Anatomical Reconstruction from Endoscopic Images: Toward Quantitative Endoscopy

Abstract

BACKGROUND: Recent advances in computational image processing have made it possible to reconstruct camera motion and scene geometry from a series of monocular images. By applying these methods to endoscopic image sequences, it is possible to create detailed, quantitative anatomic reconstructions. Such anatomic reconstructions have many potential clinical uses. Our objectives in this study are to (1) develop a process flow for reconstruction from endoscopic image sequences and (2) present results supporting the hypothesis that such reconstructions can be computed. METHODS: We first outline the overall process flow for endoscopic reconstruction. Then, we present an instantiation of this process flow using recently developed methods in computational vision. We apply these methods to cadaverous specimens for which ground truth endoscopic motion is known. RESULTS: We are able to produce consistent estimates of endoscopic motion and dense reconstructions of the surrounding anatomy for >65% of 1373 image pairs. CONCLUSION: Our study indicates that processing endoscopic images to produce anatomic structure is feasible. Such reconstructions have high potential clinical value for intraoperative navigation, diagnosis, and treatment planning.