Abstract
Conformal mapping for Computed Tomography Colonography(CTC) provides a two-dimensional (2D) representations for the original three-dimensional (3D) colon wall. Based on the flattening results of the colon, efforts have been devoted toward its applications for some medical uses, such as colon registration, Taniae Coli (TC) detection and Haustral folds segmentation, and so on. Though, the previously-used conformal mapping-based flattening methods can preserve the angle or area on the wall, the 2D flattening result still limits itself to provide more accurate information contained on the original colon wall due to its’ lack of the undulating topography. In view of this limitation of the 2D flattening model, a novelty 2.5D approach was proposed in this paper. The new approach was tested for two of the many applications, i.e., the detections of Haustral folds and TCs. Experimental results revealed its validity in these applications.
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Wang, H. et al. (2013). A 2.5D Colon Wall Flattening Model for CT-Based Virtual Colonoscopy. In: Wu, G., Zhang, D., Shen, D., Yan, P., Suzuki, K., Wang, F. (eds) Machine Learning in Medical Imaging. MLMI 2013. Lecture Notes in Computer Science, vol 8184. Springer, Cham. https://doi.org/10.1007/978-3-319-02267-3_26
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DOI: https://doi.org/10.1007/978-3-319-02267-3_26
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