M. G. Wolkenstein · H. Hutter · M. Grasserbauer

New software tools for visualization of analytical data

Received: 30 July 1997 / Accepted: 1 February 1998

Abstract Efforts towards using advanced computer graphicsfor improved visualization of three-dimensional (3-D) sec-ondary ion mass spectrometry (SIMS) data are described. Theapplication of the Visualization Toolkit (vtk), a freely availableC++ class library for 3-D graphics and visualization for bothPC and Unix systems, is demonstrated. Various available algo-rithms are used to analyze and visualize features otherwise hid-den within data. A selection of examples is presented todemonstrate the capabilities of data visualization.

Introduction

Many advanced materials such as semiconductors, refractorymetals and composites derive their qualities from the three-di-mensional distribution of trace elements. To characterize thesematerials fully, it is necessary to obtain information not only onthe chemical identity of these trace elements and their compo-nents (phases) but also on stereometric features such as size,distance and homogeneity in three-dimensional space. Sec-ondary ion mass spectrometry (SIMS) exhibits a unique poten-tial for this task: laterally resolved secondary ion signals can bemeasured during sputter removal of the material, thus yieldingsignals with n chemical (number of masses or elements mea-sured) and three spatial dimensions [1].

Computer graphics offer an opportunity to rapidly exploreand understand these complex systems. Visualization, theprocess of exploring, transforming, and viewing data as im-ages, supports the extraction of important information hiddenwithin data; it makes possible to gain understanding and insightinto data [2, 3].

Scientific visualization was up to now largely dominated bypowerful, yet very expensive commercial systems such as AVS(Advanced Visualization System) [4]. In recent months severalnon-commercial software packages have appeared. Althoughmost of these packages run only on mainframes or Unix work-stations, some are now available for personal computers. Mostprominent is the freely available Visualization Toolkit (vtk) [5].In this paper we describe our efforts towards using vtk for im-proved visualization of 3-D SIMS analytical data. We use a se-lection of available tools to demonstrate the application of datavisualization for the identification of data features that are oth-erwise difficult to grasp. We hope this to be one further step inmaking advanced visualization techniques useful to chemists intheir daily work.

Experimental

SIMS images. The measured specimen is a high-speed steel S6-5-2 (W 6%, Mo 5%, V 2%). The instrument we used is a

double focusing Secondary Ion Microscope CAMECA IMS3fwith a typical lateral resolution of 1–3 µm and a typical depthresolution of 5 nm. An intensive primary beam (primary ionO2

+, primary beam intensity 2 µA, primary beam energy 5.5keV) homogeneously illuminates the sample by scanningrapidly over an area of typically 500 × 500 µm2. The ion opti-cal system of the mass spectrometer produces a mass-filteredsecondary ion image of the surface registered using a CCDcamera system (Pulnix TM 760) in combination with a doublemicro-channel-plate fluorescent screen assembly (GalileoHOT). The camera signal is digitized by an ITI 151 image-processor and stored on the controlling computer [6]. Under thebombardment of the primary ions the surface of the sample isetched: a typical erosion rate is approximately three atomic lay-ers per second. The measurement of the lateral distributionsover the time thus allows the determination of the three-dimen-sional elemental distributions yielding a signal with n chemical(number of masses or elements measured) and three spatial di-mensions.

Computation. All computation was performed on a 100 MHzPentium computer with 32 MB RAM running under MS Windows NT 4.0. The software used, the Visualization Toolkit (vtk) [5], written by William Schroeder, KennethMartin and William Lorensen of GE Corporate Research &Development, is freely available and can be found athttp://www.cs.rpi.edu/~martink. Vtk has been implemented onnearly every Unix-based platform and PCs (Windows NT andWindows 95).

Results

3-D SIMS generates an substantial amount of analytical in-formation. A typical 3-D SIMS depth profile results in about 100 MByte of data. Scientific visualization is a technology thatpermits to extract relevant information from these complex sys-tems making use of our highly developed visual senses. In thefollowing section several examples are presented to illustratethe proficiency of visualization techniques.

Imaging secondary ion microscopy produces one or a seriesof two-dimensional section planes. The simplest visualizationmethod for these data is displaying the section planes them-selves. A trained expert with a well developed geometric sensemay be able to use this array of images to “see” the three-di-mensional structures present, while most people will have greatdifficulties to reconstruct in mind a correct representation ofthe internal sample structure.

Figure 1 displays several modes of presentation for the vi-sualization of two-dimensional elemental distributions. The hu-man visual system has a very limited ability to see subtle dif-ferences in brightness, it can only distinguish about 30 shadesof grey. In contrast to this we can distinguish hundreds of dif-ferent colors. Thus it is very common to use false-color orpseudo-color to substitute colors for brightness in a mono-chrome image. The use of color makes it easy to show and seesmall changes locally, while at the same time to identifiy simi-lar brightness values globally in an image. For the visualizationof relative intensity ratios it may also be useful to convert in-tensities into distances. This pseudo-three-dimensional repre-sentation is shown in Fig.2. Both displacement in the z-axisand color are used to show the intensity values. This makes iteasy to see small changes locally while at the same time toidentify similar brightness values globally in an image.

The structure of the specimens sampled is inherent three-di-mensional, and the goal of the analyst is to understand this spa-tial structure. Sometimes it can be advantageous to intersect the

Fresenius J Anal Chem (1998) 361 :722–724 – © Springer-Verlag 1998

M. G. Wolkenstein (Y) · H. Hutter · M. GrasserbauerInstitute of Analytical Chemistry, Vienna University of Technology, Getreidemarkt 9/151, A-1060 Wien, Austria

3-D grid structure with an arbitrarily oriented plane (Fig.3a),but this suffers from the same principal handicaps as the previ-ous method. Many aspects of structure, both quantitative andqualitative, are not accessible from section images regardlessof their orientation. Figure 3 b demonstrates the combination ofseveral views at once. This adds a feeling of three-dimension-ality of the data, but the overall structure is still not very appar-ent.

A more useful, intuitive representation of volume data isprovided by a real three-dimensional reconstruction. This vol-ume visualization poses several problems. First, due to the sig-nificant amount of computing required it is very difficult togenerate high quality images at interactive speeds. The second

problem is a rather evident one: Most analytical data are highlymultivariate; therefore to avoid visual clutter, simplification ofthe display by extracting and rendering only the relevant fea-tures of the data is required. To evade these problems we useiso-surface rendering. This fast and effective algorithm first ap-plies a surface detector to the sample array. Then geometricprimitives are fitted to the detected surfaces. Finally theseprimitives are displayed using conventional surface-renderingalgorithms. The whole algorithm is analogous to drawing thecontour lines on a topographical map. By selecting a specificcontour value and shading the generated surface, the user cangraphically explore the 3-D shape of the data.

By showing the structural boundaries in a volumetric dis-play the connections between the regions become evident (Fig.4a). One drawback of surface rendering from serial sec-tions is that the surfaces may hide what is behind them. Some-times it may not be possible to see all parts even with rotation.The definition of a cutting function often allows to view the in-ternal structure which would be hidden otherwise. Figure 4 bshows an example. Adding the information of the sectionplanes corresponding to the cutting function allows to show theintensity distribution “inside” the overall structure.

Although static pictures are a good means of communicat-ing information, interactive user-controllable computer graph-ics significantly enhance our ability to understand the encodeddata and aid in understanding and recognizing its importantfeatures. Modern visualization software is capable of drawing adisplay quickly enough (even with complex structures) to allowdirect user interaction and thus to be useful as an analysis tool.While viewing the data the user can manipulate the viewpoint.Rotating about an object, moving in any direction, “flying”through a scene helps to achieve a better understanding.

Conclusion

The purpose of our investigations was to test the abilities of a freely available software toolkit for the visualization of3-D SIMS analytical data. Transforming numbers into visuals,visualization enables researchers to observe their data and com-putations in a more meaningful form. It was shown that usingthe Visualization Toolkit (vtk), complex and sophisticated visu-alization tasks can easily be implemented on standard desktoppersonal computers. Using 3-D graphics and visualization fordata exploration, it is possible to reveal the hidden structureand composition of analytical samples; vtk presents a powerful,yet easy to use tool with unique features. Generally, it can besuccessfully utilized for various visualization tasks in analyti-cal imaging.

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Fig. 1a–c Display modes for surface information. a Originalrange image (grey-scale proportional to concentration); b con-tour map; c segmented image. Segmentation and contouringare used to locate boundaries and edges of the overall structure

a b c

Fig. 2 Pseudo-3d representation. This representation convertsintensities into distances. Both displacement in the z-axis andcolour are used to show the intensity values

Acknowledgements This work was supported by the Jubi-laeumsfond of the Oesterreichische Nationalbank (projects6176). We would like to thank the authors of the VisualizationToolkit for providing the software package to the scientificcommunity.

References

1. Hutter H, Grasserbauer M (1994) Chemometrics and Intelli-gent Laboratory Systems 24 :99–116

2.Brodlie KW et al (1992) Scientific Visualization Techniquesand Applications. Springer, Berlin Heidelberg New York

3.Gallagher RS (1995) Computer Visualization GraphicsTechniques for Scientific and Engineering Analysis. CRCPress, Boca Raton, FL

4.Upson C, Faulhaber T Jr, Kamins D et al (1989) IEEE Com-puter Graphics and Applications 9 :30–42

5.Schroeder W, Martin K, Lorensen W (1996) The Visualiza-tion Toolkit: An Object-Oriented Approach to 3D Graphics.Prentice-Hall, Upper Saddle River, New Jersey

6.Hutter H, Grasserbauer M (1992) Mikrochim Acta 107 :137–148

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Fig.3 a, b Sectioning 3-d data. a Intersection plane; b combina-tion of different views. Displaying the section planes is a simplevisualization method for 3-D data, nevertheless many aspects ofstructure are not accessible from these section images

a

b

Fig.4a, b Displaying 3-d data. a Iso-surface rendering;b combined display. A volumetric display clearly shows theconnections between the different regions. This representationcan be combined with various section planes

a

b