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LARLUS: laparoscopic augmented reality from laparoscopic ultrasound

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Abstract

Purpose

This research endeavors to improve tumor localization in minimally invasive surgeries, a challenging task primarily attributable to the absence of tactile feedback and limited visibility. The conventional solution uses laparoscopic ultrasound (LUS) which has a long learning curve and is operator-dependent.

Methods

The proposed approach involves augmenting LUS images onto laparoscopic images to improve the surgeon’s ability to estimate tumor and internal organ anatomy. This augmentation relies on LUS pose estimation and filtering.

Results

Experiments conducted with clinical data exhibit successful outcomes in both the registration and augmentation of LUS images onto laparoscopic images. Additionally, noteworthy results are observed in filtering, leading to reduced flickering in augmentations.

Conclusion

The outcomes reveal promising results, suggesting the potential of LUS augmentation in surgical images to assist surgeons and serve as a training tool. We have used the LUS probe’s shaft to disambiguate the rotational symmetry. However, in the long run, it would be desirable to find more convenient solutions.

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References

  1. Pelanis E, Teatini A, Eigl B, Regensburger A, Alzaga A, Kumar RP, Rudolph T, Aghayan DL, Riediger C, Kvarnström N, Elle OJ, Edwin B (2021) Evaluation of a novel navigation platform for laparoscopic liver surgery with organ deformation compensation using injected fiducials. Med Image Anal 69:101946

    Article  PubMed  Google Scholar 

  2. Rabbani N, Calvet L, Espinel Y, Le Roy B, Ribeiro M, Buc A, Bartoli A (2022) A methodology and clinical dataset with ground-truth to evaluate registration accuracy quantitatively in computer-assisted laparoscopic liver resection. Comput Methods Biomech Biomed Eng Imaging Visual 10(4):441–450

    Article  Google Scholar 

  3. Espinel Y, Ozgur E, Calvet L, Le Roy B, Buc E, Bartoli A (2020) Combining visual cues with interactions for 3d–2d registration in liver laparoscopy. Ann Biomed Eng 48(6):1712–1727

    Article  PubMed  Google Scholar 

  4. Kalantari MM, Ozgur E, Alkhatib M, Buc E, Le Roy B, Modrzejewski R, Mezouar Y, Bartoli A (2024) Markerless ultrasound probe pose estimation in mini-invasive surgery. In: IEEE international conference on robotics and automation, ICRA

  5. Ribeiro M, Espinel Y, Rabbani N, Pereira B, Bartoli A, Buc E (2024) Augmented reality guided laparoscopic liver resection: a phantom study with intraparenchymal tumors. J Surg Res. https://doi.org/10.1016/j.jss.2023.12.014

    Article  PubMed  Google Scholar 

  6. Montaña-Brown N, Ramalhinho J, Allam M, Davidson B, Hu Y, Clarkson MJ (2021) Vessel segmentation for automatic registration of untracked laparoscopic ultrasound to CT of the liver. Int J Comput Assist Radiol Surg. https://doi.org/10.1007/s11548-021-02400-6

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

This work is funded by project ANR JCJC—IMMORTALLS.

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Authors and Affiliations

  1. Clermont Auvergne INP, Institut Pascal, Clermont-Ferrand, France

    Mohammad Mahdi Kalantari, Erol Ozgur, Mohammad Alkhatib & Youcef Mezouar

  2. University Hospital of Clermont-Ferrand, Clermont-Ferrand, France

    Emmanuel Buc & Adrien Bartoli

  3. University Hospital of Saint-Etienne, Saint-Priest-en-Jarez, France

    Bertrand Le Roy

  4. SURGAR, 22 Allée Alan Turing, Clermont-Ferrand, France

    Richard Modrzejewski & Adrien Bartoli

Authors
  1. Mohammad Mahdi Kalantari
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  2. Erol Ozgur
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  3. Mohammad Alkhatib
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  4. Emmanuel Buc
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  5. Bertrand Le Roy
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  6. Richard Modrzejewski
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  7. Youcef Mezouar
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  8. Adrien Bartoli
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Corresponding author

Correspondence to Mohammad Mahdi Kalantari.

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Conflict of interest

Mohammad Mahdi Kalantari declares to have no potential conflicts of interest. Erol Ozgur declares to have no potential conflicts of interest. Mohammad Alkhatib declares to have no potential conflicts of interest. Emmanuel Buc declares to have no potential conflicts of interest. Bertrand Le Roy declares to have no potential conflicts of interest. Richard Modrzejewski declares to have no potential conflicts of interest. Youcef Mezouar declares to have no potential conflicts of interest. Adrien Bartoli declares to have no potential conflicts of interest.

Human and animal rights

All procedures involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. This study is also supported by ethical approval with ID IRB00008526-2019-CE58 issued by CPP Sud-Est VI in Clermont-Ferrand, France.

Informed consent

Informed consent was obtained from the patients included in the study.

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Kalantari, M.M., Ozgur, E., Alkhatib, M. et al. LARLUS: laparoscopic augmented reality from laparoscopic ultrasound. Int J CARS (2024). https://doi.org/10.1007/s11548-024-03134-x

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  • DOI: https://doi.org/10.1007/s11548-024-03134-x

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