Aims and objectives
The objective of this proof of concept study is to allow interventionalists and surgeons the direct and touchless hand gesture based control of an MRI during (real time) interventional procedures,
i.e.
MR guided prostate biopsy.
Methods and materials
Gesture recognition software for controlling a 1.5T MRI (Magnetom Avanto,
Siemens,
Germany) was implemented based on a MR-compatible camera (MR CAM Model 12M,
MRC Systems,
Germany) and Matlab R2014b (MathWorks,
USA) (Fig.
1).
A MR compatible in-room display shows the MRI user interface via virtual desktop mirroring.
The hand gestures presented to the MR camera were analysed by the software running on a separate desktop computer in the anteroom (Fig.
2).
The commands to control the MRI console were transmitted by an automation software script...
Results
The software was able to detect different hand gestures (Fig.
3): to enable the gesture recognition,
to move the FOV left/right or up/down (position of hand decides move direction and speed) and tilt MRI slice orientation by 90 degrees (sagittal,
coronal,
transverse).
Additionally,
the software allows to navigate through the already acquired images.
The system was able to identify all given hand gestures.
All test persons were able to control the MRI with gesture recognition to the tumor suspicious areas in average 182 ± 68...
Conclusion
This proof of concept study presents the implementation and evaluation of a camera based computer vision system for gesture recognition,
allowing interoperative control of a MRI using simple hand signs.
A gesture control of MRI allows new workflow concepts for a sterile and efficient work.
Personal information
Felix Güttler
Department of Radiology,
University Hospital Jena,
Friedrich Schiller University,
Germany
Am Klinikum 1
07747 Jena,
Germany
Fon: +49 3641 9 - 324 831
Fax: +49 3641 9 - 324 832
e-mail:
[email protected]
References
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