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Augmented Reality Image Guidance in Minimally Invasive Prostatectomy

  • Conference paper
Prostate Cancer Imaging. Computer-Aided Diagnosis, Prognosis, and Intervention (Prostate Cancer Imaging 2010)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6367))

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Abstract

This paper presents our work aimed at providing augmented reality (AR) guidance of robot-assisted laparoscopic surgery (RALP) using the da Vinci system. There is a good clinical case for guidance due to the significant rate of complications and steep learning curve for this procedure. Patients who were due to undergo robotic prostatectomy for organ-confined prostate cancer underwent preoperative 3T MRI scans of the pelvis. These were segmented and reconstructed to form 3D images of pelvic anatomy. The reconstructed image was successfully overlaid onto screenshots of the recorded surgery post-procedure. Surgeons who perform minimally-invasive prostatectomy took part in a user-needs analysis to determine the potential benefits of an image guidance system after viewing the overlaid images. All surgeons stated that the development would be useful at key stages of the surgery and could help to improve the learning curve of the procedure and improve functional and oncological outcomes. Establishing the clinical need in this way is a vital early step in development of an AR guidance system. We have also identified relevant anatomy from preoperative MRI. Further work will be aimed at automated registration to account for tissue deformation during the procedure, using a combination of transrectal ultrasound and stereoendoscopic video.

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© 2010 Springer-Verlag Berlin Heidelberg

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Cohen, D. et al. (2010). Augmented Reality Image Guidance in Minimally Invasive Prostatectomy. In: Madabhushi, A., Dowling, J., Yan, P., Fenster, A., Abolmaesumi, P., Hata, N. (eds) Prostate Cancer Imaging. Computer-Aided Diagnosis, Prognosis, and Intervention. Prostate Cancer Imaging 2010. Lecture Notes in Computer Science, vol 6367. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15989-3_12

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  • DOI: https://doi.org/10.1007/978-3-642-15989-3_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15988-6

  • Online ISBN: 978-3-642-15989-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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