magnetic resonance imaging. By probing tissue at multiple wavelengths, concentration of the main tissue chromophores such as oxy- and deoxy-hemoglobin, lipid, and water are obtained then used to derive functional parameters such as total hemoglobin concentration and relative oxygen saturation. In this paper, we present a multi-wavelength PMI system that was custom-built to host five different laser wavelengths. After recovering the high-resolution absorption maps, a least-squared minimization process was used to resolve the different chromophore concentration. The performance of the system was experimentally tested on a phantom with two different dyes. Their concentrations were successfully assessed with high spatial resolution and average accuracy of nearly 80%.
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Affiliation(s)
- Maha Algarawi
- Center for Functional Onco-Imaging, University of California Irvine, CA 92697, USA
- Department of Physics and Astronomy, University of California Irvine, CA 92697, USA
| | - Hakan Erkol
- Department of Physics, Bogazici University, Istanbul, Turkey
| | - Alex Luk
- Center for Functional Onco-Imaging, University of California Irvine, CA 92697, USA
| | | | - Mehmet B. Ünlü
- Department of Physics, Bogazici University, Istanbul, Turkey
| | - Gultekin Gulsen
- Center for Functional Onco-Imaging, University of California Irvine, CA 92697, USA
- Department of Physics and Astronomy, University of California Irvine, CA 92697, USA
- Department of Radiological Sciences, University of California Irvine, CA 92697, USA
| | - Farouk Nouizi
- Center for Functional Onco-Imaging, University of California Irvine, CA 92697, USA
- Department of Radiological Sciences, University of California Irvine, CA 92697, USA
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Mozumder M, Tarvainen T. Time-domain diffuse optical tomography utilizing truncated Fourier series approximation. JOURNAL OF THE OPTICAL SOCIETY OF AMERICA. A, OPTICS, IMAGE SCIENCE, AND VISION 2020; 37:182-191. [PMID: 32118896 DOI: 10.1364/josaa.37.000182] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/26/2019] [Accepted: 12/04/2019] [Indexed: 05/25/2023]
Abstract
Diffuse optical tomography (DOT) uses near infrared light for in vivo imaging of spatially varying optical parameters in biological tissues. It is known that time-resolved measurements provide the richest information on soft tissues, among other measurement types in DOT such as steady-state and intensity-modulated measurements. Therefore, several integral-transform-based moments of the time-resolved DOT measurements have been considered to estimate spatially distributed optical parameters. However, the use of such moments can result in low-contrast images and cross-talks between the reconstructed optical parameters, limiting their accuracy. In this work, we propose to utilize a truncated Fourier series approximation in time-resolved DOT. Using this approximation, we obtained optical parameter estimates with accuracy comparable to using whole time-resolved data that uses low computational time and resources. The truncated Fourier series approximation based estimates also displayed good contrast and minimal parameter cross-talk, and the estimates further improved in accuracy when multiple Fourier frequencies were used.
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Bentley A, Rowe JE, Dehghani H. Single pixel hyperspectral bioluminescence tomography based on compressive sensing. BIOMEDICAL OPTICS EXPRESS 2019; 10:5549-5564. [PMID: 31799030 PMCID: PMC6865106 DOI: 10.1364/boe.10.005549] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/13/2019] [Revised: 08/07/2019] [Accepted: 09/06/2019] [Indexed: 05/11/2023]
Abstract
Photonics based imaging is a widely utilised technique for the study of biological functions within pre-clinical studies. Specifically, bioluminescence imaging is a sensitive non-invasive and non-contact optical imaging technique that is able to detect distributed (biologically informative) visible and near-infrared activated light sources within tissue, providing information about tissue function. Compressive sensing (CS) is a method of signal processing that works on the basis that a signal or image can be compressed without important information being lost. This work describes the development of a CS based hyperspectral Bioluminescence imaging system that is used to collect compressed fluence data from the external surface of an animal model, due to an internal source, providing lower acquisition times, higher spectral content and potentially better tomographic source localisation. The work demonstrates that hyperspectral surface fluence images of both block and mouse shaped phantom due to internal light sources could be obtained at 30% of the time and measurements it would take to collect the data using conventional raster scanning methods. Using hyperspectral data, tomographic reconstruction of internal light sources can be carried out using any desired number of wavelengths and spectral bandwidth. Reconstructed images of internal light sources using four wavelengths as obtained through CS are presented showing a localisation error of ∼3 mm. Additionally, tomographic images of dual-colored sources demonstrating multi-wavelength light sources being recovered are presented further highlighting the benefits of the hyperspectral system for utilising multi-colored biomarker applications.
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Affiliation(s)
- Alexander Bentley
- School of Computer Science, College of Engineering and Physical Sciences, University of Birmingham, UK
- Physical Sciences for Health Doctoral Training Centre, College of Engineering and Physical Sciences, University of Birmingham, UK
| | - Jonathan E. Rowe
- School of Computer Science, College of Engineering and Physical Sciences, University of Birmingham, UK
| | - Hamid Dehghani
- School of Computer Science, College of Engineering and Physical Sciences, University of Birmingham, UK
- Physical Sciences for Health Doctoral Training Centre, College of Engineering and Physical Sciences, University of Birmingham, UK
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Farina A, Candeo A, Dalla Mora A, Bassi A, Lussana R, Villa F, Valentini G, Arridge S, D'Andrea C. Novel time-resolved camera based on compressed sensing. OPTICS EXPRESS 2019; 27:31889-31899. [PMID: 31684412 DOI: 10.1364/oe.27.031889] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/31/2019] [Accepted: 10/01/2019] [Indexed: 06/10/2023]
Abstract
Time-resolved cameras with high temporal resolution (down to ps) enable a huge set of novel applications ranging from biomedicine and environmental science to material and device characterization. In this work, we propose, and experimentally validate, a novel detection scheme for time-resolved imaging based on a compressed sampling approach. The proposed scheme unifies into a single element all the required operations, i.e. space modulation, space integration and time-resolved detection, paving the way to dramatic cost reduction, performance improvement and ease of use.
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Aguénounon E, Dadouche F, Uhring W, Ducros N, Gioux S. Single snapshot imaging of optical properties using a single-pixel camera: a simulation study. JOURNAL OF BIOMEDICAL OPTICS 2019; 24:1-6. [PMID: 31037929 PMCID: PMC6995955 DOI: 10.1117/1.jbo.24.7.071612] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2019] [Accepted: 03/29/2019] [Indexed: 05/29/2023]
Abstract
We present the effects of using a single-pixel camera approach to extract optical properties with the single-snapshot spatial frequency-domain imaging method. We acquired images of a human hand for spatial frequencies ranging from 0.1 to 0.4 mm - 1 with increasing compression ratios using adaptive basis scan wavelet prediction strategy. In summary, our findings indicate that the extracted optical properties remained usable up to 99% of compression rate at a spatial frequency of 0.2 mm - 1 with errors of 5% in reduced scattering and 10% in absorption.
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Affiliation(s)
| | - Foudil Dadouche
- University of Strasbourg, ICube Laboratory, Illkirch, France
| | - Wilfried Uhring
- University of Strasbourg, ICube Laboratory, Illkirch, France
| | - Nicolas Ducros
- University Lyon, INSA Lyon, UCBL, CNRS 5220, INSERM U1206, CREATIS, Villeurbanne, France
| | - Sylvain Gioux
- University of Strasbourg, ICube Laboratory, Illkirch, France
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Pian Q, Yao R, Intes X. Hyperspectral wide-field time domain single-pixel diffuse optical tomography platform. BIOMEDICAL OPTICS EXPRESS 2018; 9:6258-6272. [PMID: 31065427 PMCID: PMC6491017 DOI: 10.1364/boe.9.006258] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/27/2018] [Revised: 08/27/2018] [Accepted: 09/09/2018] [Indexed: 05/18/2023]
Abstract
We present the design and comprehensive instrumental characterization of a time domain diffuse optical tomography (TD-DOT) platform based on wide-field illumination and wide-field hyperspectral time-resolved single-pixel detection for functional and molecular imaging in turbid media. The proposed platform combines two digital micro-mirror devices (DMDs) to generate structured light and a spectrally resolved multi-anode photomultiplier tube (PMT) detector in time domain for hyperspectral data acquisition over 16 wavelength channels based on the time-correlated single-photon counting (TCSPC) technique. The design of the proposed platform is described in detail and its characteristics in spatial, temporal and spectral dimensions are calibrated and presented. The performance of the system is further validated through a phantom study where two absorbers in glass tubes with spectral contrast are mapped in a turbid medium of ~20 mm thickness. The method presented here offers the potential of accelerating the imaging process and improving reconstruction results in TD-DOT and thus facilitates its wide spread use in preclinical and clinical in vivo imaging scenarios.
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Affiliation(s)
- Qi Pian
- Biomedical Engineering Department, Rensselaer Polytechnic Institute, Troy, NY 12180, USA
- Currently with Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Ruoyang Yao
- Biomedical Engineering Department, Rensselaer Polytechnic Institute, Troy, NY 12180, USA
| | - Xavier Intes
- Biomedical Engineering Department, Rensselaer Polytechnic Institute, Troy, NY 12180, USA
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Salvador-Balaguer E, Latorre-Carmona P, Chabert C, Pla F, Lancis J, Tajahuerce E. Low-cost single-pixel 3D imaging by using an LED array. OPTICS EXPRESS 2018; 26:15623-15631. [PMID: 30114820 DOI: 10.1364/oe.26.015623] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/02/2018] [Accepted: 05/17/2018] [Indexed: 06/08/2023]
Abstract
We propose a method to perform color imaging with a single photodiode by using light structured illumination generated with a low-cost color LED array. The LED array is used to generate a sequence of color Hadamard patterns which are projected onto the object by a simple optical system while the photodiode records the light intensity. A field programmable gate array (FPGA) controls the LED panel allowing us to obtain high refresh rates up to 10 kHz. The system is extended to 3D imaging by simply adding a low number of photodiodes at different locations. The 3D shape of the object is obtained by using a non-calibrated photometric stereo technique. Experimental results are provided for an LED array with 32 × 32 elements.
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Rousset F, Ducros N, Peyrin F, Valentini G, D'Andrea C, Farina A. Time-resolved multispectral imaging based on an adaptive single-pixel camera. OPTICS EXPRESS 2018; 26:10550-10558. [PMID: 29715990 DOI: 10.1364/oe.26.010550] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/06/2023]
Abstract
Time-resolved multispectral imaging has many applications in different fields, which range from characterization of biological tissues to environmental monitoring. In particular, optical techniques, such as lidar and fluorescence lifetime imaging, require imaging at the subnanosecond scales over an extended area. In this paper, we demonstrate experimentally a time-resolved multispectral acquisition scheme based on single-pixel imaging. Single-pixel imaging is an emerging paradigm that provides low-cost high-quality images. Here, we use an adaptive strategy that allows acquisition and image reconstruction times to be reduced drastically or full basis scans. Adaptive time-resolved multispectral imaging scheme can have significant applications in biological imaging, at scales from macroscopic to microscopic.
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