A survey of the Hough transform
Computer Vision, Graphics, and Image Processing
Markov Random Field Modeling in Image Analysis
Markov Random Field Modeling in Image Analysis
Intra-retinal Layer Segmentation in Optical Coherence Tomography Using an Active Contour Approach
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part II
Detection of gad-enhancing lesions in multiple sclerosis using conditional random fields
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part III
Automated 3D reconstruction and segmentation from optical coherence tomography
ECCV'10 Proceedings of the 11th European conference on computer vision conference on Computer vision: Part III
Compensating motion artifacts of 3d in vivo SD-OCT scans
MICCAI'12 Proceedings of the 15th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
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Optical Coherence Tomography (OCT) is a noninvasive imaging technique which is used here for in vivo biocompatibility studies of percutaneous implants. A prerequisite for a morphometric analysis of the OCT images is the correction of optical distortions caused by the index of refraction in the tissue. We propose a fully automatic approach for 3D segmentation of percutaneous implants using Markov random fields. Refraction correction is done by using the subcutaneous implant base as a prior for model based estimation of the refractive index using a generalized Hough transform. Experiments show the competitiveness of our algorithm towards manual segmentations done by experts.