TY - GEN
T1 - Unified detection and tracking in retinal microsurgery
AU - Sznitman, Raphael
AU - Basu, Anasuya
AU - Richa, Rogerio
AU - Handa, Jim
AU - Gehlbach, Peter
AU - Taylor, Russell H.
AU - Jedynak, Bruno
AU - Hager, Gregory D.
PY - 2011
Y1 - 2011
N2 - Traditionally, tool tracking involves two subtasks: (i) detecting the tool in the initial image in which it appears, and (ii) predicting and refining the configuration of the detected tool in subsequent images. With retinal microsurgery in mind, we propose a unified tool detection and tracking framework, removing the need for two separate systems. The basis of our approach is to treat both detection and tracking as a sequential entropy minimization problem, where the goal is to determine the parameters describing a surgical tool in each frame. The resulting framework is capable of both detecting and tracking in situations where the tool enters and leaves the field of view regularly. We demonstrate the benefits of this method in the context of retinal tool tracking. Through extensive experimentation on a phantom eye, we show that this method provides efficient and robust tool tracking and detection.
AB - Traditionally, tool tracking involves two subtasks: (i) detecting the tool in the initial image in which it appears, and (ii) predicting and refining the configuration of the detected tool in subsequent images. With retinal microsurgery in mind, we propose a unified tool detection and tracking framework, removing the need for two separate systems. The basis of our approach is to treat both detection and tracking as a sequential entropy minimization problem, where the goal is to determine the parameters describing a surgical tool in each frame. The resulting framework is capable of both detecting and tracking in situations where the tool enters and leaves the field of view regularly. We demonstrate the benefits of this method in the context of retinal tool tracking. Through extensive experimentation on a phantom eye, we show that this method provides efficient and robust tool tracking and detection.
UR - http://www.scopus.com/inward/record.url?scp=80053529175&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=80053529175&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-23623-5_1
DO - 10.1007/978-3-642-23623-5_1
M3 - Conference contribution
AN - SCOPUS:80053529175
SN - 9783642236228
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 1
EP - 8
BT - Medical Image Computing and Computer-Assisted Intervention, MICCAI 2011 - 14th International Conference, Proceedings
T2 - 14th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2011
Y2 - 18 September 2011 through 22 September 2011
ER -