  In minimal invasive surgery, it is important to rebuild and visualize the
latest deformed shape of soft-tissue surfaces to mitigate tissue damages. This
paper proposes an innovative Simultaneous Localization and Mapping (SLAM)
algorithm for deformable dense reconstruction of surfaces using a sequence of
images from a stereoscope. We introduce a warping field based on the Embedded
Deformation (ED) nodes with 3D shapes recovered from consecutive pairs of
stereo images. The warping field is estimated by deforming the last updated
model to the current live model. Our SLAM system can: (1) Incrementally build a
live model by progressively fusing new observations with vivid accurate
texture. (2) Estimate the deformed shape of unobserved region with the
principle As-Rigid-As-Possible. (3) Show the consecutive shape of models. (4)
Estimate the current relative pose between the soft-tissue and the scope.
In-vivo experiments with publicly available datasets demonstrate that the 3D
models can be incrementally built for different soft-tissues with different
deformations from sequences of stereo images obtained by laparoscopes. Results
show the potential clinical application of our SLAM system for providing
surgeon useful shape and texture information in minimal invasive surgery.
