Dense 3D Reconstruction of Endoscopic Polyp

Abstract

This paper proposes a model for 3D reconstruction of polyp in endoscopic scene. 3D shape of polyp enables better understanding of the medical condition and can help predict abnormalities like cancer. While there has been significant progress in monocular shape recovery, the same hasn’t been the case with endoscopic images due to challenges like specular regions. We take advantage of the advances in shape recovery and suitably apply these with modifications to the scenario of endoscopic images. The model operates on 2 nearby video frames. ORB features are detected and tracked for computing camera motion and initial rough depth estimation. This is followed by a dense pixelwise operation which gives a dense depth map of the scene. Our method shows positive results and strong correspondence with the ground truth.