Medical augment reality using a markerless registration framework

Lee, Jiann-Der; Huang, Chung-Hsien; Huang, Tsing-Che; Hsieh, Hui-Yuan; Lee, Shin-Tseng

doi:10.1016/j.eswa.2011.11.009

Cited by 24 publications

(14 citation statements)

References 22 publications

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“…Indeed, markers are likely to be occluded by surgeon hand or a surgical instruments. Moreover, current on-patient visualization techniques typically evaluate their accuracy by measuring the registration errors of skin fiducials [2,3,5,6], the discrepancy in pixels in the image [8,10] and/or the processing time [4]. To address these drawbacks, a VSLAM-based method for on-patient visualization is proposed.…”

Section: On-patient Ar Visualizationmentioning

confidence: 99%

“…In surface-based registration techniques [2][3][4][5][6], a tablet-PC is mounted with a range camera, RGB-D sensor or stereo-vision to continuously capture the depth and color information, from which the skin surface is automatically extracted. This surface is then registered with the P3DM acquired from CT images, typically ICP (iterative closest point) is used.…”

Section: On-patient Ar Visualizationmentioning

confidence: 99%

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On-patient see-through augmented reality based on visual SLAM

et al. 2016

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Section: On-patient Ar Visualizationmentioning

confidence: 99%

Section: On-patient Ar Visualizationmentioning

confidence: 99%

On-patient see-through augmented reality based on visual SLAM

et al. 2016

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“…Lee et al [12] proposed a markerless registration framework for a medical augmented reality system. They use three cameras: two of them are mounted to form a stereo vision system and reconstruct the patient's head; the other camera is used to capture the images of the patient in real-time.…”

Section: Related Workmentioning

confidence: 99%

A Semi-automatic Markerless Augmented Reality Approach for On-Patient Volumetric Medical Data Visualization

Macedo

Apolinário²,

Souza

et al. 2014

2014 XVI Symposium on Virtual and Augmented Reality

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In general, augmented reality (AR) applications use polygonal models to augment a real scene. However, most of the medical applications have volumetric data to be visualized. Therefore, it is desirable to the medical AR systems to provide the visualization of these volumes into the real scene in real-time. In this paper we introduce a real-time semi-automatic approach for on-patient medical volume data visualization. It is proposed in a markerless augmented reality (MAR) environment and the medical data consists of a volume reconstructed from 3D computed tomography (CT) image data. A 3D reference model of the region of interest in the patient is generated and tracked from the Kinect depth stream. From the estimated camera pose, a volumetric medical data can be displayed to a physician inside the patient's anatomy at the location of the real anatomy. We evaluate the use of the named standard volume rendering techniques in the context of a MAR environment. The results obtained so far show that these techniques can be applied in this scenario in real-time.

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“…face, body, hand). In scenarios such as on-patient craniofacial medical data visualization [Lee et al 2012;Macedo et al 2014], it is specially important for a MAR environment to provide support for non-rigid tracking, which adds one level of interactivity for the user and improves the robustness of the tracking algorithm for rigid and non-rigid patient interactions. The main issue related to this support is that AR requires real-time interactivity and most of the current state-of-the-art works in the field of non-rigid surface registration do not provide such performance.…”

Section: Introductionmentioning

confidence: 99%

Multi-frame adaptive non-rigid registration for markerless augmented reality

Souza

Macedo

Apolinário

2014

Proceedings of the 13th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and Its Applications in Industry

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Augmented Reality is a technology in which the user's view of a real scene is augmented with virtual information. To provide realtime performance, the major of its applications only support rigid interaction with the fiducial marker (i.e. marker-based augmented reality) or the part of the real scene being used as a natural marker (i.e. markerless augmented reality). In this context, when the natural marker consists of a deformable object (e.g. face, body, hand), it is desirable for the application to support non-rigid interactions between the user and the marker. In this paper we present an adaptive non-rigid surface registration algorithm for markerless augmented reality. It is applied in a multi-frame manner to achieve fast performance. Likewise, it takes advantage from the power of the graphics processing unit to improve application's performance. Based on multi-frame adaptivity, we show that the markerless tracking runs almost in real-time, improving the accuracy of the tracking when compared to the rigid-only solution.

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Medical augment reality using a markerless registration framework

Cited by 24 publications

References 22 publications

On-patient see-through augmented reality based on visual SLAM

On-patient see-through augmented reality based on visual SLAM

A Semi-automatic Markerless Augmented Reality Approach for On-Patient Volumetric Medical Data Visualization

Multi-frame adaptive non-rigid registration for markerless augmented reality

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