Where Data Meets Computer Science
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Helix

This project focuses on a robust method for extracting a natural interpolating 3D piecewise cubic spline from a 2D input image of a helix object. We are able to use the generated spline to extract 3D metrics such as tortuosity and curvature, and validate the results against real-world samples at both macro and microscopic levels. The algorithm analytically chooses locations to sample the image to extract properties of the curve, such as its amplitude and perpendicular width, to ensure robustness. The generated 3D spline has few input parameters, and only requires a single view of the 2D dataset, making it suitable for a range of applications in engineering, physics, and biology.

Leptospira

Leptospira

Hair

Hair

Screw

Screw

Publications:

  • [2016,article] bibtex
    C. Willcocks, P. T. G. Jackson, C. J. Nelson, and B. Obara, "Extracting 3D parametric curves from 2D images of helical objects," IEEE Transactions on Pattern Analysis and Machine Intelligence, 2016.
    @article{Willcocks2016,
      author = {Chris Willcocks and Philip T.G. Jackson and Carl J. Nelson and Boguslaw Obara},
      title = {Extracting 3D parametric curves from 2D images of helical objects},
      journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
      year = {2016},
      doi = {10.1109/TPAMI.2016.2613866}
    }