Abstract
Visual quality of volume rendering for medical imagery strongly depends on the underlying transfer function. Conventional Windows–Icons–Menus–Pointer interfaces typically refer the user to browse a lengthy catalog of predefined transfer functions or to pain-staking refine the transfer function by clicking and dragging several independent handles. To turn the standard design process less difficult and tedious, this paper proposes novel interactions on a sketch-based interface that supports the design of 1D transfer functions via touch gestures to directly control voxel opacity and easily assign colors. User can select different types of transfer function shapes including ramp function, free hand curve drawing, and slider bars similar to those of a mixing table. An assorted array of thumbnails provides an overview of the data when editing the transfer function. User performance is evaluated by comparing the time and effort necessary to complete a number of tests with sketch-based and conventional interfaces. Users were able to more rapidly explore and understand volume data using the sketch-based interface, as the number of design iterations necessary to obtain a desirable transfer function was reduced. In addition, informal evaluation sessions carried out with professionals (two senior radiologists, a general surgeon and two scientific illustrators) provided valuable feedback on how suitable the sketch-based interface is for illustration, patient communication and medical education.
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Acknowledgements
All authors are thankful for the financial support given by Portuguese Foundation for Science and Technology (FCT). In particular, the first author thanks for the postdoctoral grant SFRH/BPD/97449/2013. This work was also partially supported by national funds through FCT with reference UID/CEC/50021/2013 and IT-MEDEX PTDC/EEI-SII/6038/2014.
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Lopes, D.S., Parreira, P.F., Mendes, A.R. et al. Explicit design of transfer functions for volume-rendered images by combining histograms, thumbnails, and sketch-based interaction. Vis Comput 34, 1713–1723 (2018). https://doi.org/10.1007/s00371-017-1448-8
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DOI: https://doi.org/10.1007/s00371-017-1448-8