Design, implementation and accuracy of a prototype for medical augmented reality

Pandya, Abhilash; Siadat, Mohammad-Reza; Auner, Gregory W.

doi:10.1080/10929080500221626

Cited by 12 publications

(16 citation statements)

References 10 publications

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“…AR is being applied across disciplines in higher education, including; environmental sciences, ecosystems, language, chemistry, geography and history (Johnson, Smith, Willis, Levine, & Haywood, 2011;Klopfer & Squire, 2007). Clinical care is also interested in AR because it provides doctors with an internal view of the patient, without the need for invasive procedures (Bajura, Fuchs, & Ohbuchi, 1992;Chris, 2010;De Paolis, Ricciardi, Dragoni, Aloisio, & Paolis, 2011;Lucio T. De Paolis, Pulimeno, & Aloisio, 2008;Pandya, Siadat, & Auner, 2005). Since students and medical professionals need more situational experiences in clinical care, especially for the sake of patient safety, there is a clear need to further study the use of AR in healthcare education.…”

Section: Introductionmentioning

confidence: 99%

Augmented reality in healthcare education: an integrative review

Zhu

Hadadgar

Masiello

et al. 2014

Preprint

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Background. Developing healthcare competencies in students and professionals poses great educational challenges. A possible solution is to provide learning opportunities that utilize augmented reality (AR), where virtual learning experiences can be embedded within a real physical context. The aim of this study was to provide a comprehensive overview of the current state of AR in terms of user acceptance, the AR applications currently developed and the effect of AR on the development of competencies in healthcare. Methods. We conducted an integrative review, which is the broadest type of research review method allowing for the inclusion of various research designs. This allows us to more fully understand a phenomenon of interest. Our review included multi-disciplinary research publications in English reported until 2012. Results. We found 2 529 research papers from ERIC, CINAHL, Medline, PubMed, Web of Science and Springer-link. Three qualitative, twenty quantitative and two mixed-method studies were included. Using thematic analysis, we have described characteristics for research, technology and education. This study showed that AR was applied across a wide range of topics in healthcare education. Furthermore, acceptance for AR as a learning technology was reported among the learners, as well as its potential for improving different types of competencies. Discussion. AR is still considered a novelty in the literature, with most of the studies reporting early prototypes. Additionally, the designed AR applications lacked an explicit pedagogical theoretical framework. Instead, the learning strategies adopted were of the traditional style 'see one, do one and teach one' and do not integrate clinical competencies to ensure patients' safety.PeerJ PrePrints | http://dx.doi.org/10.7287/peerj.preprints.335v2 | CC-BY 4.0 Open Access |

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Section: Introductionmentioning

confidence: 99%

Augmented reality in healthcare education: an integrative review

Zhu

Hadadgar

Masiello

et al. 2014

Preprint

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“…There are two different types of visualization technology that we are researching for the medical domain: augmented reality (AR) and virtual reality (VR) (22)(23)(24). Image guidance is an example of VR.…”

Section: Image-guided Surgerymentioning

confidence: 99%

“…This arm has five degrees of freedom and, based on our previous research (24), provides joint feedback with an accuracy of 0.87 mm. It was chosen because it is simple to use and its tracking accuracy is within acceptable limits.…”

Section: Tracking Armmentioning

confidence: 99%

A prototype biosensor‐integrated image‐guided surgery system

Reisner

King

Klein

et al. 2007

Robotics Computer Surgery

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“…This arm has five degrees of freedom and, based on our previous research [4], provides joint feedback with an accuracy of 0.87 mm. It was chosen because it is simple to use and its tracking accuracy is within acceptable limits.…”

Section: Tracking Armmentioning

confidence: 99%

Registered, Sensor-Integrated Virtual Reality for Surgical Applications

King

Reisner

Klein

et al. 2007

2007 IEEE Virtual Reality Conference

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Image guidance is a technique that often uses virtual reality to provide accurate localization and real-time surgical navigation. Combining image guidance with a biosensor based on Raman spectroscopy, a powerful laser-based analysis technique, would provide a surgeon both a diagnosis of tissue being analyzed (e.g. cancer) and localization information displayed within an imaging modality of choice. A virtual reality-based presentation of this type of mutual and registered information could lead to faster diagnoses and enable more accurate tissue resections.For our system, a portable Raman probe was attached to a passively articulated mechanical arm and used to scan and classify objects within a phantom skull. We discuss the implementation of the integrated system, its accuracy, its visualization techniques, and the future steps for its development and eventual application. INTRODUCTIONImage-guided surgery (IGS) fuses medical imaging, computer visualization, and real-time tracking of medical tools to provide the surgeon with a more detailed view of the patient's anatomy. Current techniques in image-guided surgery rely primarily on visual feedback from the surgical site. In this paper, we address the issue of extending this feedback by adding a sensing modality-Raman spectroscopy-to one of the already successful techniques of image guidance: virtual reality. It is hypothesized that other modalities of information from the surgical/tumor site based on these non-visual (biochemical) aspects will enhance the surgeon's ability to more completely define resection margins. Conventional histopathology lacks both the capability for providing immediate feedback and the precision to quantify the extent of disease, particularly in the early stages. Final results usually require 12-24 hours. Even the examination of the more immediate frozen sections require at least 20 minutes from the time the tissue is removed until the time an answer is available. During tumor-removal surgeries (e.g. for brain cancer), this means longer operation times with the patient remaining open.Raman spectroscopy is a technique capable of detecting normal and abnormal regions of tissue [1]. Its near-real-time analysis and the fact that it does not require sample preparation make it highly suited for in vivo applications [2]. Image-guided surgery helps the surgeon position and track instruments (such as a Raman probe) inside the body [3], making it a natural complement for Raman spectroscopy. Integration of this sensing technology with IGS should help maximize its usefulness for in vivo applications. Thus, this paper investigates the integration of a Raman probe with an image-guided surgery system for enhanced future tissue diagnosis. METHODIn order to evaluate the integration of Raman spectroscopy and image-guided surgery, we developed a system utilizing several hardware and software components. A portable Raman spectrometer was attached to a passively articulated mechanical arm. We also implemented classification algorithms for Raman spectra. The resu...

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Design, implementation and accuracy of a prototype for medical augmented reality

Cited by 12 publications

References 10 publications

Augmented reality in healthcare education: an integrative review

Augmented reality in healthcare education: an integrative review

A prototype biosensor‐integrated image‐guided surgery system

Registered, Sensor-Integrated Virtual Reality for Surgical Applications

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