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Advances and Applications of 3D Imaging in Medicine

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Biomedical Engineering".

Deadline for manuscript submissions: 20 October 2026 | Viewed by 382

Editor


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Guest Editor
Department of Anatomy and Embryology, Faculty of Health and Life Sciences, Maastricht University, Maastricht, The Netherlands
Interests: implementing 3D imaging/VR into education; implementing 3D imaging/VR into students’ self study

Special Issue Information

Dear Colleagues,

In recent years, three-dimensional (3D) imaging, together with virtual and augmented reality technologies, has become an increasingly important component of medical education, as well as clinical diagnosis and treatment. Three-dimensional imaging has emerged as a fundamental tool in modern medical diagnostics and treatment planning. It reconstructs volumetric representations of anatomical structures from multiple cross-sectional datasets, enabling detailed visualization of spatial relationships within the human body. This approach enhances the ability of clinicians and researchers to analyze complex anatomical and pathological features.

Compared with conventional two-dimensional imaging, 3D visualization is more intuitive because human perception is naturally adapted to stereoscopic spatial information. Consequently, 3D imaging provides substantial benefits for medical education by helping to bridge the gap between traditional anatomical training and clinical imaging. Digital 3D models derived from realistic specimens allow students to study anatomical structures in detail and to access learning materials, independent of time and location. Furthermore, immersive environments created with virtual reality enable participants to interact within shared virtual spaces, facilitating collaborative learning without the need for their physical presence in specialized facilities.

Several imaging modalities contribute to 3D medical visualization, including Computed Tomography, Magnetic Resonance Imaging, and 3D Ultrasound. These techniques acquire sequential image slices that can be computationally reconstructed by using algorithms such as volume rendering, surface rendering, and multiplanar reconstruction. The resulting volumetric datasets enable improved assessment of anatomical morphology, disease progression, and treatment outcomes, while also supporting educational applications. In addition, photorealistic scanning techniques, combined with virtual reconstruction methods and artificial intelligence-assisted processing, allow for the generation of highly detailed digital anatomical models.

In clinical practice and biomedical research, 3D imaging plays a crucial role in areas such as surgical planning, image-guided interventions, and the quantitative analysis of tissues and organs. By providing high-resolution spatial information, 3D imaging technologies contribute significantly to more accurate diagnoses and support the development of personalized therapeutic strategies.

The Special Issue “Advances and Applications of 3D Imaging in Medicine” welcomes submissions presenting recent research in this rapidly evolving and promising field. The scope includes a broad range of topics addressing the latest applications of 3D imaging in medical diagnosis and treatment, as well as patient-centred applications and medical education, including extended reality technologies such as AR/VR and virtual classrooms.

Recommended topics include, but are not limited to, the following:

  • Photorealistic anatomical specimens in education.
  • Generated 3D models for educational purposes.
  • 3D real-time recording of surgery for education and remote coaching.
  • 3D virtual classrooms.
  • Holographic models in medical training.
  • VR in patient education.
  • VR applications in geriatrics.
  • VR as part of surgery (patient side).
  • 3D VR in surgical planning and intraoperative support (doctor’s side).
  • 3D imaging in radiology and diagnosis.
  • 3D printing for education and surgical preparation.
  • 3D imaging for printing implants in dentistry and for surgical applications.
  • Applications of AI in 3D medical image processing.
  • AI-driven medical imaging for disease diagnosis and prognosis assessment.
  • ……

Dr. Andreas Herrler
Guest Editor

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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized 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

  • VR/AR/XR
  • education
  • diagnosis
  • treatment
  • visualization
  • 3D printing
  • radiology
  • photorealistic
  • generated models
  • AI

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Published Papers (2 papers)

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17 pages, 1069 KB  
Article
Development and Evaluation of a 360-Degree Video on Home Care in Undergraduate Health Sciences Education
by Nynke de Jong, Dalena van Heugten-van der Kloet, Sil Aarts and Stefan Jongen
Appl. Sci. 2026, 16(13), 6446; https://doi.org/10.3390/app16136446 (registering DOI) - 29 Jun 2026
Abstract
Access to authentic clinical learning experiences is often limited for undergraduate Health Sciences students. Immersive technologies such as 360-degree video may help bridge this gap, yet evidence regarding their use in home care education and Problem-Based Learning (PBL) remains scarce. To address this [...] Read more.
Access to authentic clinical learning experiences is often limited for undergraduate Health Sciences students. Immersive technologies such as 360-degree video may help bridge this gap, yet evidence regarding their use in home care education and Problem-Based Learning (PBL) remains scarce. To address this gap, we used a Design-Based Research (DBR) approach to develop and implement a 360-degree video-based home care learning experience and evaluated students’ perceptions of the video, VR headsets, and associated educational formats across three curricular tracks. The experiences of 251 undergraduate Health Sciences students across three different tracks (Policy, Mental Health and Digital) at Maastricht University were studied. Each track offered a different educational format using the 360-degree video as part of its Problem-Based Learning (PBL) curriculum. Students responded once to a combination of self-developed and standardized questionnaires, which included subscales from the Technology Acceptance Model 3 (TAM3) and the Video Transportation Scale (VTS). A DBR approach facilitated the iterative development and implementation of a 360-degree video-based home care learning experience embedded within a Problem-Based Learning curriculum. The intervention was successfully integrated across three tracks without compromising key PBL principles. Students generally perceived the 360-degree video and associated educational formats positively, particularly appreciating the opportunities for interaction and contextualized learning. The findings suggest that immersive 360-degree video delivered through VR headsets is a feasible and acceptable educational approach for undergraduate Health Sciences students and may provide meaningful exposure to clinical practice when access to placements is limited. Full article
(This article belongs to the Special Issue Advances and Applications of 3D Imaging in Medicine)
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12 pages, 1423 KB  
Systematic Review
Predictability of Mandibular Autorotation After Maxillary Repositioning in Orthognathic Surgery: A Systematic Review with Exploratory Quantitative Synthesis
by Andrii Hresko, Veronica Scocca, Josefina Santana and Gwen R. J. Swennen
Appl. Sci. 2026, 16(12), 5875; https://doi.org/10.3390/app16125875 - 10 Jun 2026
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Abstract
This systematic review aimed to evaluate the available evidence on methods used to predict mandibular autorotation after maxillary repositioning in orthognathic surgery. A systematic search of PubMed/MEDLINE, Cochrane Library, Scopus, Google Scholar, and EMBASE covering the period from 1970 to 2026 was performed [...] Read more.
This systematic review aimed to evaluate the available evidence on methods used to predict mandibular autorotation after maxillary repositioning in orthognathic surgery. A systematic search of PubMed/MEDLINE, Cochrane Library, Scopus, Google Scholar, and EMBASE covering the period from 1970 to 2026 was performed to identify studies reporting on prediction methods for mandibular autorotation after maxillary repositioning. Data on study design, sample size, surgical setting, prediction method, and prediction error were extracted. Because of substantial heterogeneity and incomplete reporting, quantitative synthesis was considered exploratory. Risk of bias was assessed using the ROBINS-I tool. A total of six studies met the inclusion criteria. The available evidence showed marked heterogeneity in study design, outcome definitions, anatomical landmarks, and reporting format. Earlier studies mainly used 2D cephalometric or geometric methods, whereas more recent investigations relied on 3D virtual planning and simulation-based workflows. In the exploratory subgroup meta-analysis, 3D approaches were associated with a lower pooled mean prediction error (0.57 mm, 95% CI: 0.05–1.08) than 2D methods (2.13 mm, 95% CI: 0.65–4.92), although the subgroup difference was not statistically significant (p = 0.2772). Leave-one-out sensitivity analysis showed that the direction of effect consistently favoured 3D methods. Overall, the available evidence suggests that 3D approaches may show lower mandibular autorotation prediction errors than 2D methods; however, this finding should be interpreted cautiously because of the small number of studies, substantial methodological heterogeneity, and the exploratory nature of the quantitative synthesis. Full article
(This article belongs to the Special Issue Advances and Applications of 3D Imaging in Medicine)
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