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Applied Sciences
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Application of Image Processing in Medicine
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Application of Image Processing in Medicine

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Acoustics and Vibrations".

Deadline for manuscript submissions: closed (18 March 2022) | Viewed by 11430

Special Issue Editors

Prof. Dr. Robert Koprowski

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Guest Editor
Institute of Biomedical Engineering, University of Silesia, 41-200 Sosnowiec, Poland
Interests: sport; audio systems; mountains
Prof. Dr. Sławomir Wilczyński

E-Mail Website
Guest Editor
Department of Basic Biomedical Science, Faculty of Pharmaceutical Sciences in Sosnowiec, Medical University of Silesia, Kasztanowa 3, 41-200 Sosnowiec, Poland
Interests: pharmacy; topical drug delivery; image analysis and processing; thermography; hyperspectral imaging; biomedical engineering; bioengineering
Special Issues, Collections and Topics in MDPI journals
Dr. Michele Lanza

E-Mail Website
Guest Editor
Multidisciplinary Department of Medical, Surgical and Dental Sciences, University of Campania Luigi Vanvitelli, 80131 Naples, Italy
Interests: glaucoma; cornea; cataract; refractive surgery; IOL calculation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

I am pleased to present a new Special Issue on the ‘’Application of Image Processing in Medicine’’. The application of image processing is increasingly being used in various fields of life. One such area is medicine. Modern medical imaging provides an increasing number of features derived from different types of analysis, including artificial intelligence and algorithms. In recent years, this area has been the subject of many research papers and research grants. Consequently, this Special Issue is devoted to the subject of application, in its broadest sense, of biomedical engineering, with a particular emphasis on medical imaging. Therefore, I invite authors who deal with new and modified algorithm methods, evolutionary calculations, and their new applications in biomedical imaging. I hope that this Special Issue will supplement readers’ knowledge of new artificial intelligence methods and their applications in new areas of medical imaging.

Prof. Dr. Robert Koprowski
Prof. Sławomir Wilczyński
Dr. Michele Lanza
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. Applied Sciences 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 2400 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

  • Image processing: fully automatic segmentation
  • active contour
  • stereovision
  • binarization
  • filtering
  • morphological operations Medicine: thermal imaging
  • tomography
  • eye
  • posture
  • scoliosis
  • newborns
  • thermal comfort
  • DNA
  • X-ray
  • MRI
  • angiography
  • microtubules

Published Papers (6 papers)

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Editorial

Jump to: Research

2 pages, 158 KiB  
Editorial
Special Issue on Application of Image Processing in Medicine
by Robert Koprowski, Sławomir Wilczyński and Michele Lanza
Appl. Sci. 2023, 13(1), 337; https://doi.org/10.3390/app13010337 - 27 Dec 2022
Viewed by 708
Abstract
The title and theme of this Special Issue “Application of Image Processing in Medicine” is currently very popular, topical, and important [...] Full article
(This article belongs to the Special Issue Application of Image Processing in Medicine)

Research

Jump to: Editorial

17 pages, 3185 KiB  
Article
A Novel Machine Learning Approach for Tuberculosis Segmentation and Prediction Using Chest-X-Ray (CXR) Images
by Xavier Alphonse Inbaraj, Charlyn Villavicencio, Julio Jerison Macrohon, Jyh-Horng Jeng and Jer-Guang Hsieh
Appl. Sci. 2021, 11(19), 9057; https://doi.org/10.3390/app11199057 - 28 Sep 2021
Cited by 5 | Viewed by 1713
Abstract
Tuberculosis is a potential fatal disease with high morbidity and mortality rates. Tuberculosis death rates are rising, posing a serious health threat in several poor countries around the world. To address this issue, we proposed a novel method for detecting tuberculosis in chest [...] Read more.
Tuberculosis is a potential fatal disease with high morbidity and mortality rates. Tuberculosis death rates are rising, posing a serious health threat in several poor countries around the world. To address this issue, we proposed a novel method for detecting tuberculosis in chest X-ray (CXR) images that uses a three-phased approach to distinguish tuberculosis such as segmentation, feature extraction, and classification. In a CXR, we utilized the Weiner filter to distinguish and reduce the impulse noise. The features were extracted from CXR images and trained using a decision tree classifier known as the stacked loopy decision tree (SLDT) classifier. For the classification process, the ROI-based morphological approach was applied in the mentioned three-phased approach, and the feature extraction was accomplished through chromatic and Prewitt-edge highlights. Full article
(This article belongs to the Special Issue Application of Image Processing in Medicine)
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12 pages, 33768 KiB  
Article
Detection of Respiratory Phases in a Breath Sound and Their Subsequent Utilization in a Diagnosis
by David Skalicky, Vaclav Koucky, Daniel Hadraba, Martin Viteznik, Martin Dub and Frantisek Lopot
Appl. Sci. 2021, 11(14), 6535; https://doi.org/10.3390/app11146535 - 16 Jul 2021
Cited by 6 | Viewed by 2876
Abstract
Detection of lung sounds and their propagation is a powerful tool for analysing the behaviour of the respiratory system. A common approach to detect the respiratory sounds is lung auscultation, however, this method has significant limitations including low sensitivity of human ear or [...] Read more.
Detection of lung sounds and their propagation is a powerful tool for analysing the behaviour of the respiratory system. A common approach to detect the respiratory sounds is lung auscultation, however, this method has significant limitations including low sensitivity of human ear or ambient background noise. This article targets the major limitations of lung auscultation and presents a new approach to analyse the respiratory sounds and visualise them together with the respiratory phases. The respiratory sounds from 41 patients were recorded and filtered to eliminate the ambient noise and noise artefacts. The filtered signal is processed to identify the respiratory phases. The article also contains an approach for removing the noise that is very difficult to filter but the removal is crucial for identifying the respiratory phases. Finally, the respiratory phases are overlaid with the frequency spectrum which simplifies the orientation in the recording and additionally offers the information on the inter-individual ratio of the inhalation and exhalation phases. Such interpretation provides a powerful tool for further analysis of lung sounds, simplifythe diagnosis of various types of respiratory tract dysfunctions, and returns data which are comparable among the patients. Full article
(This article belongs to the Special Issue Application of Image Processing in Medicine)
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16 pages, 3966 KiB  
Article
Automatic Mobile Warning System against People with Elevated Body Temperature
by Mariusz Marzec and Sławomir Wilczyński
Appl. Sci. 2021, 11(11), 4721; https://doi.org/10.3390/app11114721 - 21 May 2021
Cited by 2 | Viewed by 1605
Abstract
The paper proposes a system that allows for the automatic detection of people with elevated body temperature and estimates distance from them using a smartphone-type device and a single mobile thermal camera. The algorithm automatically finds and selects humans with the highest temperature, [...] Read more.
The paper proposes a system that allows for the automatic detection of people with elevated body temperature and estimates distance from them using a smartphone-type device and a single mobile thermal camera. The algorithm automatically finds and selects humans with the highest temperature, and tracks changes in their position in an image sequence. On the basis of the change in the position of the human head in the image, in subsequent frames, the algorithm estimates the distance between camera and human. Owing to the use of fast machine-learning methods, the proposed system can immediately alert the user about the presence of a people with an elevated temperature at a distance of 1–3 m as soon as it appears in the field of view of the camera. The effectiveness of the algorithm was assessed as the ratio of correct distance classifications in the test image set to the total number of test images. Values ranging from 73% to 100% were obtained for over 4000 images of humans at different distances. The proposed method allows for the quick and completely automatic warning aboutt people with elevated temperature, and can be used in popular Android mobile devices. Full article
(This article belongs to the Special Issue Application of Image Processing in Medicine)
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10 pages, 1346 KiB  
Article
Mapping of Nanomechanical Properties of Enamel Surfaces Due to Orthodontic Treatment by AFM Method
by Monika Machoy, Sławomir Wilczyński, Liliana Szyszka-Sommerfeld, Krzysztof Woźniak, Anna Deda and Sławomir Kulesza
Appl. Sci. 2021, 11(9), 3918; https://doi.org/10.3390/app11093918 - 26 Apr 2021
Cited by 7 | Viewed by 2043
Abstract
Background: Atomic force microscopy imaging was used to study the structural topography of enamel crystals in healthy and affected enamel. The correlation of topographic images with nanomechanical properties allows for the assessment of morphology and properties at the micro- and nano-meter level in [...] Read more.
Background: Atomic force microscopy imaging was used to study the structural topography of enamel crystals in healthy and affected enamel. The correlation of topographic images with nanomechanical properties allows for the assessment of morphology and properties at the micro- and nano-meter level in three dimensions simultaneously. Methods: A total of 60 premolars were treated like teeth during orthodontic bonding and debonding procedures. Every stage was observed in AFM. Surface roughness, image surface area difference, mean Young’s modulus, and mean adhesion force (the force of attraction between the scanning blade and the surface averaged over the image) were determined for the following areas: the central part of the surface, responsible for load transmission; the top of the surface, subject to the most abrasive wear; the lower part of the surface, responsible for the transport of fluids. Results: The highest roughness occurred on the etched surface—average 63 nm, followed by the intact enamel—8.3 nm, cleaned enamel—7.0 nm, and the resin-coated surface—5.4 nm. Conclusion: Etching increases enamel roughness and reduces hardness. Resin reduces roughness of the etched surface and increases hardness. The intact enamel has the highest hardness. The enamel smoothness is greater after polishing than in the intact enamel. Full article
(This article belongs to the Special Issue Application of Image Processing in Medicine)
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13 pages, 2607 KiB  
Article
Impact of the Enamel Cleaning Procedure during Debonding on Endodontium Temperature: In Vitro Tests
by Monika Machoy, Liliana Szyszka-Sommerfeld, Piotr Duda, Anna Wawrzyk, Krzysztof Woźniak and Sławomir Wilczyński
Appl. Sci. 2020, 10(23), 8672; https://doi.org/10.3390/app10238672 - 04 Dec 2020
Cited by 2 | Viewed by 1510
Abstract
Interference with live tooth tissue during dental treatment affects the temperature within the pulp. The pulp is sensitive to temperature changes, which can cause its inflammation. The aim of this study was to analyze the dynamics of pulp chamber temperature changes in response [...] Read more.
Interference with live tooth tissue during dental treatment affects the temperature within the pulp. The pulp is sensitive to temperature changes, which can cause its inflammation. The aim of this study was to analyze the dynamics of pulp chamber temperature changes in response to the enamel cleaning procedure after orthodontic treatment. In the presented in vitro studies, by using a thermal imaging camera, the change in the temperature of the vestibular wall of the pulp chamber of the incisors and premolars was assessed as a function of time under the influence of polishing the enamel with the silicone rubber and aluminum oxides used during the debonding procedure after completion of orthodontic treatment with fixed appliances. The relationship between dentin density and enamel from changing the chamber temperature was evaluated by using Micro computed tomography, microtomography (micro-CT). The maximum achieved tooth surface temperature during polishing was 52.34 °C without water cooling and 43.15 °C using water cooling. The time after which a safe pulp temperature of 40 °C was obtained without water cooling was 29.4 s, while the time with water cooling was 34.6 s. The correlation between the maximum and average temperature achieved and the density of the teeth was analyzed based on micro-CT scans. No correlation between enamel or dentin density and rise in temperature was found. Full article
(This article belongs to the Special Issue Application of Image Processing in Medicine)
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