  The accurate 3D reconstruction of deformable soft body tissues from
endoscopic videos is a pivotal challenge in medical applications such as VR
surgery and medical image analysis. Existing methods often struggle with
accuracy and the ambiguity of hallucinated tissue parts, limiting their
practical utility. In this work, we introduce EndoGaussians, a novel approach
that employs Gaussian Splatting for dynamic endoscopic 3D reconstruction. This
method marks the first use of Gaussian Splatting in this context, overcoming
the limitations of previous NeRF-based techniques. Our method sets new
state-of-the-art standards, as demonstrated by quantitative assessments on
various endoscope datasets. These advancements make our method a promising tool
for medical professionals, offering more reliable and efficient 3D
reconstructions for practical applications in the medical field.
