OCCAM › Research › Methodologies › M3: Visualisation

M3: Visualisation for applied mathematics

Researcher: Dr Brian Duffy
Team Leader(s): Prof. Alain Goriely & Prof. Min Chen
Collaborators: Dr Jeyarajan Thiyagalingam
Dr Simon Walton
Dr Eamonn A. Gaffney

Background

Applied mathematicians frequently make use of established visualisation systems to display results. However, a number of projects present serious challenges to state-of-the-art visualisation techniques. This project’s focus is to make significant advances in the field of visualisation by creating compelling, novel and new visualisations, essentially creating new tools to assist researchers in reaching conclusions and obtaining results.

Techniques and Challenges

The initial challenge was to find a particular project to visualise. We reviewed over 40 projects, and we are currently working toward developing video visualisation and summary applications for computer-aided semen analysis (CASA) in BB4. The data domain is complex, multivariate, time series and spatial, which makes it difficult for researchers and clinicians to visually correlate results. The current state-of-the-art in CASA is to compute kinematic measurements of sperm motility. In addition to this, we compute head morphology and flagellum mechanics parameters [09/50]. While techniques exist for tracking the head of the cell, segmentation of the head and flagellum is difficult.

Results

We are currently developing the visualisation application using VTK, Qt and the python programming language. We are implementing parallel coordinates and glyph-based visualisation of the spermatozoa [09/50]. The novel aspect of the project lies in designing glyphs that take full advantage of the human visual system.  The challenge is to encode the large parameter set of the spermatozoa into the glyphs in a way that they succinctly summarise the kinematics, morphology and mechanics over time. To achieve this, we are using techniques from semiology (the study of signs and sign processes).

The Future

There is much scope for expansion on the work already done, for example, a comparison of simulation models with observed data, increasing the predictive power of current CASA techniques by correlating the mechanics of the sperm with the kinematics, and extending the flagellum segmentation from the 2D+time case to the 3D+time case. The visualisation applications developed for BB4 are easily extensible to other projects in OCCAM.

References

[09/50] Gaffney E.A., Gadêlha H., Smith D.J., Blake J.R., Brown J.C.K.: Mammalian Sperm Motility: Observation and Theory, Annual Review of Fluid Mechanics, 43, 501-528, 2011

Bertin J.: Semiology of graphics: diagrams, networks, maps, University of Wisconsin Press, Berg, W. (ed.), 1983

Heer J., Bostock M., Ogievetsky V.: A Tour Through the Visualization Zoo, Stanford University

Holt W.V., O'Brien J., Abaigar T.: Applications and interpretation of computer-assisted sperm analyses and sperm sorting methods in assisted breeding and comparative research, Reproduction, Fertility and Development, 19, 709-718, 2007

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