Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
MIAR '08 Proceedings of the 4th international workshop on Medical Imaging and Augmented Reality
MICCAI '08 Proceedings of the 11th International Conference on Medical Image Computing and Computer-Assisted Intervention, Part II
Region flow: a multi-stage method for colonoscopy tracking
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part II
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part III
Deformable registration of bronchoscopic video sequences to CT volumes with guaranteed smooth output
MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part I
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Markerless endoscopic registration and referencing
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Observation-Driven adaptive differential evolution for robust bronchoscope 3-d motion tracking
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part III
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In this paper, we propose a hybrid method for tracking a bronchoscope that uses a combination of magnetic sensor tracking and image registration. The position of a magnetic sensor placed in the working channel of the bronchoscope is provided by a magnetic tracking system. Because of respiratory motion, the magnetic sensor provides only the approximate position and orientation of the bronchoscope in the coordinate system of a CT image acquired before the examination. The sensor position and orientation is used as the starting point for an intensity-based registration between real bronchoscopic video images and virtual bronchoscopic images generated from the CT image. The output transformation of the image registration process is the position and orientation of the bronchoscope in the CT image. We tested the proposed method using a bronchial phantom model. Virtual breathing motion was generated to simulate respiratory motion. The proposed hybrid method successfully tracked the bronchoscope at a rate of approximately 1 Hz.