A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
A survey of the Hough transform
Computer Vision, Graphics, and Image Processing
A new curve detection method: randomized Hough transform (RHT)
Pattern Recognition Letters
CVGIP: Image Understanding
Randomized Hough transform (RHT): basic mechanisms, algorithms, and computational complexities
CVGIP: Image Understanding
Combination of local and global line extraction
Real-Time Imaging
An Efficient Method for Generating Discrete Random Variables with General Distributions
ACM Transactions on Mathematical Software (TOMS)
Shape Detection in Computer Vision Using the Hough Transform
Shape Detection in Computer Vision Using the Hough Transform
A new model for the recovery of cylindrical structures from medical image data
CVRMed-MRCAS '97 Proceedings of the First Joint Conference on Computer Vision, Virtual Reality and Robotics in Medicine and Medial Robotics and Computer-Assisted Surgery
Fast Quantification of Abdominal Aortic Aneurysms from CTA Volumes
MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
MICCAI '00 Proceedings of the Third International Conference on Medical Image Computing and Computer-Assisted Intervention
Comparisons of Probabilistic and Non-probabilistic Hough Transforms
ECCV '94 Proceedings of the Third European Conference-Volume II on Computer Vision - Volume II
Segmentation of nerve bundles and ganglia in spine MRI using particle filters
MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part III
A novel method for retinal vessel tracking using particle filters
Computers in Biology and Medicine
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In this paper, we present a new approach for coarse segmentation of tubular anatomical structures in 3D image data. Our approach can be used to initialise complex deformable models and is based on an extension of the randomized Hough transform (RHT), a robust method for low-dimensional parametric object detection. In combination with a discrete Kalman filter, the object is tracked through 3D space. Our extensions to the RHT feature adaptive selection of the sample size, expectation-dependent weighting of the input data, and a novel 3D parameterisation for straight elliptical cylinders. For initialisation, only little user interaction is necessary. Experimental results obtained for 3D synthetic as well as for 3D medical images demonstrate the robustness of our approach w.r.t. image noise. We present the successful segmentation of tubular anatomical structures such as the aortic arc or the spinal chord.