TY - GEN
T1 - Surface reconstruction from tracked endoscopic video using the structure from motion approach
AU - Sun, Deyu
AU - Liu, Jiquan
AU - Linte, Cristian A.
AU - Duan, Huilong
AU - Robb, Richard A.
PY - 2013
Y1 - 2013
N2 - The lack of 3D vision and proper depth perception associated with traditional endoscopy significantly limits the quality of the diagnostic examinations and therapy delivery. To address this challenge, we propose a technique to reconstruct a 3D model of the visualized scene from a sequence of spatially-encoded endoscopic video frames. The method is based on the structure from motion approach adopted from computer vision, and uses both the intrinsic camera parameters, as well as the tracking transforms associated with each acquired video frame to calculate the global coordinates of the features in the video, and generate a true size 3D model of the imaged scene. We conducted a series of phantom experiments to evaluate the robustness of the proposed method and the accuracy of a generated 3D scene, which yielded 1.7±0.9 mm reconstruction error. We also demonstrated the application of the proposed method using patient-specific endoscopic video image samples acquired during an in vivo gastroscopy procedure.
AB - The lack of 3D vision and proper depth perception associated with traditional endoscopy significantly limits the quality of the diagnostic examinations and therapy delivery. To address this challenge, we propose a technique to reconstruct a 3D model of the visualized scene from a sequence of spatially-encoded endoscopic video frames. The method is based on the structure from motion approach adopted from computer vision, and uses both the intrinsic camera parameters, as well as the tracking transforms associated with each acquired video frame to calculate the global coordinates of the features in the video, and generate a true size 3D model of the imaged scene. We conducted a series of phantom experiments to evaluate the robustness of the proposed method and the accuracy of a generated 3D scene, which yielded 1.7±0.9 mm reconstruction error. We also demonstrated the application of the proposed method using patient-specific endoscopic video image samples acquired during an in vivo gastroscopy procedure.
KW - endoscopy
KW - hand-eye calibration
KW - motion tracking device
KW - reconstruction
KW - structure from motion
UR - http://www.scopus.com/inward/record.url?scp=84890902026&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84890902026&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-40843-4_14
DO - 10.1007/978-3-642-40843-4_14
M3 - Conference contribution
AN - SCOPUS:84890902026
SN - 9783642408427
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 127
EP - 135
BT - Augmented Reality Environments for Medical Imaging and Computer-Assisted Interventions - 6th Int. Workshop, MIAR 2013 and 8th Int. Workshop, AE-CAI 2013, Held in Conjunction with MICCAI 2013, Proc.
T2 - 6th International Workshop on Augmented Reality Environments for Medical Imaging and Computer-Assisted Interventions, MIAR 2013 and 8th International Workshop, AE-CAI 2013, Held in Conjunction with MICCAI 2013
Y2 - 22 September 2013 through 22 September 2013
ER -