1. Introduction

The National Institute of Standards and Technology

(NIST) was established in 1901 as the National Bureau

of Standards. Although NIST’s mission has expanded

over the years, metrology, or measurement science, has

remained a central theme. In recent years, it had

become apparent that we could advance measurement

science by bringing interactive measurement methods

into the immersive environment. Immersive visualization provides a sense of being physically present in the

same space with virtual data representations. As we

move through the virtual environment and examine

these virtual objects, we observe their physical extents,

shapes, alignments, and separations. All of these

dimensional properties can be measured, so why not

use the virtual environment itself as a vehicle for

making these measurements?

While it would be ideal to derive measurements in

the course of the physical experiments during which the

original data are acquired, this is not always possible.

For example, tomographic data (such as the tissue engineering data described below) require a reconstruction

phase to get it into a form where we can begin to derive

measurements of length, area, or volume. This is also

true of computational experiments in which data may

be generated during computational runs, but those data

might not be amenable to direct measurements.

Measurement from within the immersive environment

provides unique capabilities in this regard. In particular, the interactive nature of the immersive environment

allows the researcher to apply scientific judgment in

identifying features of interest and performing manual

measurements of those features.1 When automatic

measurement algorithms do not yet exist, the informed

judgment of the scientist can be effectively exercised in

the virtual environment.

The Scientific Applications and Visualization Group

at NIST has been collaborating with NIST scientists on 

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257

[J. Res. Natl. Inst. Stand. Technol. 112, 257-270 (2007)]

Measurement Tools for the Immersive

Visualization Environment: Steps Toward the

Virtual Laboratory

Volume 112 Number 5 September-October 2007

John G. Hagedorn, Joy P.

Dunkers, Steven G. Satterfield,

Adele P. Peskin, John T. Kelso,

and Judith E. Terrill

National Institute of Standards

and Technology,

Gaithersburg, MD 20899-8911

john.hagedorn@nist.gov

joy.dunkers@nist.gov

steven.satterfield@nist.gov

adele.peskin@nist.gov

john.kelso@nist.gov

judith.terrill@nist.gov

This paper describes a set of tools for

performing measurements of objects

in a virtual reality based immersive

visualization environment. These tools

enable the use of the immersive environment as an instrument for extracting

quantitative information from data

representations that hitherto had be used

solely for qualitative examination. We

provide, within the virtual environment,

ways for the user to analyze and interact

with the quantitative data generated. We

describe results generated by these

methods to obtain dimensional descriptors

of tissue engineered medical products.

We regard this toolbox as our first

step in the implementation of a virtual

measurement laboratory within an

immersive visualization environment.

Key words: immersive visualization;

measurement; tissue engineering; virtual

laboratory; virtual reality.

Accepted: September 26, 2007

Available online: http://www.nist.gov/jres

1 Certain commercial equipment, instruments, or materials are identified in this paper to foster understanding. Such identification does

not imply recommendation or endorsement by the National Institute

of Standards and Technology, nor does it imply that the materials or

equipment identified are necessarily the best available for the

purpose.
a variety of projects involving scientific visualization.

As part of those efforts, we have created an immersive

visualization system that is pictured in Fig. 1. This figure indicates several important components of the system: the three screens that provide the visual display,

the motion tracked stereoscopic glasses, and the handheld motion tracked input device. The screens are large

projection video displays that are placed edge-to-edge

in a corner configuration. These three screens are used

to display a single three-dimensional (3D) stereo scene

as shown in the figure. The scene is updated based on

the position of the user as determined by the motion

tracker. This allows the system to present to the user a

3D virtual world within which the user can move and

interact with the virtual objects. The main interaction

device is a hand-held three button motion-tracked wand

with a joystick.

We have been using this virtual environment for

various applications such as visualization of chemical

simulations, microscopy, and rheological properties of

concrete [1]. In these applications, we have used the

immersive visualization system to provide the scientist

with views and interactions for a qualitative experience

of data. The user can look at data representations at any

scale and position, move through data and change scale

and orientation easily, and control the elements of the

virtual world using a variety of interaction techniques.

This is fairly typical of the current use of virtual reality for scientific visualization. The technology provides

the researcher with the ability to perform qualitative

tasks with the virtual data representations such as looking for patterns or seeing spatial relationships among

elements. Uses of immersive visualization for applications such as architectural walk-throughs [2] and psychological treatment [3] are clearly using the technology to provide the user with a subjective qualitative

experience.

Although we intend this measurement work to be

useful in many contexts, our driving application is tissue engineering, which will be described in more detail

below. We had been using our immersive visualization

system to provide researchers with qualitative views of

their tissue engineering data [4], and it was a natural

step to begin to use it to extract quantitative information from the virtual scene. With the tools that we

describe here, the researcher can make measurements

of virtual objects and perform analyses of those measurements within the virtual environment. In effect, we

have made the immersive visualization environment

into a scientific instrument that gives us the ability to

acquire and process data.

It is these tools that are the main subject of this paper.

This project is a first step toward a true virtual laboratory [4]. We envision the virtual laboratory as a place

where researchers interact with ongoing physical

experiments and simulations using interactive tools for

visualization, measurement, and analysis of the experimental or simulation data. This first step relies on manual measurement methods based on researchers’ scientific judgements.

This work is not the first attempt to perform measurements in a virtual reality environment or desktop

visualization system. For example, Crumbs [5] is a system that allows researchers to manually measure the

lengths of fibers in volume data sets. Bethel [6]

describes a system that uses a virtual protractor and

caliper to measure angles and distances from stereo

image pairs generated by a scanning electron microscope. The most pertinent prior work has been done for

two medical applications [7, 8]. The tools in these

projects measure distance, volume, and angles, and

both operate on desktop systems. A virtual tape measure [9] has been developed to aid in micro-surgery that

operates in an augmented reality environment. The

most relevant work is described by Reitinger [10] who

describes a set of virtual reality tools for making measurements (distance, angle, and volume) for surgical

planning. They point out that the virtual environment

affords more natural interactions, so the user is able to

make measurements more effectively than could be

done on a desktop system. Our work involves the

implementation of some similar measurement tools,

some novel tools, and incorporates more tools for

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Fig. 1. A user in the NIST immersive visualization environment.
statistical analyses and investigation of the measurement data derived from the 3D scene. Moreover, the

toolbox is not specific to any one application; the tools

are general and can be moved from application to application.

2. The Tissue Engineering Application

The project that has motivated this work involves the

characterization of materials used in tissue engineered

medical products (TEMPs). Tissue engineering is an

emerging interdisciplinary field that has evolved

because of the dire need for compatible replacement

organs and tissues in light of the shortages of transplantable organs and the problems associated with biomaterial implants [11].

The term tissue engineering is defined as: “The application of principles and methods of engineering and

life sciences toward a fundamental understanding of

structure-function relationships in normal and pathological mammalian tissues and the development of

biological substitutes to restore, maintain, or improve

tissue function.” [12] TEMPs often consist of a synthetic or naturally-derived scaffold that provides form and

foundation for cells as they produce the tissue of interest. Successful TEMPs will allow cell infiltration

and foster proliferation and differentiation within the

scaffold.

According to a recent review by Lysaght [13],

20 TEMPs had entered Food and Drug Administration

clinical trials by the end of 2002. Four were approved,

and none are commercially successful despite sound

technology behind the products. Some of the reasons

for the lack of commercial success cited in this review

are: improvement over existing therapies either are not

large enough or are for too small a patient group, protracted and costly regulatory approval caused the products to require a very large return on investment, ineffective marketing, limited physician and user acceptance, and lack of a low cost manufacturing approach.

Tissue engineering and regenerative medicine have

been identified by NIST as biotechnology areas where

metrology development is required to lower the cost

barrier for product commercialization. To this end, the

Biomaterials Group at NIST is developing measurements and methods to quantify cell/scaffold interactions. In this case, we are quantifying how the structure

of these scaffolds influences cell response and nutrient

and waste transport. We are quantifying structural

descriptors such as porosity, pore size distribution, pore

connectivity and tortuosity, strut size distribution, strut

planarity and orientation, and anisotropy measures of

the aforementioned descriptors. Using the immersive

visualization environment lets us simultaneously spatially encode the values of these descriptors within a 3D

image of the scaffold and see correlations not readily

observable with desktop displays.

Some techniques traditionally used to quantify scaffold structure include scanning electron microscopy,

mercury and flow porosimetry, gas adsorption, and

pycnometry [14]. These techniques probe a limited

number of descriptors of interest—most commonly

porosity, pore size distribution, tortuosity, surface area,

permeability, and compressibility—with caveats. The

biggest drawback to all of these techniques is that they

do not provide a direct measure of scaffold structure in

three dimensions. X-ray micro-computed tomography

(X-ray μ-CAT) provides a direct measure of scaffold

structure and has been used to generate 3D images of

scaffolds [15, 16]. There have been several efforts to

quantify the results from using this technique for both

scaffold structure [14, 17] and mineralization within

bone tissue constructs [18, 19].

In this work, we use X-ray μ-CAT images from two

types of structures commonly used in orthopedic applications: regular structures manufactured using rapid

prototyping (RP) methods (Scaffold A) and random

structures fabricated with salt-leaching (Scaffold B).

Figure 2 shows two-dimensional (2D) X-ray μ-CAT

images of Scaffolds A and B, and Fig. 3 shows 3D representations of both Scaffolds A and B. The characteristics of these two scaffold types will be described in

more detail in Sec. 5.

Scaffold A is being considered as a geometric reference scaffold. A geometric reference scaffold has a

well-defined and reproducible geometry to control the

effect that geometry has on cell response so that other

factors such as cell type or growth factors can be investigated. We are interested in how well Scaffold A

adheres to its design specifications and in fabrication

variability. The scaffold descriptors of interest are:

fiber diameter and aspect ratio, fiber orientation, parallelism of fibers, planarity of fiber layers, and angles

between fibers. Cell ingrowth is an issue for structures

like those of Scaffold B. Our intent is to develop tools

that measure not only the size of the pores but also the

size and number of connections between pores. This

information is critical in designing scaffolds that enable

cell ingrowth and efficient transport of nutrients and

waste.

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3. The Tools

Clearly, it would be desirable to develop automated

methods or a hybrid mixture of automated and interactive methods for measuring these scaffold descriptors,

but such methods do not yet exist. In their absence, we

have pursued purely interactive methods implemented

within the immersive visualization environment. We designed a collection of general-purpose tools to address

the immediate research needs of the tissue engineering

project. Our objective was to build a software system

within the virtual environment that integrates measurement, analysis, and interactions that link analysis results

with the visualization. More specifically, we envisioned

the following scenario:

• The user manually collects a series of measurements.

• A statistical analysis is made.

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Fig. 2. Two-dimensional slices of X-ray μ-CAT data for both Scaffold A and Scaffold B.

Scaffold A Scaffold B

Fig. 3. Three-dimensional representations of the X-ray μ-CAT data. for Scaffolds A and B.
• This analysis, including a representation of the

distribution of measurements, is presented to the

user in the virtual environment as either a table

or a histogram.

• The user can then interact with the display of the

measurement distribution in order to highlight

measurements (in the virtual scene) that fall

within any selected range of values.

All of these tasks should be performed in real-time

during the immersive visualization session. We

designed and implemented the following tools to support the measurements needed for the tissue engineering project:

• LineMeasure

• CylinderMeasure

• EllipsoidMeasure

• WandClip

• BoxClip

The first three tools produce measurements: the

other two tools are supporting software intended to

improve the utility of the measurement tools. Each of

the three measurement tools places objects into the

virtual world that are, in some sense, surrogates for the

features being measured. The researcher can position

and stretch those surrogate objects to fit the features of

the data representations under study. The measurement

of those features can then be taken from the known

dimensions of the surrogates, and the user is able to

analyze and interact with those measurements.

We envision these tools as the first of a set that will

form a general purpose tool-box for the measurement

of dimensional quantities in a virtual laboratory.

3.1 LineMeasure

With the LineMeasure tool, the user can measure the

linear distances between pairs of points in the virtual

scene. Each measurement is represented visually by a

line connecting the points, 3D markers at each end

point, and a text display of the length of the line segment. See Fig. 4 for an example showing two such

measurements. The interface is modal with four modes:

create mode, edit mode, delete mode, and inactive

mode. The user switches modes by making selections

using the menuing system.

In create mode, the user can make a new measurement by moving a 3D cursor to the desired location and

pressing a wand button dedicated to this tool. After the

first point is selected, a 3D rubberband line is displayed

between the first anchor point and the current location

of the wand. A numeric text display is superimposed

over the line. The text is continually updated to show

the current length of the line. The user moves the wand

to the second point and presses the wand

button again to complete the measurement.

In edit mode, the user can modify existing measurements, and in delete mode the user can remove measurements. The user can also go into inactive mode

which simply causes the tool to ignore all user input

except for selecting one of the other modes; this mode

is useful during scene navigation and measurement

inspection.

At any step in the process, the user can analyze and

interact with the current set of measurements through a

panel that is displayed by the menuing system within

the virtual scene. Figure 5 shows the panel in use in the

context of the virtual scene. When the user presses the

Get Data button on the panel, a histogram of the line

segment lengths together with their mean and standard 

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Fig. 4. The LineMeasure tool. Two measurements are shown

measuring the diameters of two struts of a Scaffold A sample.
deviation are displayed. The user can use the wand to

sweep out a portion of the histogram and have the

system highlight the corresponding line segment measurements whose lengths lie in that portion of the

histogram.

Note that the use of the rubberband line is a standard

technique in desktop interfaces for interactively connecting two points. We felt that users would find this a

familiar (and thus easy to use) feedback mechanism.

The numeric display of the line length while it is being

stretched to the desired points was intended to provide

the type of quantitative information that one might see

on a technical drawing, with the added benefit of continual update during the interactive operation. Note also

that the highlighting based on interaction with the

histogram could be regarded as a form of an interactive

technique known as brushing [20].

3.2 CylinderMeasure

This tool enables the user to interactively measure

tube-like structures. This is done by placing a 3D wireframe representation of a quasi-cylinder unto the scene

and moving that object to approximate the position of

the tube structure. This quasi-cylinder (which we will

refer to simply as a cylinder) is a tube with elliptical

cross section that can be manipulated to change its

length, either cross sectional axis, and orientation.

Figure 6 shows the CylinderMeasure tool in use.

The interface of CylinderMeasure is also modal. In

this case, there are three modes: create/edit mode,

delete mode, and inactive mode. For this tool, we combine create and edit modes to minimize the number of

times that the user must change modes.

In create/edit mode, the user can create a new cylinder measurement or modify an existing measurement.

Again, the primary interaction is through the motiontracked wand to which a virtual 3D cursor is attached.

When the cursor is not in proximity of an existing

cylinder measurement, pressing the wand button causes the creation of a new cylinder measurement placed

at the location of the 3D cursor with a standard size and

orientation.

The user can move any cylinder measurement object

by grabbing it by its center and dragging, while the

length and orientation of the cylinder can be changed

by grabbing and dragging end-points of the cylinder.

The lengths of the cross sectional axes can be interactively changed by dragging axes end points; this action

can also be used to reorient the elliptical cross sections

rotationally about the longitudinal axis.

Similar to the LineMeasure tool, there is a delete

mode in which the user can delete existing cylinder

measurements, and an inactive mode that causes the

tool to ignore user input except for moving to another

mode.

Interactive analysis of these cylinder measurements

can take several forms. We have implemented several

analyses that can be accessed during the immersive

session:

• average diameter

• longitudinal direction

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Fig. 5. The analysis panel for the LineMeasure tool as it might

appear in the 3D scene. The user has swept out a range of lengths

from about 290 to 320 on the histogram and the corresponding

measurements have been highlighted in the virtual world.

Fig. 6. The CylinderMeasure tool in use. The user has fit the cylinder surrogate object to a strut of the Scaffold A sample. Note that this

strut has been isolated by use of the BoxClip tool (see Sec. 3.5).
• aspect ratio of cylinder cross section

• eccentricity of cylinder cross section.

Except for longitudinal direction, each of these

analyses present a mean and a standard deviation,

together with a histogram in a panel in the virtual

scene; the display is similar to that in Fig. 5. The longitudinal direction analysis is done by calculating an

average 3D direction for the longitudinal axis of the

cylinder using spherical weighted averaging [21];

angular deviations of each measurement are then calculated for each measurement and a histogram of these

deviations is presented to the user in the virtual scene.

In all cases, the user can interactively sweep out a range

of the histogram and highlight the measurements in that

range in the 3D scene.

It should be noted that there are other sorts of analyses that could be done for the cylinder measurements.

For example, we could provide statistics on the volume,

length, or cross sectional area of the cylinders.

3.3 EllipsoidMeasure

The EllipsoidMeasure tool gives the user the ability

to measure 3D regions that are ellipsoidal in nature.

The user places a sphere into the 3D scene, then stretches, drags, and orients it to form an ellipsoid that fits the

region to be measured. Each of the three axes can be

independently changed and the location and orientation

of the ellipsoid can be directly manipulated. Figure 7

shows the tool in use.

As with the previous tools, the interface is modal. In

create/edit mode, the user can place a new measurement with a point and click using the motion tracked

wand. The initial ellipsoid is a wire-frame sphere with

X, Y, and Z axes displayed to the user. The user can

pick any of the six axis end-points to stretch or compress each dimension or to reorient the ellipsoid; the

center is fixed during axis end-point manipulations.

The user can also select the center point of the ellipsoid

to drag it to a new position.

Again, the tool has both delete and inactive

modes that operate as in the CylinderMeasure and

LineMeasure tools.

As for the CylinderMeasure tool, there are many

analyses of the ellipsoid data that we could have provided to the user during the interactive session. For

our initial purposes, we implemented the following

analyses:

• 3D direction of the longest axis

• length of the longest axis

• eccentricity of the cross section perpendicular

to the longest axis

The length and eccentricity measurements are presented with the mean, standard deviation and histogram

display in a panel similar to that in Fig. 5. The 3D direction of the longest axis is handled much as the 3D

direction of the longitudinal axis of the cylinder measurements as described above. The interaction with the

histogram and the highlighting behavior is provided in

a similar way.

3.4 WandClip

The WandClip tool lets the user discard portions of

the 3D scene to reveal interior structure that may be

hidden. When this tool is activated. a virtual plane

(indicated by a wireframe rectangle) is attached to the

3D position of the wand. The position of this plane

relative to the wand is configurable, but is usually specified to be about 0.2 m away from the wand in real

space and oriented orthogonal to the Y axis of the

wand. The tool is configured such that it can act on

some elements of the virtual scene while leaving others

unaffected.

As the user moves the wand in the 3D scene, the

plane cuts into the scene, acting like a sort of window

into the interior structure of objects. It is as if the user

is controlling the position of a sheet of glass and everyVolume 112, Number 5, September-October 2007

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Fig. 7. The EllipsoidMeasure tool in use to measure pore size in the

Scaffold B material.
thing that is closer to the viewer than that sheet is

removed from the scene. Figure 8 shows the operation

of WandClip. This tool is not directly tied to the operation of the measurement tools, but it is intended to help

the user to make preliminary identification of structures

to be measured.

3.5 BoxClip

The BoxClip tool is related to the WandClip tool in

that it clips out portions of the 3D scene in order to

reveal hidden features. However the BoxClip tool is not

always tied to the position of the wand; the user can

position a clipping box that remains spatially stable in

the virtual scene.

The tool presents the user with a wire-frame box.

Objects outside of that box are clipped out of the 3D

scene. Each face of the box can be selected and dragged

with the motion-tracked wand; it is a rubberband box

that can easily be stretched and compressed to encompass the desired region. As with WandClip, this tool can

be configured so that it will clip some elements and not

others. Figure 9 shows BoxClip in action.

Again, this tool is not inherently tied to any of the

measurement tools, however we intend to use this tool

to facilitate the measurement interactions. The tool can

be used to isolate regions of interest and features to be

measured. Because the displayed sub-region is spatially stable, measurements can be easily made on the

exposed structures.

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Fig. 8. The WandClip tool in action. The image on the left shows a complete Scaffold A data set. The

image on the right shows the samce data set with the interior revealed by the WandClip tool.

Fig. 9. The BoxClip tool used to reveal a single strut of Scaffold A material. The image on the left

shows a complete scaffold A data set and the image on the right shows the action of the BoxClip tool.
4. Implementation

The underlying software on which our immersive

system is built is DIVERSE [22], which provides a

portable, modular, open source software platform that

manages all aspects of the virtual environment. This

includes handling the interfaces to devices (such

as motion trackers and user interface devices), stereo

parallax, asynchronous viewing frusta, and other functions required for a fully immersive virtual reality

system.

There are several features of DIVERSE that are particularly useful in the work described here. DIVERSE

provides:

• a flexible scheme for use of the graphics scenegraph

• support for addition of user-supplied components

• support for communication via shared memory

between components

The graphics scenegraph is a data structure that

describes a hierarchy of relationships among all of the

items to be displayed in the virtual scene. DIVERSE

provides a structure into which we place the data representations, such as the models of the scaffold material

as well as the surrogate objects created by the measurement tools. The scenegraph gives us simple mechanisms for controlling, for example, which items are

affected by the clipping tools and which are not.

DIVERSE’s support for user-supplied software components and shared memory communication is central

to the way that we build our tools. We add software

components to the system through dynamically shared

objects (DSOs), which DIVERSE loads at run-time and

executes during immersive sessions. DIVERSE executes the code in DSOs in clearly defined and easily

controlled ways, and each DSO component can communicate to other DSO components or to external programs via DIVERSE-supplied shared memory tools.

Moreover, this shared memory can be networked,

allowing these external programs to be executed on any

system accessible to our immersive system.

The design and implementation of our measurement

tools are inspired, in part. by the Unix Philosophy [23]

which calls for simple components connected by

simple interfaces. In standard Unix programming, this

often means small programs, each of which does one

thing well, connected by text files (or pipes). In that

tradition, we try to design DSOs, each with a limited

general-purpose functionality, that communicate

through shared memory. Furthermore, non-DSO computation can communicate with DSO components

through shared memory, further enhancing our ability

to extend the system. Using these mechanisms, we are

able to augment the functionality of the virtual environment in an incremental fashion and to build and to combine sets of components that are useful for a variety of

applications.

Within this context, we use VEWL (the Virtual

Environment Windowing Library) [24] to provide

many aspects of our user interface. VEWL is a software

subsystem that operates within the DIVERSE framework, with both DSO and non-DSO components. It

enables the use of standard desktop user interfaces

within the immersive environment. With VEWL, we

are able to use simple existing graphical user interface

(GUI) tools, such as FLTK (the Fast Light Toolkit)

[25], to quickly construct effective user interfaces that

operate within the immersive environment. Communication with other DSOs and other external programs

are easily accomplished through shared memory.

Each of the measurement tools described above was

implemented as a separate DSO. User input such as

mode changes, wand button presses, and wand position

are conveyed to the DSOs through shared memory. The

execution of external programs is also managed

through these mechanisms. For example, when the user

presses a button on one of the VEWL-menus, an external program, Dataplot [26], is executed to generate

statistics and to produce the histograms described

above. Dataplot is simply an existing application

program that is executed, unmodified, during the

immersive session. Information is passed between

Dataplot and the DIVERSE DSOs via files.

Another aspect of our implementation approach was

to try to provide user interface methods that would be

familiar to the user whenever possible. This is why,

even with the 3D virtual scene, we use standard 2D

desktop GUI mechanisms, as provided by FLTK and

VEWL. Another example is our use of the rubberband

line in the LineMeasure tool; this is a mechanism that

the user is likely to have seen and used in 2D drawing

applications.

5. Methods

As mentioned above, we use X-ray μ-CAT images of

our two scaffold types: the geometrically regular

Scaffold A and the randomly structured Scaffold B. The

particular RP technology used for Scaffold A is called

fused deposition modeling (FDM) [27]. In short, FDM

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creates successive cross sections of a 3D object. FDM

heats the polymer, in our case poly(ε-caprolactone)

(PCL), to a high temperature to reduce its viscosity and

then extrudes the PCL through a small nozzle. As the

nozzle moves along both the x- and y-axis across a

foundation, polymer is deposited in a pre-defined

pattern and fused with the layer below. Successive

cross sectional patterns are laid down until the object is

completed. The struts are designed to be 400 μm in

diameter and are laid down in a 0-60-120 degree layer

pattern. The gap width is designed to be 800 μm.

The salt leached scaffold, Scaffold B, was made by

first infiltrating packed sodium chloride crystals with a

dimethacrylate resin. The sizes of the sodium chloride

crystals were selected by sieving through openings of

250 μm to 150 μm. The samples were photocured,

postcured in a vacuum oven, and soaked in deionized

water to remove the salt. Details about this procedure

are provided elsewhere [28].

The X-ray μ-CAT images were generated with a

Skyscan 1072 scanner with voxel spacing of 12.88 μm

in each direction. The images were output as a series of

bitmap image files. Each 2D image series was assembled into a 3D data set which was then converted to a

polygonal surface representation with a combination of

custom software and the Visualization Toolkit (VTK)

library [29]. These polygonal models were the virtual

data representations that were displayed, manipulated,

and measured in the immersive visualization environment. Figure 3 shows renderings of the polygonal

models for Scaffolds A and B. We generated data for

two samples of Scaffold A, which we will refer to as

PCL1 and PCL2, and one sample of Scaffold B, the salt

leached structure.

In addition to these experimentally derived data sets,

we also constructed a virtual model that conforms to

the design specifications for Scaffold A as described

above; we refer to this as the Scaffold A Synthetic

Model. The Synthetic Model is, however, polygonally

based so it is an approximation of the ideal structure.

The first of the measurement tools that we implemented was the LineMeasure tool. We used this to

measure the diameters of the struts in the PCL1

scaffold. Each strut was measured in several places for

a total of 82 linear measurements over the entire

sample. Upon completion of the implementation of the

CylinderMeasure tool, we manually fit cylinders to

each strut in the PCL1, PCL2, and Synthetic Model

structures. We used these to measure horizontal gap

width, vertical gap width, strut aspect ratio, strut parallelism, and strut planarity. A total of 21 struts were

measured in PCL1, 25 struts in PCL2, and 26 struts in

the Synthetic Model. We then used the EllipsoidMeasure tool to try to measure pore size in the salt

leached material (Scaffold B); our difficulties in making these measurements will be described in Secs. 6

and 7.

6. Results

As the main subject of this paper is the tools themselves, we present only a few of the quantitative results

that we obtained from the measurements of Scaffold A

to give an indication of the utility of our tools.

Table 1 shows the mean vertical distances between

struts (in μm) for the three Scaffold A samples. The

results for the Synthetic Model conform well to the

design specifications and give us confidence in our

measurement methods. The results for PCL1 and PCL2

allow us to compare the design specifications to the

manufactured material; the design calls for a center-tocenter distance of 1200 μm and an edge-to-edge gap of

800 μm. The statistics show us that these distances are

far smaller than expected. Similarly, Table 2 shows the

mean angles between adjacent struts for the Synthetic

Model, PCL1, and PCL2. In this case, we see very good

agreement between the angles specified in the design

(60 degrees) and the angles measured by our system for

the Synthetic Model as well as the manufactured

samples. We should note that for the statistics presented in Tables 1 and 2, the breakdown by orientation was

done after the interactive measurement sessions by analyzing data files stored during the sessions.

In addition to these data, we also obtained useful

measurements of strut diameter, aspect ratio, planarity,

and parallelism for Scaffold A sample. However the

measurement of pore sizes in Scaffold B (the salt

leached scaffold) using the EllipsoidMeasure tool

proved problematic. We were unable to get satisfactory

results in this task, which will be discussed more in the

next section.

We will use these data to relate dimensional characteristics to functional characteristics of the scaffold

materials. Establishing these relationships will require

experiments that correlate scaffold structural descriptors with cell response (i.e., proliferation and differentiation).

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7. Discussion

The measurements made of the Scaffold A Synthetic

Model and the derived statistics show very good agreement with the design specification that was used to construct the model. This gives us considerable confidence

in the measurements and statistics for the manufactured

models (PCL1 and PCL2). It seems likely that the

largest source of the error that we see in the Synthetic

Model data is due to the difficulty of precisely positioning the tools by hand in the virtual world and to the fact

that the Synthetic Model is approximated in the virtual

world by a polygonal model.

We can expect that errors of similar or greater magnitude are present in the measurements of PCL1 and

PCL2, where the correctness of the polygonal data

representations must be assessed. Of course, the

assumption that the data representations are true to the

underlying physical phenomena is inherent in all use of

visualization (immersive and otherwise). The value of

any insight gained from a visualization is entirely

dependent on the fidelity of the visual representation to

the phenomenon being studied. When making measurements in the virtual environment, it will be important to

estimate the errors introduced by the use of that technology so that these errors can be included in a statement of uncertainty for the measurements. For example, the accuracy and calibration of the motion tracking

system [30] affects the accuracy of the measurements.

The assessment of errors specifically attributable to the 

use of the immersive visualization environment is the

subject of a separate project that is in progress at NIST

and will not be addressed here. Measurement errors

will differ from application to application and from one

immersive system to another. It is unclear whether the

magnitude of the errors in the measurements described

here materially affect our understanding of the scaffold

materials.

While using these tools, it became very clear that the

scientific judgment of the researchers played a critical

role in the accuracy of the results. For example, in

using the CylinderMeasure tool, the user must judge

where to place the walls of the modeled cylinder, which

inevitably must deviate from the walls of the strut as

represented in the virtual environment. The results are

only as good as the researcher’s judgment. But, of

course, the whole point is that the struts are not perfect

cylinders and some best-fit must be found. Our tools

provide a manual method, but this certainly suggests

that we might want to pursue automated methods as

well as hybrids of automated and manual methods.

As mentioned above, we were unable to make useful

measurements of pore sizes in the salt leached scaffold

material using the EllipsoidMeasure tool. We found

that the manipulation of the ellipsoid models was

reasonably easy and placing them relative to the salt

leached scaffold model was not difficult. The problem

arose from the nature of the salt leached scaffold data

and the polygonal representation generated from those

data. We found that the irregular structure of the

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Table 1. Mean and standard deviation of measured vertical distances in μm between struts broken down by orientation

group. Each orientation group is labeled according to its nominal orientation in degrees: 0, 60, or 120

Strut Syn Model PCL1 PCL2

Groups Mean SD Mean SD Mean SD

Center 0 1199.9 1.1 835.9 19.2 721.7 5.7

to 60 1199.6 1.2 799.9 5.7 749.2 32.3

Center 120 1200.5 0.9 844.0 60.2 761.1 19.8

Edge 0 804.5 1.0 539.7 7.9 378.2 7.5

to 60 801.1 0.9 473.6 10.9 399.4 27.2

Edge 120 802.7 0.9 542.3 68.8 427.2 4.3

Table 2. Mean and standard deviation of measured angles in degrees between struts in different orientation groups

Syn Model PCL1 PCL2

Strut Groups Mean SD Mean SD Mean SD

0 and 60 59.9 0.1 60.2 0.3 60.0 0.4

0 and 120 60.0 0.0 60.3 0.2 59.9 0.3

60 and 120 60.1 0.1 59.6 0.2 59.9 0.3
scaffold material made it difficult for the researcher to

unambiguously identify specific pores as well as pore

connections. It was felt that any measurements that we

made with the ellipsoids would be unreliable.

Concerning ease-of-use, we found that use of the

LineMeasure tool was easy and fast. We were able to

make many measurements and we have confidence in

the statistics generated from these measurements. The

use of the CylinderMeasure tool was quite timeconsuming, however we felt that the quality of the

results were good. Certainly the fact that the angular

measurements so closely matched the design specifications serves to verify both the accuracy of the manufacturing process as well as the accuracy of the measurement method. We felt that we were well-compensated

for the investment in time in using the CylinderMeasure tool. The information provided by this tool

was very rich and we were easily able to derive many

descriptors from the same set of fitted cylinders.

We also found that these manual methods (particularly CylinderMeasure) were tiring for the user. (Note

that for our studies, we generally want to make many

measurements and calculate statistics. This means that

many repetitions of the use of the tool were required.)

The fatigue was partly due to the fact that it was difficult to manually drag the surrogate objects to exactly

the point desired. The steadiness of the hand became a

factor and many small adjustments were often required

to get the desired result. This problem could be somewhat mitigated by enlarging the scale of the virtual

scene so that small mis-positionings would have less

impact. This rescaling, however, presented its own

difficulties when navigating through the larger virtual

world.

Another important user-interface issue was visual

clutter. This was particularly a problem when using the

CylinderMeasure tool; it is visually confusing when

there are many cylinders (as produced by the measurement tool) present on the screen simultaneously. We

need mechanisms for managing the display of these

cylinders. Sometimes it is useful and important to be

able see many at the same time, but sometimes it

disrupts the user’s ability to understand the scene.

The clipping tools were useful in helping to alleviate

some of the visual clutter and as an aid in isolating the

elements of the scene to be measured. The BoxClip tool

was far more useful than the WandClip tool because the

box was not directly tied to the position of the wand.

The clipping box could by placed and sized exactly as

the user desired and remained stable during the measurement tasks. This was very effective in allowing the

user to work on particular features of the data representations. This tool has been used quite productively in

other applications, particularly in a project involving

the visualization of a simulation of hydrating cement.

We also found that we needed mechanisms for

grouping measurements. For example, the statistics that

we show above have measurements grouped by layer or

by orientation. This grouping was done in a post processing step. It would be very desirable to be able to

specify the groupings and to show group statistics during the immersive session.

While 3D manipulations and interactions were greatly facilitated by the immersive environment, control

functions such as specification of statistical analyses,

saving disk files, and so on were hampered by the

limitations of our interface. We were limited by the use

of a simple pointing device and standard 2D GUI-based

interfaces for such interactions. There were too many

choices and options to effectively present the user with

a full range of control.

Finally, it is worth considering the concept of presence and how it relates to our measurement tools.

“Presence is defined as the subjective experience of

being in one place or environment, even when one is

physically situated in another.” [31] Presence is important to us only insofar as it furthers our goals of perceiving structure and spatial relationships and as it

facilitates the use of our measurement tools. In the use

of our tools, there is a strong sense of direct interaction

with the 3D data representations. However breaks in

the sense of presence are not uncommon, but neither

are they troublesome. In any event, whether or not the

user experiences a subjective sense of presence, we

believe that the immersive visualization environment

provides the ability to interact with virtual objects and

tools much more effectively than would be possible

with a desktop system.

8. Future Work and Conclusions

We are planning to continue to enhance and expand

our set of measurement tools in a variety of ways. We

plan to add tools that enable the interactive measurement of additional quantities. For example, we will

need a tool for directly measuring angles (our current

tools only allow this indirectly). We also see a need for

tools that will measure the volume of regions of various

shapes and tools for measurement of surface characteristics such as curvature and area. Our current tools need

enhancements to improve their ease-of-use and accuracy. For example, we would like to have interactive

dragging of objects or points that is geometrically constrained. For example, one might want to constrain the

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dragging of a point to a horizontal plane. While using

the system we also often want the ability to place a

point precisely onto an existing surface (a snap-to

feature). We also wish to implement a mechanism for

moving elements very small amounts without depending on having a very steady hand (a tweak mode). As

described above, we also need mechanisms for hiding

and revealing the visual items created by tools in the

3D scene in order to reduce visual clutter.

A very interesting future direction for this work will

be the investigation of the interplay between manual

measurement methods, as described here, and automatic measurement tools. For example, looking at the

data for the Scaffold A samples, one could well imagine an algorithm for making an automatic fit of a cylinder to a strut, but will the automatic method produce

satisfactory results? If we have automatic methods that

produce mediocre results, we could implement a hybrid

approach where the automatic methods produce preliminary measurements that are then interactively adjusted

by the researcher in the immersive environment. The

virtual environment could also be used to show the

researcher the operation of automatic methods. For

example, iterative methods could be displayed with

time sequences of intermediate results.

One of the greatest problems to be addressed in this

work revolves around user interface. As we give

researchers more options for the analysis and display of

new measurements in the immersive environment, we

need to give them more ways of specifying those

options. Standard 2D GUI techniques like menus, buttons, and sliders are useful, but they will not do the

whole job. We need to provide users with the ability to

specify a very wide range of choices with control of

many parameters. This is a substantial challenge.

Because we have not performed formal user studies,

we cannot definitively say that our measurement

methods in the immersive environment are superior to

equivalent methods that might be implemented on a

desktop system. However we can say that these tools

have been effective in making useful measurements of

tissue engineering scaffold materials and that the

immersive experience seems to have substantially contributed to the effectiveness of the tools. We look

forward to performing usability studies in the future.

With these measurement tools and the means to

analyze the resulting data during the interactive

session, we are taking steps toward the implementation

of a virtual laboratory. In this virtual laboratory, we

can interact directly with data representations and

acquire new quantitative insight into experiments and

simulations.

Acknowlegements

We would like to thank Sheng Lin-Gibson and Forrest

A. Landis for providing the salt leached scaffold.

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About the authors: John Hagedorn is a mathematician in the Scientific Applications and Visualization

Group of the Mathematical and Computational

Sciences Division of the Information Technology

Laboratory at NIST. Joy Dunkers is a Physical Scientist

in the Biomaterials Group of the Polymers Division of

the Materials Science and Engineering Laboratory at

NIST. Steven Satterfield is a computer scientist in the

Scientific Applications and Visualization Group of the

Mathematical and Computational Sciences Division of

the Information Technology Laboratory at NIST. Adele

Peskin is a computer scientist in the Scientific Applications and Visualization Group of the Mathematical

and Computational Sciences Division of the

Information Technology Laboratory at NIST. John

Kelso is a mathematician in the Scientific Applications

and Visualization Group of the Mathematical and

Computational Sciences Division of the Information

Technology Laboratory at NIST. Judith Terrill is a

Computer Scientist, and the Leader of the Scientific

Applications and Visualization Group of the Mathematical and Computational Sciences Division of the

Information Technology Laboratory at NIST. The

National Institute of Standards and Technology is an

agency of the U.S. Department of Commerce.

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Journal of Research of the National Institute of Standards and Technology

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