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Advanced Optoelectronic Sensors and Biomedical Application

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

Deadline for manuscript submissions: closed (25 July 2021) | Viewed by 5754

Special Issue Editors


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Guest Editor
1. Biomedical Engineering (BME) Institute, Chinese Academy of Medical Sciences and Peking Union Medical College, Baidi Road, Tianjin 300192, China
2. Electronics Science Technology College, University of Electronic Science and Technology of China, Chengdu 610051, China
Interests: optoelectronic sensors and sensing system; medical optoelectronics; device and instrumentation; optical imaging
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Physics, University of Paderborn, Paderborn, Germany
Interests: nanoscience; material growth; device fabrication; photonics; electronics
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Biomedical Engineering, College of Engineering, University of Kentucky, Lexington, KY 40506, USA
Interests: biomedical optics; optical sensor; diffuse optics; optical imaging; tomography; finite element method; Monte Carlo method

Special Issue Information

Dear Colleagues,

Due to the huge impact of the COVID-19 epidemic, people are paying tremendous attention to health and biomedicine. Optoelectronic technologies are playing an important role in monitoring, detection and diagnosis of COVID-19, convalescence, and healthcare for the aging population, for which is critical to have advanced optoelectronic sensors with high performance. Innovative optoelectronic sensors for health care, medicine, and wellbeing have thus attracted a great deal of attention in many fields, such as materials and optoelectronic sensors, biomedical engineering, biomedical optics, instrumentation, intelligence hardware, optoelectronics, computer science, medical robots, hospital managements, and healthy building. Innovative optoelectronic sensors, sensing technologies, and sensing system, which are compatible or implantable for convalescence instruments or medical robots, are facing increasing demand for dysfunctional and aging people, patients, healthcare workers, and medical staff. From simple biophotoic sensors in healthcare to intelligent medical robots, fast and timely probing of health dangers such as virus and bacterial, accurate detection, and early warning of health or disease conditions for people, interacting with different living scenarios and environments, represent demanding requirements.

The aim of this Special Issue is to collect up-to-date advances on optoelectronic sensors and sensing systems for healthcare, clinics, biological safety, healthy building, and environment. High-quality research articles, short communications, as well as reviews, are welcome. Of special interest are research works that seek to address recent developments in small-size, wearable, high-sensitivity, and fast optoelectronic sensors or sensing systems targeting biomedicine, their fusion into COVID-19, monitoring, diagnosis, medical robots, brain–computer interfaces, sensing technology and algorithms, sensing mathematics and calibration, reliability testing, novel strategies in handling issues in on-human applications, state-of-the-art applications, innovative data analysis technologies on sensed data in the biomedicine framework, as well as relevant prospects in terms of opportunities and challenges.

Submissions are welcomed in, but not limited to, the following and/or related topics:

  • New materials of optoelectronic sensors;
  • Novel technologies changing materials to advanced optoelectronic sensors;
  • Novel sesning technologies for the COVID-19 epidemic, health, and clinics;
  • Printed, flexible, biodegradable, and biocompatible optoelectronics;
  • Sensor devices;
  • Novel optoelectronics for brain activity monitoring and brain–computer interfaces;
  • Sensors and systems for aging and hysical rehabilitation;
  • Wearable and implantable optoelectronic sensors;
  • Optoelectronic sensors and optoelectronics fot healthy building and enviorment;
  • Application of optoelectronic sensors in health/medical devices and robots;
  • Reliability testing and calibration of the above sensors and systems;
  • Algorithm and mathmatics in applications in sensing and beyond;
  • Issues and strategies in on-human applications of the above sensors;
  • Innovative data analysis technologies in the above scope.

Prof. Dr. Ting Li
Dr. Yunyan Zhang
Dr. Chong Huang
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

  • optoelectronic sensors
  • biomedicine
  • sensing system

Published Papers (2 papers)

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Research

14 pages, 6074 KiB  
Article
An Unsupervised Learning-Based Multi-Organ Registration Method for 3D Abdominal CT Images
by Shaodi Yang, Yuqian Zhao, Miao Liao and Fan Zhang
Sensors 2021, 21(18), 6254; https://doi.org/10.3390/s21186254 - 18 Sep 2021
Cited by 1 | Viewed by 2146
Abstract
Medical image registration is an essential technique to achieve spatial consistency geometric positions of different medical images obtained from single- or multi-sensor, such as computed tomography (CT), magnetic resonance (MR), and ultrasound (US) images. In this paper, an improved unsupervised learning-based framework is [...] Read more.
Medical image registration is an essential technique to achieve spatial consistency geometric positions of different medical images obtained from single- or multi-sensor, such as computed tomography (CT), magnetic resonance (MR), and ultrasound (US) images. In this paper, an improved unsupervised learning-based framework is proposed for multi-organ registration on 3D abdominal CT images. First, the explored coarse-to-fine recursive cascaded network (RCN) modules are embedded into a basic U-net framework to achieve more accurate multi-organ registration results from 3D abdominal CT images. Then, a topology-preserving loss is added in the total loss function to avoid a distortion of the predicted transformation field. Four public databases are selected to validate the registration performances of the proposed method. The experimental results show that the proposed method is superior to some existing traditional and deep learning-based methods and is promising to meet the real-time and high-precision clinical registration requirements of 3D abdominal CT images. Full article
(This article belongs to the Special Issue Advanced Optoelectronic Sensors and Biomedical Application)
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12 pages, 22725 KiB  
Communication
Effect of Spectral Signal-to-Noise Ratio on Resolution Enhancement at Surface Plasmon Resonance
by Long Ma, Guo Xia, Shiqun Jin, Lihao Bai, Jiangtao Wang, Qiaoqin Chen and Xiaobo Cai
Sensors 2021, 21(2), 641; https://doi.org/10.3390/s21020641 - 18 Jan 2021
Cited by 3 | Viewed by 2709
Abstract
Refractive index resolution is an important indicator for a wavelength interrogation surface plasmon resonance sensor, which can be affected by signal-to-noise ratio. This paper investigates the impact of spectral signal-to-noise ratio on a surface plasmon resonance sensor. The effects of different spectral powers [...] Read more.
Refractive index resolution is an important indicator for a wavelength interrogation surface plasmon resonance sensor, which can be affected by signal-to-noise ratio. This paper investigates the impact of spectral signal-to-noise ratio on a surface plasmon resonance sensor. The effects of different spectral powers and noises are compared and verified through simulation and experiments. The results indicate that the optimal resonance wavelength is changed and the refractive index resolution can even be nearly twice as good when the spectral signal-to-noise ratio is increased. The optimal resonance wavelength can be found by changing the spectral power distribution or noise. Full article
(This article belongs to the Special Issue Advanced Optoelectronic Sensors and Biomedical Application)
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