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Three-Dimensional (3D) Biophotonics Sensing and Reconstruction towards Biomedical Research
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Three-Dimensional (3D) Biophotonics Sensing and Reconstruction towards Biomedical Research

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensing and Imaging".

Deadline for manuscript submissions: closed (31 May 2022) | Viewed by 17982

Special Issue Editors

Dr. Ana Doblas

E-Mail Website
Guest Editor
Department of Electrical and Computer Engineering, The University of Memphis, Memphis, TN 38152, USA
Interests: biomedical systems; optical imaging systems for microscopy; multidimensional imaging techniques; computational imaging for microscopy
Special Issues, Collections and Topics in MDPI journals
Dr. Carlos Trujillo

E-Mail Website
Guest Editor
School of Applied Sciences and Engineering – Fundamental Sciences, Universidad EAFIT, Medellin, Colombia
Interests: optical systems; deep learning techniques; computational imaging strategies
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The purpose of emerging biophotonics sensors, including simultaneous hardware and software development, is to enable the observation of biological cells,  organisms, and systems with a high sensitivity, accuracy, and spatial and temporal resolutions. Such achievements have unraveled novel dynamics and mechanism of biological systems, hence encouraging the scientific community to advance the design and implementation of novel three-dimensional imaging sensing and reconstruction methods. This Special Feature calls for innovative and original contributions in the development of imaging sensing and reconstruction approaches that extend the capabilities of existing techniques in terms of spatial resolution, imaging depth, imaging speed, or any other feature relevant for biomedical research.

Topics of interest include, but are not limited to, the following:

  • Development and performance of new detectors.
  • Development and performance of new sources and light-shaping devices.
  • Development and performance of novel three-dimensional imaging sensing systems.
  • Investigation of new features and applications using imaging reconstruction post-processing technologies.
  • Development and performance of new computational imaging approaches, for instance, compressive sensing and machine learning techniques, including different and adapted versions of deep neural network (DNN) strategies.

Dr. Ana Doblas
Dr. Carlos Trujillo
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • physical sensors
  • biosensors
  • lab-on-a-chip
  • sensor devices
  • sensor technology and application
  • signal processing
  • deep learning in sensor systems
  • sensing systems

Published Papers (7 papers)

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Research

8 pages, 1212 KiB  
Communication
Real-Time Reflectance Measurement Using an Astigmatic Optical Profilometer
by Hsien-Shun Liao, Ya-Kang Huang, Jian-Yuan Syu-Gu and En-Te Hwu
Sensors 2022, 22(16), 6242; https://doi.org/10.3390/s22166242 - 19 Aug 2022
Viewed by 1160
Abstract
An astigmatic optical profilometer with a commercial optical pickup head provides benefits, such as high resolution, compact size, and low cost. To eliminate artifacts caused by complex materials with different reflectances, a z-axis modulation mode is proposed to obtain quantitative surface morphology by [...] Read more.
An astigmatic optical profilometer with a commercial optical pickup head provides benefits, such as high resolution, compact size, and low cost. To eliminate artifacts caused by complex materials with different reflectances, a z-axis modulation mode is proposed to obtain quantitative surface morphology by measuring S curves on all image pixels. Moreover, the slope of the linear region in the S curve shows a positive relationship with the surface reflectance. However, the slope was calculated using an offline curve fitting method, which did not allow real-time reflectance imaging. Furthermore, quantitative reflectance data were unavailable because of the lack of calibration. In this study, we propose a novel method for real-time reflectance imaging by measuring the amplitude of a focus error signal (FES). The calibration results displayed a linear relationship between the FES amplitude and reflectance. The reflectance image of a grating sample with chrome patterns on a glass substrate demonstrates accurate reflectance measurements with a micrometer spatial resolution. Full article
(This article belongs to the Special Issue Three-Dimensional (3D) Biophotonics Sensing and Reconstruction towards Biomedical Research)
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17 pages, 6040 KiB  
Article
Reconstructing a Deblurred 3D Structure in a Turbid Medium from a Single Blurred 2D Image—For Near-Infrared Transillumination Imaging of a Human Body
by Koichi Shimizu, Sihan Xian and Jiekai Guo
Sensors 2022, 22(15), 5747; https://doi.org/10.3390/s22155747 - 1 Aug 2022
Cited by 3 | Viewed by 1531
Abstract
To provide another modality for three-dimensional (3D) medical imaging, new techniques were developed to reconstruct a 3D structure in a turbid medium from a single blurred 2D image obtained using near-infrared transillumination imaging. One technique uses 1D information of a curvilinear absorber, or [...] Read more.
To provide another modality for three-dimensional (3D) medical imaging, new techniques were developed to reconstruct a 3D structure in a turbid medium from a single blurred 2D image obtained using near-infrared transillumination imaging. One technique uses 1D information of a curvilinear absorber, or the intensity profile across the absorber image. Profiles in different conditions are calculated by convolution with the depth-dependent point spread function (PSF) of the transillumination image. In databanks, profiles are stored as lookup tables to connect the contrast and spread of the profile to the absorber depth. One-to-one correspondence from the contrast and spread to the absorber depth and thickness were newly found. Another technique uses 2D information of the transillumination image of a volumetric absorber. A blurred 2D image is deconvolved with the depth-dependent PSF, thereby producing many images with points of focus on different parts. The depth of the image part can be estimated by searching the deconvolved images for the image part in the best focus. To suppress difficulties of high-spatial-frequency noise, we applied a noise-robust focus stacking method. Experimentation verified the feasibility of the proposed techniques, and suggested their applicability to curvilinear and volumetric absorbers such as blood vessel networks and cancerous lesions in tissues. Full article
(This article belongs to the Special Issue Three-Dimensional (3D) Biophotonics Sensing and Reconstruction towards Biomedical Research)
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12 pages, 3520 KiB  
Article
Single-Shot 3D Topography of Transmissive and Reflective Samples with a Dual-Mode Telecentric-Based Digital Holographic Microscope
by Ana Doblas, Charity Hayes-Rounds, Rohan Isaac and Felio Perez
Sensors 2022, 22(10), 3793; https://doi.org/10.3390/s22103793 - 17 May 2022
Cited by 3 | Viewed by 4623
Abstract
Common path DHM systems are the most robust DHM systems as they are based on self-interference and are thus less prone to external fluctuations. A common issue amongst these DHM systems is that the two replicas of the sample’s information overlay due to [...] Read more.
Common path DHM systems are the most robust DHM systems as they are based on self-interference and are thus less prone to external fluctuations. A common issue amongst these DHM systems is that the two replicas of the sample’s information overlay due to self-interference, making them only suitable for imaging sparse samples. This overlay has restricted the use of common-path DHM systems in material science. The overlay can be overcome by limiting the sample’s field of view to occupy only half of the imaging field of view or by using an optical spatial filter. In this work, we have implemented optical spatial filtering in a common-path DHM system using a Fresnel biprism. We have analyzed the optimal pinhole size by evaluating the frequency content of the reconstructed phase images of a star target. We have also measured the accuracy of the system and the sensitivity to noise for different pinhole sizes. Finally, we have proposed the first dual-mode common-path DHM system using a Fresnel biprism. The performance of the dual-model DHM system has been evaluated experimentally using transmissive and reflective microscopic samples. Full article
(This article belongs to the Special Issue Three-Dimensional (3D) Biophotonics Sensing and Reconstruction towards Biomedical Research)
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8 pages, 2361 KiB  
Communication
Use of a Rotating Square Spatial-Frequency Filter to Map the Optical Path Length Variation in Microscopic Biological Samples
by Ignacio Iglesias
Sensors 2022, 22(5), 1842; https://doi.org/10.3390/s22051842 - 25 Feb 2022
Viewed by 1375
Abstract
Gradient images can be obtained using a rotating square mask to filter the angular spectra of the wavefront generated by a complex transmittance object. This method can be applied to measure the three-dimensional structure of microscopic biological samples through the relationship of the [...] Read more.
Gradient images can be obtained using a rotating square mask to filter the angular spectra of the wavefront generated by a complex transmittance object. This method can be applied to measure the three-dimensional structure of microscopic biological samples through the relationship of the phase with the optical path length. This work describes the implementation of a system using an inverted optical microscope and shows the experimental results of phase maps generated by boar sperm cells. Full article
(This article belongs to the Special Issue Three-Dimensional (3D) Biophotonics Sensing and Reconstruction towards Biomedical Research)
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17 pages, 5051 KiB  
Article
Design, Calibration, and Application of a Robust, Cost-Effective, and High-Resolution Lensless Holographic Microscope
by Jose Angel Picazo-Bueno, Karina Trindade, Martin Sanz and Vicente Micó
Sensors 2022, 22(2), 553; https://doi.org/10.3390/s22020553 - 11 Jan 2022
Cited by 7 | Viewed by 2669
Abstract
Lensless holographic microscope (LHM) is an emerging very promising technology that provides high-quality imaging and analysis of biological samples without utilizing any lens for imaging. Due to its small size and reduced price, LHM can be a very useful tool for the point-of-care [...] Read more.
Lensless holographic microscope (LHM) is an emerging very promising technology that provides high-quality imaging and analysis of biological samples without utilizing any lens for imaging. Due to its small size and reduced price, LHM can be a very useful tool for the point-of-care diagnosis of diseases, sperm assessment, or microfluidics, among others, not only employed in advanced laboratories but also in poor and/or remote areas. Recently, several LHMs have been reported in the literature. However, complete characterization of their optical parameters remains not much presented yet. Hence, we present a complete analysis of the performance of a compact, reduced cost, and high-resolution LHM. In particular, optical parameters such as lateral and axial resolutions, lateral magnification, and field of view are discussed into detail, comparing the experimental results with the expected theoretical values for different layout configurations. We use high-resolution amplitude and phase test targets and several microbeads to characterize the proposed microscope. This characterization is used to define a balanced and matched setup showing a good compromise between the involved parameters. Finally, such a microscope is utilized for visualization of static, as well as dynamic biosamples. Full article
(This article belongs to the Special Issue Three-Dimensional (3D) Biophotonics Sensing and Reconstruction towards Biomedical Research)
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18 pages, 4835 KiB  
Article
Video-Rate Quantitative Phase Imaging Using a Digital Holographic Microscope and a Generative Adversarial Network
by Raul Castaneda, Carlos Trujillo and Ana Doblas
Sensors 2021, 21(23), 8021; https://doi.org/10.3390/s21238021 - 1 Dec 2021
Cited by 13 | Viewed by 3262
Abstract
The conventional reconstruction method of off-axis digital holographic microscopy (DHM) relies on computational processing that involves spatial filtering of the sample spectrum and tilt compensation between the interfering waves to accurately reconstruct the phase of a biological sample. Additional computational procedures such as [...] Read more.
The conventional reconstruction method of off-axis digital holographic microscopy (DHM) relies on computational processing that involves spatial filtering of the sample spectrum and tilt compensation between the interfering waves to accurately reconstruct the phase of a biological sample. Additional computational procedures such as numerical focusing may be needed to reconstruct free-of-distortion quantitative phase images based on the optical configuration of the DHM system. Regardless of the implementation, any DHM computational processing leads to long processing times, hampering the use of DHM for video-rate renderings of dynamic biological processes. In this study, we report on a conditional generative adversarial network (cGAN) for robust and fast quantitative phase imaging in DHM. The reconstructed phase images provided by the GAN model present stable background levels, enhancing the visualization of the specimens for different experimental conditions in which the conventional approach often fails. The proposed learning-based method was trained and validated using human red blood cells recorded on an off-axis Mach–Zehnder DHM system. After proper training, the proposed GAN yields a computationally efficient method, reconstructing DHM images seven times faster than conventional computational approaches. Full article
(This article belongs to the Special Issue Three-Dimensional (3D) Biophotonics Sensing and Reconstruction towards Biomedical Research)
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10 pages, 2374 KiB  
Communication
Hyperspectral Three-Dimensional Fluorescence Imaging Using Snapshot Optical Tomography
by Cory Juntunen, Isabel M. Woller and Yongjin Sung
Sensors 2021, 21(11), 3652; https://doi.org/10.3390/s21113652 - 24 May 2021
Cited by 7 | Viewed by 2396
Abstract
Hyperspectral three-dimensional (3D) imaging can provide both 3D structural and functional information of a specimen. The imaging throughput is typically very low due to the requirement of scanning mechanisms for different depths and wavelengths. Here we demonstrate hyperspectral 3D imaging using Snapshot projection [...] Read more.
Hyperspectral three-dimensional (3D) imaging can provide both 3D structural and functional information of a specimen. The imaging throughput is typically very low due to the requirement of scanning mechanisms for different depths and wavelengths. Here we demonstrate hyperspectral 3D imaging using Snapshot projection optical tomography (SPOT) and Fourier-transform spectroscopy (FTS). SPOT allows us to instantaneously acquire the projection images corresponding to different viewing angles, while FTS allows us to perform hyperspectral imaging at high spectral resolution. Using fluorescent beads and sunflower pollens, we demonstrate the imaging performance of the developed system. Full article
(This article belongs to the Special Issue Three-Dimensional (3D) Biophotonics Sensing and Reconstruction towards Biomedical Research)
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