TY - GEN
T1 - Real-time online adaption for robust instrument tracking and pose estimation
AU - Rieke, Nicola
AU - Tan, David Joseph
AU - Tombari, Federico
AU - Vizcáıno, Josué Page
AU - di San Filippo, Chiara Amat
AU - Eslami, Abouzar
AU - Navab, Nassir
N1 - Publisher Copyright:
© Springer International Publishing AG 2016.
PY - 2016
Y1 - 2016
N2 - We propose a novel method for instrument tracking in Retinal Microsurgery (RM) which is apt to withstand the challenges of RM visual sequences in terms of varying illumination conditions and blur. At the same time,the method is general enough to deal with different background and tool appearances. The proposed approach relies on two random forests to,respectively,track the surgery tool and estimate its 2D pose. Robustness to photometric distortions and blur is provided by a specific online refinement stage of the offline trained forest,which makes our method also capable of generalizing to unseen backgrounds and tools. In addition,a peculiar framework for merging together the predictions of tracking and pose is employed to improve the overall accuracy. Remarkable advantages in terms of accuracy over the state-of-the-art are shown on two benchmarks.
AB - We propose a novel method for instrument tracking in Retinal Microsurgery (RM) which is apt to withstand the challenges of RM visual sequences in terms of varying illumination conditions and blur. At the same time,the method is general enough to deal with different background and tool appearances. The proposed approach relies on two random forests to,respectively,track the surgery tool and estimate its 2D pose. Robustness to photometric distortions and blur is provided by a specific online refinement stage of the offline trained forest,which makes our method also capable of generalizing to unseen backgrounds and tools. In addition,a peculiar framework for merging together the predictions of tracking and pose is employed to improve the overall accuracy. Remarkable advantages in terms of accuracy over the state-of-the-art are shown on two benchmarks.
UR - https://www.scopus.com/pages/publications/84996477452
U2 - 10.1007/978-3-319-46720-7_49
DO - 10.1007/978-3-319-46720-7_49
M3 - Conference contribution
AN - SCOPUS:84996477452
SN - 9783319467191
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 422
EP - 430
BT - Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings
A2 - Ourselin, Sebastian
A2 - Joskowicz, Leo
A2 - Sabuncu, Mert R.
A2 - Wells, William
A2 - Unal, Gozde
PB - Springer Verlag
T2 - 1st International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2016 held in conjunction with 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016
Y2 - 21 October 2016 through 21 October 2016
ER -