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Bioengineering
Special Issues
Multimodal Imaging Methodologies and Virtual/Augmented Reality for Biomedical Applications
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Multimodal Imaging Methodologies and Virtual/Augmented Reality for Biomedical Applications

A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biosignal Processing".

Deadline for manuscript submissions: closed (30 April 2025) | Viewed by 4835

Special Issue Editors

Dr. Vera Gramigna

E-Mail Website
Guest Editor
Department of Medical and Surgical Sciences, University of Catanzaro "Magna Graecia", 88100 Catanzaro, Italy
Interests: neuroimaging; biomedical engineering; rehabilitation; biomechanics; biomedical devices
Special Issues, Collections and Topics in MDPI journals
Dr. Arrigo Palumbo

E-Mail Website
Guest Editor
Department of Medical and Surgical Sciences, University of Catanzaro "Magna Graecia", 88100 Catanzaro, Italy
Interests: virtual, augmented, and extended reality technologies; biomedical engineering; rehabilitation; electronic devices for telemedicine applications; remote home monitoring systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Imaging methodologies play pivotal roles in clinical diagnosis and biomedical research.

The use of individual modalities (magnetic resonance imaging (MRI), computerized tomography (CT), positron emission tomography (PET), single-photon emission computed tomography (SPECT), functional near infrared spectroscopy (fNIRS), etc.) provides selective information on anatomical structure, pathophysiology, metabolism, structural connectivity, functional connectivity, etc.

Most recently, due to rapid advances in high-speed communication and computation, augmented reality/virtual reality (AR/VR) approaches are being used in conjunction with medical imaging with the potential to revolutionize how imaging information is applied in clinical practice.

This Special Issue focuses on the integration of different imaging modalities and the application of this multimodal imaging approach in the fields of biomedicine and healthcare.

Considering the huge application of this technology and its impact on clinical practice and public health, Bioengineering is launching this Special Issue to highlight the potential of multimodal imaging methods in detecting additional information that could be missed by considering each modality individually, enhancing the accuracy of diagnosis and therapeutical treatment of several pathologies.

Papers which focus on innovative approaches in biomedical applications using multimodal imaging methodologies are welcome to contribute to this Special Issue.

Dr. Vera Gramigna
Dr. Arrigo Palumbo
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. Bioengineering is an international peer-reviewed open access monthly 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 2700 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

  • multimodal imaging
  • magnetic resonance imaging (MRI)
  • computerized tomography (CT)
  • positron emission tomography (PET)
  • single-photon emission computed tomography (SPECT)
  • functional near infrared spectroscopy (fNIRS)
  • virtual, augmented, and mixed reality
  • biomedicine
  • human–robot interaction
  • technology in healthcare

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

Published Papers (3 papers)

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Research

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15 pages, 831 KiB  
Article
Analysis of the Relationship Between Scale Invariant Feature Transform Keypoint Properties and Their Invariance to Geometrical Transformation Applied to Cone-Beam Computed Tomography Images
by Diletta Pennati and Leonardo Bocchi
Bioengineering 2024, 11(12), 1236; https://doi.org/10.3390/bioengineering11121236 - 6 Dec 2024
Cited by 1 | Viewed by 912
Abstract
Image registration is a crucial post-processing technique in biomedical imaging, enabling the alignment and integration of images from various sources to facilitate accurate diagnosis, treatment planning, and longitudinal studies. This paper explores the application of Scale Invariant Feature Transform (SIFT), a robust feature-based [...] Read more.
Image registration is a crucial post-processing technique in biomedical imaging, enabling the alignment and integration of images from various sources to facilitate accurate diagnosis, treatment planning, and longitudinal studies. This paper explores the application of Scale Invariant Feature Transform (SIFT), a robust feature-based method for the alignment of biomedical images. SIFT is particularly advantageous due to its invariance to scale, rotation, and affine transformations, making it well-suited for handling the diverse and complex nature of biomedical images. However, SIFT was not initially developed specifically for medical imaging applications, so it is necessary to adapt the algorithm to those kinds of images. In particular, this work was focused on images obtained with Cone-Beam Computed Tomography (CBCT) technology. Besides fine-tuning SIFT parameters on a case-by-case basis, the novelty of this work consists of finding the optimal SIFT parameters on the basis of the keypoints stability. A statistical analysis throughout a dataset of images obtained with CBCT technology was performed to find the best SIFT parameters setting, in terms of computational cost and result quality, compared to default presets. Full article
(This article belongs to the Special Issue Multimodal Imaging Methodologies and Virtual/Augmented Reality for Biomedical Applications)
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Review

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15 pages, 2419 KiB  
Review
The Role of Imaging of Lymphatic System to Prevent Cancer Related Lymphedema
by Vincenzo Cuccurullo, Marco Rapa, Barbara Catalfamo, Gianluca Gatta, Graziella Di Grezia and Giuseppe Lucio Cascini
Bioengineering 2023, 10(12), 1407; https://doi.org/10.3390/bioengineering10121407 - 10 Dec 2023
Cited by 2 | Viewed by 2101
Abstract
Lymphedema is a progressive chronic condition affecting approximately 250 million people worldwide, a number that is currently underestimated. In Western countries, the most common form of lymphedema of the extremities is cancer-related and less radical surgical intervention is the main option to prevent [...] Read more.
Lymphedema is a progressive chronic condition affecting approximately 250 million people worldwide, a number that is currently underestimated. In Western countries, the most common form of lymphedema of the extremities is cancer-related and less radical surgical intervention is the main option to prevent it. Standardized protocols in the areas of diagnosis, staging and treatment are strongly required to address this issue. The aim of this study is to review the main diagnostic methods, comparing new emerging procedures to lymphoscintigraphy, considered as the golden standard to date. The roles of Magnetic Resonance Lymphangiography (MRL) or indocyanine green ICG lymphography are particularly reviewed in order to evaluate diagnostic accuracy, potential associations with lymphoscintigraphy, and future directions guided by AI protocols. The use of imaging to treat lymphedema has benefited from new techniques in the area of lymphatic vessels anatomy; these perspectives have become of value in many clinical scenarios to prevent cancer-related lymphedema. Full article
(This article belongs to the Special Issue Multimodal Imaging Methodologies and Virtual/Augmented Reality for Biomedical Applications)
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Other

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19 pages, 1827 KiB  
Systematic Review
Advancing Gait Analysis: Integrating Multimodal Neuroimaging and Extended Reality Technologies
by Vera Gramigna, Arrigo Palumbo and Giovanni Perri
Bioengineering 2025, 12(3), 313; https://doi.org/10.3390/bioengineering12030313 - 19 Mar 2025
Viewed by 767
Abstract
The analysis of human gait is a cornerstone in diagnosing and monitoring a variety of neuromuscular and orthopedic conditions. Recent technological advancements have paved the way for innovative methodologies that combine multimodal neuroimaging and eXtended Reality (XR) technologies to enhance the precision and [...] Read more.
The analysis of human gait is a cornerstone in diagnosing and monitoring a variety of neuromuscular and orthopedic conditions. Recent technological advancements have paved the way for innovative methodologies that combine multimodal neuroimaging and eXtended Reality (XR) technologies to enhance the precision and applicability of gait analysis. This review explores the state-of-the-art solutions of an advanced gait analysis approach, a multidisciplinary concept that integrates neuroimaging, extended reality technologies, and sensor-based methods to study human locomotion. Several wearable neuroimaging modalities such as functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG), commonly used to monitor and analyze brain activity during walking and to explore the neural mechanisms underlying motor control, balance, and gait adaptation, were considered. XR technologies, including virtual, augmented, and mixed reality, enable the creation of immersive environments for gait analysis, real-time simulation, and movement visualization, facilitating a comprehensive assessment of locomotion and its neural and biomechanical dynamics. This advanced gait analysis approach enhances the understanding of gait by examining both cerebral and biomechanical aspects, offering insights into brain–musculoskeletal coordination. We highlight its potential to provide real-time, high-resolution data and immersive visualization, facilitating improved clinical decision-making and rehabilitation strategies. Additionally, we address the challenges of integrating these technologies, such as data fusion, computational demands, and scalability. The review concludes by proposing future research directions that leverage artificial intelligence to further optimize multimodal imaging and XR applications in gait analysis, ultimately driving their translation from laboratory settings to clinical practice. This synthesis underscores the transformative potential of these approaches for personalized medicine and patient outcomes. Full article
(This article belongs to the Special Issue Multimodal Imaging Methodologies and Virtual/Augmented Reality for Biomedical Applications)
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