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Imaging in Biomedical Sensing

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

Deadline for manuscript submissions: closed (31 October 2022) | Viewed by 9927

Special Issue Editors


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Guest Editor
UAV Research Centre, Ghent University, 9000 Ghent, Belgium
Interests: artificial intelligence; hyperspectral imaging; LiDAR; data fusion; UAS
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Telecommunications and information processing, Universiteit Gent, Ghent, Belgium
Department of Physics and astronomy processing, Universiteit Gent, Ghent, Belgium
Interests: image reconstruction; inverse problems; image and video analysis; machine learning

Special Issue Information

Dear Colleagues,

Thanks to the rapidly increasing capability of imaging and processing technology, the life sciences applications have become more and more reliant on intelligent image/video processing and image/video analysis techniques. The goal of this Special Issue is to present high-impact issues in image and video processing related, but not limited to, the light-based imaging and microscopy, CT, electron microscopy, MRI, ultrasound, and PET/SPECT fields.

A common challenge in these fields is the need to process ever increasing amounts of data to answer specific research questions. Associated areas are the algorithmic development of novel sensing technology and the use of intricate image and video analysis/evaluation methods for specific use cases. These trends have resulted in a recent surge in publications in the following fields:

  • Image and video analysis for life sciences;
  • Image and video quality assessment;
  • Application of deep learning in biomedicine and bioinformatics;
  • Inverse problems and image reconstruction;
  • Image Representation learning;
  • High-throughput image and video processing/analysis;
  • Hybrid neural networks;
  • Sensor fusion;
  • Computational imaging

We aim to publish the most recent advances in the highly active research fields of sensing, data fusion, and machine learning in biomedical imaging. Contributions from both theoretical and specific application domains are welcome, and we will also accept tutorial and survey/overview manuscripts.

Dr. Hiep Luong
Prof. Jan Aelterman
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.

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Published Papers (2 papers)

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Research

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18 pages, 4976 KiB  
Article
The Influence of Filters on EEG-ERP Testing: Analysis of Motor Cortex in Healthy Subjects
by Ilona Karpiel, Zofia Kurasz, Rafał Kurasz and Klaudia Duch
Sensors 2021, 21(22), 7711; https://doi.org/10.3390/s21227711 - 19 Nov 2021
Cited by 5 | Viewed by 2937
Abstract
The raw EEG signal is always contaminated with many different artifacts, such as muscle movements (electromyographic artifacts), eye blinking (electrooculographic artifacts) or power line disturbances. All artifacts must be removed for correct data interpretation. However, various noise reduction methods significantly influence the final [...] Read more.
The raw EEG signal is always contaminated with many different artifacts, such as muscle movements (electromyographic artifacts), eye blinking (electrooculographic artifacts) or power line disturbances. All artifacts must be removed for correct data interpretation. However, various noise reduction methods significantly influence the final shape of the EEG signal and thus its characteristic values, latency and amplitude. There are several types of filters to eliminate noise early in the processing of EEG data. However, there is no gold standard for their use. This article aims to verify and compare the influence of four various filters (FIR, IIR, FFT, NOTCH) on the latency and amplitude of the EEG signal. By presenting a comparison of selected filters, the authors intend to raise awareness among researchers as regards the effects of known filters on latency and amplitude in a selected area—the sensorimotor area. Full article
(This article belongs to the Special Issue Imaging in Biomedical Sensing)
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Review

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19 pages, 954 KiB  
Review
A Survey of Methods and Technologies Used for Diagnosis of Scoliosis
by Ilona Karpiel, Adam Ziębiński, Marek Kluszczyński and Daniel Feige
Sensors 2021, 21(24), 8410; https://doi.org/10.3390/s21248410 - 16 Dec 2021
Cited by 16 | Viewed by 6261
Abstract
The purpose of this article is to present diagnostic methods used in the diagnosis of scoliosis in the form of a brief review. This article aims to point out the advantages of select methods. This article focuses on general issues without elaborating on [...] Read more.
The purpose of this article is to present diagnostic methods used in the diagnosis of scoliosis in the form of a brief review. This article aims to point out the advantages of select methods. This article focuses on general issues without elaborating on problems strictly related to physiotherapy and treatment methods, which may be the subject of further discussions. By outlining and categorizing each method, we summarize relevant publications that may not only help introduce other researchers to the field but also be a valuable source for studying existing methods, developing new ones or choosing evaluation strategies. Full article
(This article belongs to the Special Issue Imaging in Biomedical Sensing)
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