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Advanced Biomedical Optics and Imaging
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Advanced Biomedical Optics and Imaging

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

Deadline for manuscript submissions: closed (15 March 2023) | Viewed by 12097

Special Issue Editor

Prof. Dr. Alexandre Douplik

E-Mail Website
Guest Editor
Department of Physics, Toronto Metropolitan University, 350 Victoria Street, Toronto, ON M5B 2K3, Canada
Interests: biophotonics; photonics; optics; medical lasers

Special Issue Information

Dear Colleagues,

This Special Issue of Sensors is devoted to Advanced Biomedical Optics and Imaging—a rapidly developing field of cutting-edge optical and photonic technologies addressing fundamental and applied biomedical problems, such as early diagnosis and effective treatment of diseases. The papers invited should cover a range of emerging areas in the sections of advanced biomedical imaging and biospectroscopy, novel approaches in biophotonic diagnostics and therapeutics, multimodal and multispectral approaches, biooptical sensing techniques, optical biopsies, nanobiophotonics. and neurophotonics. Papers on these key topics may provide comprehensive reviews of the current situation in the field, future trends, as well as original research results and recent developments, both experimental and theoretical. These studies will contribute to the development of new diagnostic, therapeutic, and theranostic modalities serving healthcare and improving human wellbeing. MDPI provides a rapid publication for all types of papers, including not only short communications and letters but also comprehensive reviews and research studies. A guide for authors on how to submit papers is available on https://www.mdpi.com/journal/sensors/instructions.

Prof. Dr. Alexandre Douplik
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. 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

  • biophotonics
  • biomedical optics
  • biospectroscopy
  • optical bioimaging
  • biosensors
  • photomedicine
  • optical biopsy
  • phototheranostics

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (5 papers)

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Research

17 pages, 171558 KiB  
Communication
Two Filters for Acquiring the Profiles from Images Obtained from Weak-Light Background, Fluorescence Microscope, Transmission Electron Microscope, and Near-Infrared Camera
by Yinghui Huang, Ruoxi Yang, Xin Geng, Zongan Li and Ye Wu
Sensors 2023, 23(13), 6207; https://doi.org/10.3390/s23136207 - 6 Jul 2023
Viewed by 1557
Abstract
Extracting the profiles of images is critical because it can bring simplified description and draw special attention to particular areas in the images. In our work, we designed two filters via the exponential and hypotenuse functions for profile extraction. Their ability to extract [...] Read more.
Extracting the profiles of images is critical because it can bring simplified description and draw special attention to particular areas in the images. In our work, we designed two filters via the exponential and hypotenuse functions for profile extraction. Their ability to extract the profiles from the images obtained from weak-light conditions, fluorescence microscopes, transmission electron microscopes, and near-infrared cameras is proven. Moreover, they can be used to extract the nesting structures in the images. Furthermore, their performance in extracting images degraded by Gaussian noise is evaluated. We used Gaussian white noise with a mean value of 0.9 to create very noisy images. These filters are effective for extracting the edge morphology in the noisy images. For the purpose of a comparative study, we used several well-known filters to process these noisy images, including the filter based on Gabor wavelet, the filter based on the watershed algorithm, and the matched filter, the performances of which in profile extraction are either comparable or not effective when dealing with extensively noisy images. Our filters have shown the potential for use in the field of pattern recognition and object tracking. Full article
(This article belongs to the Special Issue Advanced Biomedical Optics and Imaging)
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18 pages, 5469 KiB  
Article
Design of a Low-Cost Diffuse Optical Mammography System for Biomedical Image Processing in Breast Cancer Diagnosis
by Josué D. Rivera-Fernández, Karen Roa-Tort, Suren Stolik, Alma Valor, Diego A. Fabila-Bustos, Gabriela de la Rosa, Macaria Hernández-Chávez and José M. de la Rosa-Vázquez
Sensors 2023, 23(9), 4390; https://doi.org/10.3390/s23094390 - 29 Apr 2023
Cited by 2 | Viewed by 2577
Abstract
Worldwide, breast cancer is the most common type of cancer that mainly affects women. Several diagnosis techniques based on optical instrumentation and image analysis have been developed, and these are commonly used in conjunction with conventional diagnostic devices such as mammographs, ultrasound, and [...] Read more.
Worldwide, breast cancer is the most common type of cancer that mainly affects women. Several diagnosis techniques based on optical instrumentation and image analysis have been developed, and these are commonly used in conjunction with conventional diagnostic devices such as mammographs, ultrasound, and magnetic resonance imaging of the breast. The cost of using these instruments is increasing, and developing countries, whose deaths indices due to breast cancer are high, cannot access conventional diagnostic methods and have even less access to newer techniques. Other studies, based on the analysis of images acquired by traditional methods, require high resolutions and knowledge of the origin of the captures in order to avoid errors. For this reason, the design of a low-cost diffuse optical mammography system for biomedical image processing in breast cancer diagnosis is presented. The system combines the acquisition of breast tissue photographs, diffuse optical reflectance (as a biophotonics technique), and the processing of digital images for the study and diagnosis of breast cancer. The system was developed in the form of a medical examination table with a 638 nm red-light source, using light-emitted diode technology (LED) and a low-cost web camera for the acquisition of breast tissue images. The system is automatic, and its control, through a graphical user interface (GUI), saves costs and allows for the subsequent analysis of images using a digital image-processing algorithm. The results obtained allow for the possibility of planning in vivo measurements. In addition, the acquisition of images every 30° around the breast tissue could be used in future research in order to perform a three-dimensional (3D) reconstruction and an analysis of the captures through deep learning techniques. These could be combined with virtual, augmented, or mixed reality environments to predict the position of tumors, increase the likelihood of a correct medical diagnosis, and develop a training system for specialists. Furthermore, the system allows for the possibility to develop analysis of optical characterization for new phantom studies in breast cancer diagnosis through bioimaging techniques. Full article
(This article belongs to the Special Issue Advanced Biomedical Optics and Imaging)
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Graphical abstract

14 pages, 5033 KiB  
Article
Honeycomb Artifact Removal Using Convolutional Neural Network for Fiber Bundle Imaging
by Eunchan Kim, Seonghoon Kim, Myunghwan Choi, Taewon Seo and Sungwook Yang
Sensors 2023, 23(1), 333; https://doi.org/10.3390/s23010333 - 28 Dec 2022
Cited by 6 | Viewed by 2991
Abstract
We present a new deep learning framework for removing honeycomb artifacts yielded by optical path blocking of cladding layers in fiber bundle imaging. The proposed framework, HAR-CNN, provides an end-to-end mapping from a raw fiber bundle image to an artifact-free image via a [...] Read more.
We present a new deep learning framework for removing honeycomb artifacts yielded by optical path blocking of cladding layers in fiber bundle imaging. The proposed framework, HAR-CNN, provides an end-to-end mapping from a raw fiber bundle image to an artifact-free image via a convolution neural network (CNN). The synthesis of honeycomb patterns on ordinary images allows conveniently learning and validating the network without the enormous ground truth collection by extra hardware setups. As a result, HAR-CNN shows significant performance improvement in honeycomb pattern removal and also detailed preservation for the 1961 USAF chart sample, compared with other conventional methods. Finally, HAR-CNN is GPU-accelerated for real-time processing and enhanced image mosaicking performance. Full article
(This article belongs to the Special Issue Advanced Biomedical Optics and Imaging)
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17 pages, 5305 KiB  
Article
Acquisition and Analysis of Microcirculation Image in Septic Model Rats
by Chen Ye, Mami Kawasaki, Kazuya Nakano, Takashi Ohnishi, Eizo Watanabe, Shigeto Oda, Taka-Aki Nakada and Hideaki Haneishi
Sensors 2022, 22(21), 8471; https://doi.org/10.3390/s22218471 - 3 Nov 2022
Cited by 1 | Viewed by 2029
Abstract
Background: Microcirculation is a vital sign that supplies oxygen and nutrients to maintain normal life activities. Sepsis typically influences the operation of microcirculation, which is recovered by the administration of medicine injection. Objective: Sepsis-induced variation and recovery of microcirculation are quantitatively [...] Read more.
Background: Microcirculation is a vital sign that supplies oxygen and nutrients to maintain normal life activities. Sepsis typically influences the operation of microcirculation, which is recovered by the administration of medicine injection. Objective: Sepsis-induced variation and recovery of microcirculation are quantitatively detected using microcirculation images acquired by a non-contact imaging setup, which might assist the clinical diagnosis and therapy of sepsis. Methods: In this study, a non-contact imaging setup was first used to record images of microcirculation on the back of model rats. Specifically, the model rats were divided into three groups: (i) the sham group as a control group; (ii) the cecum ligation and puncture (CLP) group with sepsis; and (iii) the CLP+thrombomodulin (TM) group with sepsis and the application of TM alfa therapy. Furthermore, considering the sparsity of red blood cells (RBCs), the blood velocity is estimated by robust principal component analysis (RPCA) and U-net, and the blood vessel diameter is estimated by the contrast difference between the blood vessel and tissue. Results and Effectiveness: In the experiments, the continuous degradation of the estimated blood velocity and blood vessel diameter in the CLP group and the recovery after degradation of those in the CLP+TM group were quantitatively observed. The variation tendencies of the estimated blood velocity and blood vessel diameter in each group suggested the effects of sepsis and its corresponding therapy. Full article
(This article belongs to the Special Issue Advanced Biomedical Optics and Imaging)
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15 pages, 2056 KiB  
Article
Towards Development of Specular Reflection Vascular Imaging
by Timothy Burton, Gennadi Saiko and Alexandre Douplik
Sensors 2022, 22(8), 2830; https://doi.org/10.3390/s22082830 - 7 Apr 2022
Cited by 5 | Viewed by 2094
Abstract
Specular reflection from tissue is typically considered as undesirable, and managed through device design. However, we believe that specular reflection is an untapped light-tissue interaction, which can be used for imaging subcutaneous blood flow. To illustrate the concept of subcutaneous blood flow visualization [...] Read more.
Specular reflection from tissue is typically considered as undesirable, and managed through device design. However, we believe that specular reflection is an untapped light-tissue interaction, which can be used for imaging subcutaneous blood flow. To illustrate the concept of subcutaneous blood flow visualization using specular reflection from the skin, we have developed a ray tracing for the neck and identified conditions under which useful data can be collected. Based on our model, we have developed a prototype Specular Reflection Vascular Imaging (SRVI) device and demonstrated its feasibility by imaging major neck vessels in a case study. The system consists of a video camera that captures a video from a target area illuminated by a rectangular LED source. We extracted the SRVI signal from 5 × 5 pixels areas (local SRVI signal). The correlations of local SRVIs to the SRVI extracted from all pixels in the target area do not appear to be randomly distributed, but rather form cohesive sub-regions with distinct boundaries. The obtained waveforms were compared with the ECG signal. Based on the time delays with respect to the ECG signal, as well as the waveforms themselves, the sub-regions can be attributed to the jugular vein and carotid artery. The proposed method, SRVI, has the potential to contribute to extraction of the diagnostic information that the jugular venous pulse can provide. Full article
(This article belongs to the Special Issue Advanced Biomedical Optics and Imaging)
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