Clinical Evaluation of an Automatic Path Tracker for Virtual Colonoscopy
MICCAI '01 Proceedings of the 4th International Conference on Medical Image Computing and Computer-Assisted Intervention
MICCAI '02 Proceedings of the 5th International Conference on Medical Image Computing and Computer-Assisted Intervention-Part II
A self-organising network that grows when required
Neural Networks - New developments in self-organizing maps
MoNiF: a Modular Neuro-Fuzzy Controller for Race Car Navigation
CIRA '97 Proceedings of the 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation
Efficient 3D Binary Image Skeletonization
CSBW '05 Proceedings of the 2005 IEEE Computational Systems Bioinformatics Conference - Workshops
Harmonic skeleton guided evaluation of stenoses in human coronary arteries
MICCAI'05 Proceedings of the 8th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
A neuro-fuzzy controller for mobile robot navigation and multirobotconvoying
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Singularity and kinematics analysis for a class of PPUU mobile parallel robots
ROBIO'09 Proceedings of the 2009 international conference on Robotics and biomimetics
| Hi-index | 0.02 |
Objective: In this paper, we present an autonomous virtual mobile robot (AVMR) for three-dimensional (3D) exploration of unknown tubular-like structures in 3D images. Methods and materials: The trajectory planning for 3D central navigation is achieved by combining two neuro-fuzzy controllers, and is based on 3D sensory information; a Hough transform is used to locally fit a cylinder during the exploration, estimating the local radius of the tube. Nonholonomic constraints are applied to assure a smooth, continuous and unique final path. When applied to 3D medical images, the AVMR operates as a virtual endoscope, directly providing anatomical measurements of the organ. After a thorough validation on challenging synthetic environments, we applied our method to eight micro-CT datasets of cochleae. Results: Validation on synthetic environments proved the robustness of our method, and highlighted key parameters for the design of the AVMR. When applied to the micro-CT datasets, the AVMR automatically estimated length and radius of the cochleae: results were compared to manual delineations, proving the accuracy of our approach. Conclusions: The AVMR presents several advantages when used as a virtual endoscope: the nonholonomic constraint guarantees a unique and smooth central path, which can be reliably used both for qualitative and quantitative investigation of 3D medical datasets. Results on the micro-CT cochleae are a significant step towards the validation of more clinical computed tomography (CT) studies.