Virtual voyage: interactive navigation in the human colon
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
Improved visualization in virtual colonoscopy using image-based rendering
EGVISSYM'01 Proceedings of the 3rd Joint Eurographics - IEEE TCVG conference on Visualization
Colon Unfolding Via Skeletal Subspace Deformation
MICCAI '08 Proceedings of the 11th International Conference on Medical Image Computing and Computer-Assisted Intervention, Part II
Lung nodule detection via Bayesian voxel labeling
IPMI'07 Proceedings of the 20th international conference on Information processing in medical imaging
A probabilistic model for haustral curvatures with applications to colon CAD
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention
Model-Based analysis of local shape for lesion detection in CT scans
MICCAI'05 Proceedings of the 8th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Part-Based local shape models for colon polyp detection
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part II
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Virtual colonoscopy or 'colonography' is a patient-friendly, modern screening technique for polyps. Automatic detection of polyps can serve to assist the radiologist. This paper presents a method based on clustering the principal curvatures. Via automatic polyp detection 5/6 polyps (5 mm) were detected at the expense of 9 false positive findings per case. For visualization, the bowel surface is presented to the physician in a 'panoramic' way as a sequence of unfolded cubes. Conventionally, only 93% of the colon surface is available for examination. In our approach the area in view is increased to 99.8%. The unfolded cube visualization is another step to optimize polyp detection by visual examination. Experiments show a sensitivity of 10/10 (on a per patient basis) for any polyp. The specificity was 7/10.