Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
6.8
3.9
Journals
Sensors
Special Issues
Sensors for Biomedical Imaging 2023
sensors-logo
Submit to Sensors Review for Sensors Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Sensors for Biomedical Imaging 2023

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

Deadline for manuscript submissions: closed (20 September 2023) | Viewed by 1861

Special Issue Editors

Prof. Dr. Arcangelo Merla

E-Mail Website
Guest Editor
Department of Engineering and Geology, University of G. d'Annunzio Chieti and Pescara, 65127 Pescara, Italy
Interests: infrared imaging; medical imaging; neuroimaging; psychophysiology; human–machine interaction
Special Issues, Collections and Topics in MDPI journals
Dr. Antonio Maria Chiarelli

E-Mail Website
Guest Editor
Infrared Imaging Lab, ITAB Institute for Advanced Biomedical Technologies, Department of Neuroscience, Imaging and Clinical Sciences, University of Chieti-Pescara, 66100 Chieti, Italy
Interests: infrared imaging; diffuse optical imaging; neuroimaging; Bayesian statistics; machine learning
Special Issues, Collections and Topics in MDPI journals
Dr. Daniela Cardone

E-Mail Website
Guest Editor
Department of Engineering and Geology, University of G. d'Annunzio Chieti and Pescara, 65127 Pescara, Italy
Interests: artificial intelligence methods; robotics and affective computing; human–machine interaction; processing methods and analysis of biomedical images and physiological signals; computer vision
Special Issues, Collections and Topics in MDPI journals
Dr. David Perpetuini

E-Mail Website
Guest Editor
Department of Engineering and Geology, University of G. d'Annunzio Chieti and Pescara, 65127 Pescara, Italy
Interests: infrared thermography; functional infrared spectroscopy (fNIRS); electroencephalography (EEG); photoplethysmography (PPG); wearable sensors; affective computing; machine learning; artificial intelligence
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Biomedical research advancement is strictly interconnected with the development of novel sensor technology. This Special Issue aims to highlight recent advances in sensor development and to provide an opportunity for knowledge sharing between sensors experts and scientists that use sensor technology for biomedical applications. Hardware advances have provided the opportunity to utilize health-monitoring technologies in heterogeneous environments, ranging from clinical settings to home monitoring. Novel algorithmic approaches (e.g., machine learning), recent growth in computational power, and multimodal integration have enabled new analysis techniques to further exploit biomedical technology. Different innovative detectors and applications that rely on such sensors, with emphasis on wireless or portable technology, are suitable topics, but other relevant subjects are also welcome. Original papers that describe new biomedical research or innovative applications and sensors are welcome. We look forward to your participation in this Special Issue.

Prof. Dr. Arcangelo Merla
Dr. Antonio Maria Chiarelli
Dr. Daniela Cardone
Dr. David Perpetuini
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

  • biomedical sensors
  • detectors
  • medical imaging
  • multimodal monitoring
  • portable technology
  • machine learning
  • data-driven analysis
  • image processing

Published Papers (1 paper)

Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

11 pages, 1427 KiB  
Article
Investigation of the Relationship between Body Parameters and mAs Using Non-Contact Two-Dimensional Thickness Measurement in Chest Digital Radiography
by Jia-Ru Lin, I-Hao Cheng, Yu-Syuan Liang, Jyun-Jie Li, Jen-Ming Tsai, Min-Tsung Wang, Te-Pao Lin, Su-Lan Huang and Ming-Chung Chou
Sensors 2023, 23(16), 7169; https://doi.org/10.3390/s23167169 - 14 Aug 2023
Viewed by 1169
Abstract
The current study aimed to investigate the relationship between body parameters and the current–time product (mAs) in chest digital radiography using a non-contact infrared thickness-measurement sensor. An anthropomorphic chest phantom was first used to understand variations in mAs over multiple positionings during chest [...] Read more.
The current study aimed to investigate the relationship between body parameters and the current–time product (mAs) in chest digital radiography using a non-contact infrared thickness-measurement sensor. An anthropomorphic chest phantom was first used to understand variations in mAs over multiple positionings during chest radiography when using the automatic exposure control (AEC) technique. In a human study, 929 consecutive male subjects who underwent regular chest examinations were enrolled, and their height (H), weight (W), and body mass index (BMI) were recorded. In addition, their chest thickness (T) was measured at exhalation using a non-contact infrared sensor, and chest radiography was then performed using the AEC technique. Finally, the relationship between four body parameters (T, BMI, T*BMI, and W/H) and mAs was investigated by fitting the body parameters to mAs using three curve models. The phantom study showed that the maximum mAs was 1.76 times higher than the lowest mAs during multiple positionings in chest radiography. In the human study, all chest radiographs passed the routine quality control procedure and had an exposure index between 100 and 212. In curve fitting, the comparisons showed that W/H had a closer relationship with mAs than the other body parameters, while the first-order power model with W/H fitted to mAs performed the best and had an R-square of 0.9971. We concluded that the relationship between W/H and mAs in the first-order power model may be helpful in predicting the optimal mAs and reducing the radiation dose for chest radiography when using the AEC technique. Full article
(This article belongs to the Special Issue Sensors for Biomedical Imaging 2023)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-1
Back to TopTop