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J. Imaging
Special Issues
Current Highlights and Future Applications of Computational Imaging
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Current Highlights and Future Applications of Computational Imaging

A special issue of Journal of Imaging (ISSN 2313-433X). This special issue belongs to the section "Computational Imaging and Computational Photography".

Deadline for manuscript submissions: closed (31 July 2021) | Viewed by 10897

Special Issue Editor

Dr. Stefano Selci

E-Mail Website
Guest Editor
Institute for Photonics and Nanotechnologies, ARTOV C.N.R., Via del Fosso del Cavaliere 100, 00133 Roma, Italy
Interests: scanning electron microscopy; optics; optoelectronics; experimental physics; solid state physics; condensed matter physics; optical physics; photonics; thin films and nanotechnology; nanotechnology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleague,

Computational imaging is quite a recent diversification of conventional imaging systems. Instead of relying on the conventional source—optical block—sample-detector scheme, new techniques have been invented by introducing a computational logical block inserted between the data and the obtained images. Seismic imaging, tomography, computational microscopies, photography and many other technologies not limited by specific interactions, wavelengths or scope fall under this very broad definition.

Among rapidly growing techniques, ptychography smartly solves the inverse optical problem. This means that it gains information about the phase as a part of the decoding process and is available in a broad range of applications, after having been initially sought for high energy imaging needs. Another example is Fresnel incoherent correlation holography (FINCH), which obtains a full 3D image by digitally recording sequentially reflected white light images from a 3D object through a diffractive optical element and reconstructing a full hologram via computer.

The aim of this Special Issue is, therefore, to illustrate the advantages and the potentialities made possible by the advances of powerful and inexpensive computing platforms, realizing new ideas that were simply not possible until a few years ago.

Dr. Stefano Selci
Guest Editor

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. Journal of Imaging is an international peer-reviewed open access monthly 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 1800 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

  • computational microscopy
  • optical microscopy
  • ptychography
  • Fourier ptychography
  • holography
  • 3D imaging

Published Papers (3 papers)

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17 pages, 5020 KiB  
Article
Optical Imaging of Magnetic Particle Cluster Oscillation and Rotation in Glycerol
by River Gassen, Dennis Thompkins, Austin Routt, Philippe Jones, Meghan Smith, William Thompson, Paul Couture, Dmytro A. Bozhko, Zbigniew Celinski, Robert E. Camley, Guy M. Hagen and Kathrin Spendier
J. Imaging 2021, 7(5), 82; https://0-doi-org.brum.beds.ac.uk/10.3390/jimaging7050082 - 29 Apr 2021
Cited by 2 | Viewed by 2091
Abstract
Magnetic particles have been evaluated for their biomedical applications as a drug delivery system to treat asthma and other lung diseases. In this study, ferromagnetic barium hexaferrite (BaFe12O19) and iron oxide (Fe3O4) particles were suspended [...] Read more.
Magnetic particles have been evaluated for their biomedical applications as a drug delivery system to treat asthma and other lung diseases. In this study, ferromagnetic barium hexaferrite (BaFe12O19) and iron oxide (Fe3O4) particles were suspended in water or glycerol, as glycerol can be 1000 times more viscous than water. The particle concentration was 2.50 mg/mL for BaFe12O19 particle clusters and 1.00 mg/mL for Fe3O4 particle clusters. The magnetic particle cluster cross-sectional area ranged from 15 to 1000 μμm2, and the particle cluster diameter ranged from 5 to 45 μμm. The magnetic particle clusters were exposed to oscillating or rotating magnetic fields and imaged with an optical microscope. The oscillation frequency of the applied magnetic fields, which was created by homemade wire spools inserted into an optical microscope, ranged from 10 to 180 Hz. The magnetic field magnitudes varied from 0.25 to 9 mT. The minimum magnetic field required for particle cluster rotation or oscillation in glycerol was experimentally measured at different frequencies. The results are in qualitative agreement with a simplified model for single-domain magnetic particles, with an average deviation from the model of 1.7 ± 1.3. The observed difference may be accounted for by the fact that our simplified model does not include effects on particle cluster motion caused by randomly oriented domains in multi-domain magnetic particle clusters, irregular particle cluster size, or magnetic anisotropy, among other effects. Full article
(This article belongs to the Special Issue Current Highlights and Future Applications of Computational Imaging)
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20 pages, 12719 KiB  
Article
Two-Stage Alignment of FIB-SEM Images of Rock Samples
by Iryna Reimers, Ilia Safonov, Anton Kornilov and Ivan Yakimchuk
J. Imaging 2020, 6(10), 107; https://0-doi-org.brum.beds.ac.uk/10.3390/jimaging6100107 - 10 Oct 2020
Cited by 3 | Viewed by 4047
Abstract
Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) tomography provides a stack of images that represent serial slices of the sample. These images are displaced relatively to each other, and an alignment procedure is required. Traditional methods for alignment of a 3D image are [...] Read more.
Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) tomography provides a stack of images that represent serial slices of the sample. These images are displaced relatively to each other, and an alignment procedure is required. Traditional methods for alignment of a 3D image are based on a comparison of two adjacent slices. However, such algorithms are easily confused by anisotropy in the sample structure or even experiment geometry in the case of porous media. This may lead to significant distortions in the pore space geometry, if there are no stable fiducial marks in the frame. In this paper, we propose a new method, which meaningfully extends existing alignment procedures. Our technique allows the correction of random misalignments between slices and, at the same time, preserves the overall geometrical structure of the specimen. We consider displacements produced by existing alignment algorithms as a signal and decompose it into low and high-frequency components. Final transformations exclude slow variations and contain only high frequency variations that represent random shifts that need to be corrected. The proposed algorithm can operate with not only translations but also with arbitrary affine transformations. We demonstrate the performance of our approach on a synthetic dataset and two real FIB-SEM images of natural rock. Full article
(This article belongs to the Special Issue Current Highlights and Future Applications of Computational Imaging)
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11 pages, 5850 KiB  
Tutorial
Lensless Three-Dimensional Quantitative Phase Imaging Using Phase Retrieval Algorithm
by Vijayakumar Anand, Tomas Katkus, Denver P. Linklater, Elena P. Ivanova and Saulius Juodkazis
J. Imaging 2020, 6(9), 99; https://0-doi-org.brum.beds.ac.uk/10.3390/jimaging6090099 - 20 Sep 2020
Cited by 22 | Viewed by 4038
Abstract
Quantitative phase imaging (QPI) techniques are widely used for the label-free examining of transparent biological samples. QPI techniques can be broadly classified into interference-based and interferenceless methods. The interferometric methods which record the complex amplitude are usually bulky with many optical components and [...] Read more.
Quantitative phase imaging (QPI) techniques are widely used for the label-free examining of transparent biological samples. QPI techniques can be broadly classified into interference-based and interferenceless methods. The interferometric methods which record the complex amplitude are usually bulky with many optical components and use coherent illumination. The interferenceless approaches which need only the intensity distribution and works using phase retrieval algorithms have gained attention as they require lesser resources, cost, space and can work with incoherent illumination. With rapid developments in computational optical techniques and deep learning, QPI has reached new levels of applications. In this tutorial, we discuss one of the basic optical configurations of a lensless QPI technique based on the phase-retrieval algorithm. Simulative studies on QPI of thin, thick, and greyscale phase objects with assistive pseudo-codes and computational codes in Octave is provided. Binary phase samples with positive and negative resist profiles were fabricated using lithography, and a single plane and two plane phase objects were constructed. Light diffracted from a point object is modulated by phase samples and the corresponding intensity patterns are recorded. The phase retrieval approach is applied for 2D and 3D phase reconstructions. Commented codes in Octave for image acquisition and automation using a web camera in an open source operating system are provided. Full article
(This article belongs to the Special Issue Current Highlights and Future Applications of Computational Imaging)
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