One of the current limits of laparosurgery is the
absence of a 3D sensing facility for standard monocular laparoscopes.
Significant progress has been made to acquire 3D from
a single camera using Visual SLAM (Simultaneous Localization
And Mapping), however most of the current approaches rely
on the assumption that the observed tissue is rigid or undergoes
periodic deformations. In laparoscopic surgery, these assumptions
do not apply due to the unpredictable and elastic deformation
of the tissues.
We propose a new sequential 3D reconstruction method
adapted to reconstructing organs in the abdominal cavity. We
draw on recent computer vision methods exploiting a known
3D view of the environment at rest position called a template.
However, no such method has ever been attempted in-vivo.
State-of-the-art methods assume that the environment can be
modeled as an isometric developable surface: one which deforms
isometrically to a plane. While this assumption holds for paper
and cloth-like surfaces, it certainly does not fit human organs and
tissue in general. Our method tackles these limits: it uses a nondevelopable
template and copes with natural 3D deformations
by introducing quasi-conformal prior. Our method adopts a new
two-phase approach. First the 3D template is reconstructed invivo
using RSfM (Rigid Shape-from-Motion) while the surgeon
is exploring – but not deforming – structures in the abdominal
cavity. Second, the surgeon manipulates and deforms the environment.
Here, the 3D template is quasi-conformally deformed to
match the 2D image data provided by the monocular laparoscope.
This second phase only relies on a single image. Therefore it copes
with both sequential processing and self-recovery from tracking
failures.
The proposed approach has been validated using: (i) in-vivo
animal data with ground-truth, and (ii) in-vivo laparoscopic
videos of a real patient’s uterus. Our experimental results
illustrate the ability of our method to reconstruct natural 3D
deformations typical in real surgery.
Malti, A. (2014). Variational Formulation of the Template-Based Quasi-Conformal Shape-from-Motion from Laparoscopic Images. International Journal of Advanced Computer Science and Applications, 5(3). https://doi.org/10.14569/IJACSA.2014.050323
Malti, Abed. "Variational Formulation of the Template-Based Quasi-Conformal Shape-from-Motion from Laparoscopic Images." International Journal of Advanced Computer Science and Applications, vol. 5, no. 3, 2014, https://doi.org/10.14569/IJACSA.2014.050323.
@article{Malti2014,
title = {Variational Formulation of the Template-Based Quasi-Conformal Shape-from-Motion from Laparoscopic Images},
journal = {International Journal of Advanced Computer Science and Applications},
volume = {5},
number = {3},
year = {2014},
publisher = {The Science and Information Organization},
author = {Abed Malti},
doi = {10.14569/IJACSA.2014.050323},
url = {https://doi.org/10.14569/IJACSA.2014.050323}
}
Open Access — licensed under a
Creative Commons Attribution 4.0 International License.
Unrestricted use, distribution, and reproduction in any medium, even commercially, as long as the original work is properly cited.