3D Multiscale visualisation for medical datasets

N. J B McFarlane; G. J. Clapworthy; A. Agrawal; M. Viceconti; F. Taddei; E. Schileo; F. Baruffaldi

doi:10.1109/MediVis.2008.14

3D Multiscale visualisation for medical datasets

N. J B McFarlane, G. J. Clapworthy, A. Agrawal, M. Viceconti, F. Taddei, E. Schileo, F. Baruffaldi

Istituti Ortopedici Rizzoli

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

A 3D multiscale view has been developed for medical datasets that are composed of multiple images of very different spatial sizes. The example data consisted of 3 volume images of bone: a 400mm femur; a 20mm micro-CT image of trabeculae; and a 0.5mm nano-CT image of a single trabecula. The images were nested, the nano-CT being inside the micro-CT, which was within the head of the femur. The images were visualised using a volume slice view. The dataset was multiscale in that each image could not be usefully resolved at the scale of the next larger image. The multiscale interaction within the system is based on the replacement of sub-scale images by small click-and-zoom tokens. Issues relating to interaction with the tokens are discussed and early outcomes from this form representation are described.

Original language	English
Title of host publication	Proceedings - 5th International Conference BioMedical Visualization, Information Visualization in Medical and Biomedical Informatics, MediVis 2008
Pages	47-52
Number of pages	6
DOIs	https://doi.org/10.1109/MediVis.2008.14
Publication status	Published - 2008
Event	5th International Conference BioMedical Visualization: Information Visualization in Medical and Biomedical Informatics, MediVis 2008 - London, United Kingdom Duration: Jul 9 2008 → Jul 11 2008

Other

Other	5th International Conference BioMedical Visualization: Information Visualization in Medical and Biomedical Informatics, MediVis 2008
Country/Territory	United Kingdom
City	London
Period	7/9/08 → 7/11/08

ASJC Scopus subject areas

Computer Vision and Pattern Recognition
Biomedical Engineering

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10.1109/MediVis.2008.14

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McFarlane, N. J. B., Clapworthy, G. J., Agrawal, A., Viceconti, M., Taddei, F., Schileo, E., & Baruffaldi, F. (2008). 3D Multiscale visualisation for medical datasets. In Proceedings - 5th International Conference BioMedical Visualization, Information Visualization in Medical and Biomedical Informatics, MediVis 2008 (pp. 47-52). [4618612] https://doi.org/10.1109/MediVis.2008.14

McFarlane, NJB, Clapworthy, GJ, Agrawal, A, Viceconti, M , Taddei, F , Schileo, E & Baruffaldi, F 2008, 3D Multiscale visualisation for medical datasets. in Proceedings - 5th International Conference BioMedical Visualization, Information Visualization in Medical and Biomedical Informatics, MediVis 2008., 4618612, pp. 47-52, 5th International Conference BioMedical Visualization: Information Visualization in Medical and Biomedical Informatics, MediVis 2008, London, United Kingdom, 7/9/08. https://doi.org/10.1109/MediVis.2008.14

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abstract = "A 3D multiscale view has been developed for medical datasets that are composed of multiple images of very different spatial sizes. The example data consisted of 3 volume images of bone: a 400mm femur; a 20mm micro-CT image of trabeculae; and a 0.5mm nano-CT image of a single trabecula. The images were nested, the nano-CT being inside the micro-CT, which was within the head of the femur. The images were visualised using a volume slice view. The dataset was multiscale in that each image could not be usefully resolved at the scale of the next larger image. The multiscale interaction within the system is based on the replacement of sub-scale images by small click-and-zoom tokens. Issues relating to interaction with the tokens are discussed and early outcomes from this form representation are described.",

author = "McFarlane, {N. J B} and Clapworthy, {G. J.} and A. Agrawal and M. Viceconti and F. Taddei and E. Schileo and F. Baruffaldi",

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AU - Clapworthy, G. J.

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AU - Taddei, F.

AU - Schileo, E.

AU - Baruffaldi, F.

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3D Multiscale visualisation for medical datasets

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