IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN … · Addressing the Future of Clinical Information...

IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE, VOL. 11, NO. 2, MARCH 2007 127

Addressing the Future of Clinical InformationSystems—Web-Based Multilayer Visualization

Chueh-Loo Poh, Richard I. Kitney, and Rasu B. K. Shrestha

Abstract—This paper addresses some key issues relating to thedevelopment of new technology for clinical information systems(CIS) in relation to imaging and visualizing data. With the in-creasing importance of molecular and cellular biology, a new typeof medicine, molecular based medicine, is now developing. Thiswill significantly alter the way in which medicine is practiced.The view is presented that CIS will need to operate seamlesslyacross the Biological Continuum, i.e., the hierarchy of the humanorganism comprising systems, viscera, tissue, cells, proteins, andgenes. We propose a multilayered visualization interface, whichoperates across the Biological Continuum, based on Web-basedtechnology. A visualization interface package for two-dimensionaland three-dimensional image data at the visceral and cellular lev-els is described. Two application examples are presented: 1) MRknee images, at the visceral level and 2) endothelial nuclei images,acquired from confocal laser microscopy, at the cellular level.

Index Terms—Biomedical imaging, CIS, PACS, three-dimensional (3-D) visualization, Web-based.

I. INTRODUCTION

C LINICAL information systems (CIS) have developedrapidly over the last decade. Much of this development

has involved various imaging modalities, coupled to PACS. Theuniversal availability of information, including images, wave-forms, etc., will become increasingly important. This paper ad-dresses some of the important issues relating to the developmentof new technology for CIS. With the increasing importance ofmolecular and cellular biology, a new type of medicine, molec-ular based medicine, is now developing. This will significantlyalter the way in which medicine is practiced. The view willbe presented in this paper that future CIS will need to oper-ate seamlessly across the biological continuum (BC), i.e., thehierarchy of the human organism comprising systems, viscera,tissue, cells, proteins and genes.

A. Overview

The history of PACS is illustrated in Fig. 1. In the 1980s and1990s PACS was the domain of the scanner manufacturers; in the1990s, the film manufactures became involved, because of theshift away from film. From now and for the foreseeable future

Manuscript received June 25, 2005; revised October 11, 2005 and January 5,2006. This work was supported in part by the SIMILAR EU Network of Excel-lence. The work of C.-L. Poh was supported by an NTU Overseas Scholarship.

C.-L. Poh and R. I. Kitney are with the Department of Bioengineering, Im-perial College, London SW7 2BX, U.K. (e-mail: [email protected]).

R. B. K. Shrestha is with the Department of Radiology, University of South-ern California, USC Healthcare Consultation Center II, Los Angeles, CA 90033USA.

Color version of Figs. 2, 7, 8, 11, 12, and 13 are available online at http://ieeexplore.ieee.org

Digital Object Identifier 10.1109/TITB.2006.875680

(i.e., for the next one or two decades) the emphasis will be on in-formation integration and its universal data access. Increasingly,there will be less reliance on film. Future generations of PACSwill be based on system integration and software for fully Web-based systems as part of a CIS. Web-based infrastructures arenow being implemented. They allow the CIS (including PACS)to move from a department system to an enterprise wide system.The DICOM standard is the glue that makes open architectureCIS (including PACS) work. Consequently, DICOM is centralto the development of CIS.

The clinical trends described above will lead to a world inwhich imaging systems will be used routinely and directly, notjust in radiology, but across a range of clinical specialties (e.g.,cardiology, oncology, surgery, pathology, etc.). Image data ac-quisition already takes place in many of these specialties, butthe images are often only viewed on technology associated withthe acquisition device. A good example of this is the acquisitionand viewing of arthroscopy images. In many specialties, imag-ing is currently where radiology was in the 1980s, i.e., viewingon individual machines. This situation will significantly alterin the near future largely, both directly and indirectly, throughchanges in technology. These changes will allow universal ac-cess to data, images, waveforms, etc., across the enterprise (e.g.,the hospital) and beyond.

Four key components that make the universal image and dataaccess achievable are:

� price and power of computers—for example, Pentium com-puters have the processing power of the Unix workstationspreviously used for PACS at a fraction of the price;

� availability, use and price of industry standard hardware;this moves PACS from being based on specialist hardwareand operating systems to standard hardware and operatingsystems—with all the associated cost savings, which canbe achieved through economies of scale;

� presence of a comprehensive international standard forimaging (DICOM), together with other standards (e.g.,HL7 and Extensible Markup Language, XML);

� ability to provide fully Web-based CIS, including PACS;these systems use specialist application software that runson standard hardware and standard operating systems.

B. Clinical Needs

Clinical needs must be thought of in terms of different timescales.

1) Immediate Future: In the immediate future there willbe a need to provide much more universal Web-based accessto images, which have been traditionally associated withRadiology (e.g., magnetic resonance imaging (MRI), computed

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128 IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE, VOL. 11, NO. 2, MARCH 2007

Fig. 1. History of PACS and the associated standards.

tomography (CT), ultrasound, X-ray, angiography, etc.) acrossdifferent clinical specialties, within the enterprise (e.g., the hos-pital). However, there is also a rapidly developing need to pro-vide universal Web-based access to a wider range of images fromprocedures such as minimal access surgery (e.g., arthroscopyand laparoscopy); the recording of physiological waveforms(e.g., EKGs, blood pressure, heart rate variability, etc.); aswell as histological and hematological images. In addition,CIS will need to incorporate diagnostic photographic imagese.g., retinal images; dermatological images and more generalclinical photography. It is important to note that many of theseimage types are already defined within the DICOM standard.

2) Next 5–10 Years: Over this period the landscape ofmedicine is set to change radically. These changes are impor-tant because the CIS that will be installed in the future must beable to accommodate the changes in clinical practice, which arelikely to occur over this time frame and beyond.

Clinically, it is critical for these changes in the CIS to allowfor the seamless integration of molecular imaging, also calledthe next frontier of diagnostic imaging. Traditional imagingtechniques have probed the end results of disease processes; butwe are now at a stage where clinicians are being able to visualizeand identify the evolution of disease processes long before thesigns and symptoms of these processes become apparent byvisually observing the abnormalities and changes at the cellularand molecular levels. This will entirely transform the approachto clinical diagnosis from an imaging level, allowing detectionof pathologies at the “predisease” level.

February 2001 was an important date in the history ofmedicine. This was the date of the publication of the paperin Nature that reported the initial sequencing of the HumanGenome [1]. In practical terms this date represents the dawn ofthe “New Medicine,” i.e., molecular based medicine. From nowon there will be a rapidly developing trend away from a data poor

to a data rich health care environment; and a move away fromtreating clinically evident disease to diagnosis and treatmentbased on an understanding of the disease mechanisms. Both ofthese trends will have a profound effect upon the way in whichmedicine in practiced. There will be an increasing reliance onimaging across many medical specialties involving integratedcare.

Clinicians will be able to accurately pinpoint troublesomegenes and use imaging and associated molecular therapy as partof an overall strategy to treat existing as well as potential diseaseprocesses.

Central to these developments is the concept of the BC [2], [3],i.e., the hierarchy of the human organism comprising:

� systems;� viscera;� tissue;� cells;� proteins;� genes.Medicine today is often practiced at one or two of these levels,

i.e., there is generally little or no vertical integration across thelevels. This is set to radically change. The ability to image at allof these levels will become central to the practice of medicine.

Fig. 2 illustrates the overall schema for the type of CIS (basedon the BC model) which forms the conceptual basis of this paper.Referring to the figure, the left-hand side of the diagram showsthe visualization schema and the right-hand side the equivalentmodeling. The figure illustrates the layout for all the six levelsof the BC (i.e., level 1, system to level 6, gene; see key in the topright hand section of Fig. 2) and how they are linked. In practicethe user can choose, via the user input interface, which of thelevels they wish to address. All of the levels are linked to a com-mon database. (Later in the paper, we will present an exampleof how the schema of Fig. 2 is used at the visceral and cellular


POH et al.: FUTURE OF CIS—WEB-BASED MULTILAYER VISUALIZATION 129

Fig. 2. Multilayered visualization and modeling.

levels for visualization.) Another aspect of the concept illus-trated in Fig. 2 is that at many levels and in many instances, dataand images from the models can be compared with the equiva-lent patient data (as shown by the double headed arrows in thecenter of the diagram). Another important feature of the schemais that geometric integrity is preserved across the levels—eventhough different modalities are used for the data acquisition [4].

C. Scope of the Paper

In this paper, we will focus on some of the visualizationissues associated with our conceptual model (Fig. 2), i.e., wedo not address anything related to modeling studies. This is thesubject of a separate area of work. The concept is that at eachLevel relevant mathematical models (either produced by our

group or other workers) will be incorporated, as appropriate.This is being done by the use of Markup Languages (e.g., inthe case of cellular level—Level 4—by CellML [5]). As statedin the previous paragraph, this will enable direct comparisonbetween visualization and model results. In any area ofapplication typically there will be a wide range of data [bothtwo-dimensional (2-D) and three-dimensional (3-D)] acrossthe BC. Hence, there is a tremendous need to readily accessand view the full range of data. In this paper, we propose amultilayered visualization interface across the BC based onWeb-based technology to address this need—this is based onearlier work [6]–[10]. The aim is to develop common softwarevisualization interfaces that can be applied to all the levels of theBC, as shown in Fig. 3. (It is important to understand that at thisstage the software system that we describe is designed purely



Fig. 3. Visualization across all the levels of the BC based on a commonVisualization Package schema.

as a practical implementation of aspects of the CIS model—i.e.,we are, for example, not claiming that parts of our software arenecessarily state of the art or that we are in any way developingor describing a system specification.) A key to achieving thisaim is the use of DICOM standard as the image data format.Consequently, a standards converter (Fig. 3) is necessary toreformat data from various imaging modalities [e.g., electronmicroscopy (EM) and atomic force microscopy (AFM)] into toa standard format. The schema proposed in this paper (Fig. 5)relates to the processes after the standards converter (see Fig. 3).

Specifically, we describe the application of a common visu-alization package (VP)—see Fig. 5—to visualize data at thevisceral and cellular levels of the BC (Fig. 3). Our focus is onthe software processes and graphical user interfaces (GUI) thatwere developed to view 2-D and 3-D image data. Two exam-ple applications are presented: MR knee images—used in thediagnosis of osteoarthritis (OA) at the visceral level; and im-ages acquired from confocal microscopy—used in the study ofatherosclerosis at the cellular level.

D. Web-Based Visualization Interface Designs

Visualization and imaging at different levels of the BC, the useof Web-based information and communication technology, willbecome increasingly important in molecular based medicine. Inthe context of CIS, Web-based technologies (such as universalWeb browser technology and standard communication formats)should be used to access the full range of data across the BC.The use of Web-based technologies will allow clinicians to gainuniversal access to a patient’s data in real time anywhere in theEnterprise (e.g., the hospital) using PCs, MACs, etc. [7]. Theneed for a proprietary workstation can be overcome and, con-sequently, costs can be reduced. In this context by proprietaryworkstation, we mean special viewing workstations, i.e., fromscanner manufacturers. What we are proposing is the use ofspecialist viewing software based on standard hardware and op-erating systems. This technology can be implemented on boththe Internet and on Intranets.

An additional advantage of the Web-based approach is thatthe client software can be platform independent, as long as theWeb browser is supported. Hence, the system can be a fullyportable application, which can be used in different locationswith Internet connection. Standards are very important for thedevelopment of such applications, because they need to com-municate with each other to perform useful tasks. The use ofstandard Web-based content formats, such as Hypertext MarkupLanguage (HTML) and XML, will greatly facilitate communi-cation of such applications and the development of user inter-faces. The DICOM standard was created to aid the distributionand viewing of 2-D medical images, e.g., CT and MR scans,and ultrasound. The standard is central to the development ofPACS. In general, the DICOM image format is not currentlysupported by standard Web browsers. This poses a problem ifstandard Web browsers are used to view 2-D medical images.

E. Web-Based 3-D Visualization

With the advent of high-resolution 3-D imaging modalities,3-D visualization in biology and medicine has become possible.This extends across a wide range of scale—i.e., from individ-ual molecules (proteins/genes) and cells through the varietiesof tissue to complete organs and physiological system. 3-D vi-sualization is proving to be useful in a wide range of medicaland biological applications. 3-D imaging studies, such as postprocessed CT and MR studies, provide the primary source ofpatient-specific data for such applications. We would argue thatreal-time 3-D visualization and manipulation is necessary in or-der that clinicians can make full use of the information containedin medical image data. This is exemplified by the growing trendof using 16, 32, or 64 slice-CT scanners, which has resulted inhuge data sets for the same study protocol, with each study nowgrowing in size from a few dozen images to thousands of im-ages. 3-D visualization is now a necessity to even comprehendthese growing data sets.

A range of visualization software for medical images alreadyexists. These software packages can be roughly divided into twocategories. Category A comprises packages that generally runon standalone workstations. Category B comprises Web-basedsoftware packages that have been developed for specializedapplications.

1) Category A—3-D Visualization Software Packages:Some of the 3-D visualization software packages, under this cat-egory are: ANALYZE [11]; Open Source 3-D Slicer [12]; Julius[13]; OsiriX [14] and Advanced Visual Systems (AVS) [15].These systems generally allow 2-D to 3-D reconstruction, 3-Dvisualization, and quantitative analysis of various medical scans.They also provide: extensive functionality—such as interactiveorthogonal and oblique sectioning of 3-D models [11], [12];support both medical and biological multidimensional imageformats, e.g., in ANALYZE [11]; and a single portable and ex-tendable environment for image-guided medicine, e.g., in 3-DSlicer [12]. There also exist open source visualization and im-age processing toolkits such as Visualization Toolkit (VTK) [16]and Insight Segmentation and Registration Toolkit (ITK) [17].These toolkits have been widely used in the development of



medical software programs, e.g., 3-D Slicer, Julius and OsiriX.These visualization systems have been used in various medicalapplications. They generally run on standalone workstations.

2) Category B—Web-Based Visualization Systems: Re-cently, a number of Web-based visualization systems and ap-plications, using application programming interfaces (APIs),have been reported in the literature. These include Virtual Real-ity Modeling Markup Language (VRML)/Extensible 3-D (X3-D) [18], Java3-D [19] and programming languages—such asJava [20]—to utilize the capabilities of high speed networks;an Internet-based system for simulation-based medical plan-ning for cardiovascular disease—which utilizes Java and VRML[18]; a medical visualization system for medical diagnosis us-ing Java3-D [19]; and the anatomy browser of surgical planninglaboratory (SPL), using Java applets [20], which combines 3-Dsurface models of anatomical structures, their cross-sectionalslices and textual descriptions of their structures.

There are a number of important differences between ourapproach and the software listed above under categories A andB. Our approach is fully Web-based; i.e., it aligns with categoryB software that allows much wider access to the data images,etc.—often across the enterprise. However, there are a number ofdifferences between our software and the other packages listedunder category B.

1) Our software is designed for the implementation of theschema illustrated in Fig. 2—i.e., to allow the display,storage and integration of a range of images into a commonframework.

2) Our software is specifically designed to match the conceptof the BC; i.e., to deal with data from different imagingmodalities and different levels of the BC—while preserv-ing geometric integrity [4].

3) Our software is designed to be compatible with existingPACS systems.

4) Although we are not addressing modeling in this paper,our software is also designed to interface with modelingsoftware and associated data at different levels of the BC—for example, such packages as CellML [5].

In Web-based 3-D visualization applications, there is, typi-cally, no access to large-scale computing environments. Newtechniques have to be developed to achieve a reduction in thecomputational expense of the 3-D reconstruction process; aswell as the number of generated primitives to be viewed onpersonal computers [21]. Surface rendering and volume ren-dering are two classes of 3-D reconstruction techniques thatare commonly used. Web-based 3-D visualization applications,based on surface rendering techniques [21], [22], have been de-scribed. Surface rendering, however, normally requires an ex-tensive amount of preprocessing. In addition, the quality of thefinal visualized model is limited by the accuracy of the segmen-tation process. Due to the high resolution of the volume data,this usually results in a large number of polygons [21].

Volume rendering is a more general rendering method. It canmimic surface rendering (but not vice versa) [23]. The mainadvantage of volume rendering is its ability to preserve theintegrity of the original data throughout the visualization pro-cess [24]. However, the method requires much larger amounts

of computational time than surface rendering. Recently, therehas been progress toward Web-based visualization using volumerendering, but, to date, there are only a few reported implemen-tations [25], [26].

As a result of these considerations, and because the currentprimary objective for our 3-D visualization is to display andmanipulate data at various levels of the BC, we have, for themoment, implemented only surface rendering. This providesthe speed of image manipulation that we require. However, weare currently working on 3-D volume rendering methods, whichwill be integrated into our system in the future.

The GUI is important in the diagnostic process when the clini-cian is visualizing 3-D anatomic structures. It is often difficult torelate the 3-D model to the original 2-D images. Hence, if abnor-malities are identified in the 3-D model, it is frequently difficultto accurately identify them in the 2-D images acquired on thescanner. One approach to overcoming this problem is to displaythe original 2-D images and the 3-D model on the same interfacewith their geometric relationships maintained [11], [12]. Theseuser interfaces are, however, standalone—i.e., not Web-based.

II. MATERIALS AND METHODS

This section describes the design of a multilayered visualiza-tion schema and the approach that we have taken in relation tothe development of the interfaces. The design of the visualiza-tion package is described in the second section; this is followedby a description of the development of various software pro-cesses.

A. Overview of Multilayered Visualization Schema

The design of a multilayered visualization schema for theBC is shown in Fig. 4. The system comprises three functionalsections: Section A, user input and display; Section B, visual-ization packages; and Section C, databases. Referring to Fig. 4,for convenience, only two example levels of the six levels of theBC are shown at Section B.

1) Section A: This section of the overall system comprisesthe user interface and display that is used for all six-levels ofthe BC. Web-based technology was used in the developmentof the user interface for viewing 2-D images and 3-D models.The interface captures user inputs; for example, the user cannavigate and select the image dataset of interest through view-ing a series of image thumbnails on a standard Web browser.After selecting the image dataset, images are retrieved from thedatabase for viewing. Backend processes, e.g., 3-D reconstruc-tion, are carried out on the server and the generated 3-D modelsare viewed on the client.

The user interface is designed to be interactive and intuitive.The interface allows the user to view 3-D models and 2-D im-ages, (still and moving). An important feature of the interfaceis its ability to present quantitative information. For example,this may relate to the anatomical properties of tissue and tissuefunction in health and disease. An illustrative example, whichwill be described later in this paper, is the use of the interface tostudy cartilage thickness changes in OA [27]–[33].



Fig. 4. Schema of multilayered visualization. At section B only two-levels of the BC are shown (i.e., visceral and tissue) in the diagram, for convenience.

2) Section B: This section comprises the VPs for each layerof the BC. Once the image data have been acquired, their manip-ulation, in terms of 2-D images and the creation of 3-D models(i.e., visualization, rendering), uses virtually the same approachfor all levels of the BC. Consequently, the VPs comprise com-mon software and processes. For example, 3-D surface and vol-ume reconstruction techniques that can be applied to images ob-tained from different imaging modalities. It is important to notethat standards, e.g., DICOM, are key to making this approachpossible. The main difference between the VPs for differentlevels of the BC is likely to lie in the segmentation processesapplied to images acquired using different modalities. TheseVPs will, in the future (during further development stages of oursystem), be linked through an automatic interface that will allowseamless navigation from one VP to another and incorporatingother types of data (e.g., physiological waveforms, movies, andsounds). The developments for other types of data will base ona similar framework that we have implemented for images.

3) Section C: This section comprises the interface from theVPs to database. This involves storing and retrieving imagedatasets from the database using Structured Query Language(SQL) commands. The data retrieved are/will be processed bythe appropriate VP. Although the focus in this paper is on imag-ing and visualization, it should be noted that the database mayinclude other patient related diagnostic data—such as blood testresults and physiological waveforms (e.g., ECGs). These datamay well be related to the EPR aspects of a CIS, but a discussionof this topic is beyond the scope of this paper.

B. Visualization Package Schema

The detailed schema of a VP is illustrated in Fig. 5. The VPcomprises viewing interfaces for both 2-D images and 3-D mod-els using a Web browser on the client: Segmentation, 3-D recon-struction, and 3-D slicing are carried out on the server. Hence,the general approach is for computationally intensive processes

Fig. 5. Schema of a visualization package.

to be carried in the server. The main advantage of such architec-ture is that the server can carry out the computationally demand-ing processes and download the results back to the client. Thus,a user with a standard desktop computer can utilize the power ofa much more powerful computer and view the results locally.

Referring to Fig. 5, users navigate and select image datasetsby viewing a set of image thumbnails in the Web browser. Si-multaneously, any important parameters that are required bythe visualization processes can be specified. Users may chooseto view 2-D images or 3-D models. At this point selected im-age datasets are retrieved from the database and, if appropriate,passed through a segmentation process. Two classes of 3-D re-construction techniques are commonly used: surface renderingand volume rendering [24]. For surface rendering, segmentationis essential to identify the structure of interest within biomedicalimage, particularly in the case of MR images. (For CT images thetissue boundaries are much clearer; hence, segmentation is usu-ally unnecessary.) Therefore, a segmentation process is included



in the schema: ideally, this should be fully automatic. However,in practice automatic segmentation has proved to be very dif-ficult, particularly for pathological data [28]. Semi-automaticapproaches that require a certain degree of user interventionhave been found to be much more reliable [28]–[30], providedthat the voxel size is properly defined (i.e., resolution). Our semi-automatic segmentation is based on edge detection using a radiisearch approach, designed to segment articular cartilage fromMR knee images [33]. Volume rendering is a more reliable tech-nique and segmentation is not required. The main advantage ofvolume rendering is its ability to preserve the integrity of theoriginal data throughout the visualization process. However, thisoften requires large amounts of computation time compared tosurface rendering. Hence, surface rendering is used in our cur-rent implementation. Surface rendering provides a well-defined3-D surface model of anatomical structures. In our interface thesurface rendered model is displayed, together with 2-D images.The model gives the 3-D perspective of the structure of interestand the 2-D images provide the overall view with respect to therest of the tissue in the volume.

In client/server architecture, following the 3-D reconstructionprocess a file that describes the 3-D scene graph must be down-loaded to the client for viewing. Web-based technology has nowdeveloped to the point where 3-D visualization is practicable.HTML has wide acceptance. It is, however, normally a 2-D con-tent format and provides only limited resources for supportinginteractive 3-D graphics over the web. VRML was developed toaddress these difficulties.

VRML is the ISO standard for transmitting 3-D content overthe web [34]. It supports various multimedia data types (e.g., au-dio, image, video) and integrates with web scripting languages,e.g., JavaScript. A VRML scene graph can be viewed fromWeb browsers, e.g., Internet Explorer (IE) by using a third partyVRML plug-in. Recently, X3-D, which is the new developmentof VRML, has been adopted by the Moving Picture ExpertsGroup (MPEG) to bring interactive 3-D graphics to the MPEG-4 multimedia standard [35]. It has added features, e.g., 3-Dtexture mapping and a number of different file formats avail-able; including XML. Consequently, the VRML/X3-D standardwas chosen as the file format for our system to ensure smoothcommunication with various applications. The reconstructionprogram was written in C++ using objects from VTK [16] for3-D processing. At the end of the process, VRML files are ex-ported and downloaded through the network to the client forviewing. The volume data are visualized through MultiPlanarReformatting (MPR)—i.e., 3-D Slicing. As it is often difficultto relate 3-D models to the original 2-D images, images from or-thogonal planes can be reformatted and displayed, together withthe 3-D models, to facilitate the visualization process. This 3-Dslicing process, based on MPR, was implemented within the re-construction program. Original DICOM images were the inputto the program. Current VRML plug-ins only support standardmedia formats and do not support DICOM format. As a result,reformatted images from orthogonal planes (i.e., sagittal, axial,and coronal) were generated using the JPEG format.

Using the interface on the client, users can view 2-D DICOMimages and the associated 3-D model downloaded from the

Fig. 6. (a) A typical sagittal slice image from a normal volunteer, showingthick articular cartilage. (b) A sagittal slice image from a patient with OA,showing reduced cartilage thickness.

server to the Web browser. The user can then manipulate the 3-Dmodel using geometric maneuvers—such as translation, zoom-ing and rotation. Furthermore, 2-D images can be displayedwithin the same 3-D scene for re-slicing back into 2-D—i.e.,the system supports nonorthogonal 2-D slicing/viewing. Cur-rently, most Web-based interfaces do not support the viewingof DICOM images. Hence, a Java applet was written to decodeand display DICOM images. Therefore, in our 2-D viewer theuser can view full resolution medical images and perform basictasks associated with DICOM images, in relation to PACS—windowing and leveling, etc.

C. Examples

The functionality of the system will now be demonstrated bymeans of two examples, the first at the visceral level and thesecond at the cellular level.

1) Visceral Level: OA can be described as the degradationand loss of articular cartilage. Because of its excellent soft tissuecontrast, MRI is becoming increasingly clinically important inthe assessment of OA. For the purposes of the example, weselected two sets of MR knee images in DICOM format. Thefirst set consists of 56 sagittal slices from a normal volunteer.Each slice has a matrix size of 256× 256 with a slice thickness of1.5 mm. The second dataset comprises of 23 sagittal slices froma patient with OA—each slice has a matrix size of 512× 512,with a slice thickness of 3 mm. Fig. 6 shows two representativeMR knee images from the datasets used in our study.

2) Cellular Level: Confocal microscopy is used to imageendothelial cells of arterial wall for the study of Atherosclerosis[36]. We used two sets of images showing the endothelial cellsof the thoracic aorta wall of a mouse as illustrated in Fig. 7.The images were acquired by confocal microscope and storedin TIFF format. Each set consists of 40 image slices and eachslice has a matrix size of 2048× 2048, with a slice thickness of1.5 µm.

D. Thumbnail Selection

We have developed an image thumbnail selection user inter-face. With the interface, the user can select the images related toa particular study of the patient via the Web browser. The imagethumbnails are displayed using scalar vector graphics (SVG)format. As a result, it is possible to zoom in or to enlarge theimage thumbnails during the selection process [see Fig. 8(a)].



Fig. 7. Sample image showing (a) autofluorescence of the arterial wall and(b) endothelial nuclei (in red) at the same spatial location.

The image data related to a particular study of the patient arelisted as hyperlinks on the bottom left frame of the interface. Inaddition, the representative thumbnails of the data are displayedin frame on the far right.

E. Preprocessing

1) Visceral Level: MR images were segmented prior to3-D reconstruction. Femur, tibia and the femoral cartilage weresegmented from the volume dataset and saved as three separateset of images. The segmented images were saved in DICOMformat. These structures were segmented and saved separatelyso that the individual 3-D model could be manipulated afterreconstruction. Under DICOM the hierarchy is Study, Series,Images. In this context, the three data files (i.e., femur, tibia,and the femoral cartilage) will be stored and linked under theheading of the original 2-D images.

2) Cellular Level: A region of interest (ROI) of size512× 512 was defined in one image. This was then saved asa separate image in grayscale DICOM format. The same pro-cedure was performed automatically for all the 80 images. Asa result, 80 images (i.e., 40 images from the autofluorescencedataset and 40 from the endothelial nuclei dataset) were pro-duced; these were subsequently used for 3-D reconstruction.

F. 3-D Reconstruction

Our 3-D reconstruction program generates a surface modelfrom segmented image data. The program was written in C++using VTK for processing. We have implemented a data-processing pipeline using VTK objects. In this approach, allthe data are read and a pixel threshold is defined to select therequired structure for reconstruction. Subsequently, the volumedata are smoothed to reduce step-like artifacts in the model.The volume is then processed using a marching-cubes algo-rithm [37]. This process produces triangles within the voxelsthat contain the surface. While marching cubes can produce avery accurate surface model, the method does so by generating alarge number of polygons (to capture the details of the surface).To prevent the model becoming too large for the client to render,polygon-decimation implementation, provided with VTK, wasused to reduce the number of triangles. The last stage in thepipeline exports the scene to files in VRML format. These are

then downloaded to the client and rendered in a standard Webbrowser using a VRML plug-in.

G. VRML 3-D Slicing

A VRML 3-D slicing interface was developed by our groupto allow orthogonal 2-D images to be displayed with the 3-Dmodels. A Web-based approach was adopted. As described ear-lier, VRML is normally used for visualizing 3-D models. Themain reason for this is that VRML is already the standard fortransmitting 3-D content on the Internet. The VRML 3-D slicingprogram is divided into two main parts: 1) a backend programto produce images from the three orthogonal planes and 2) aVRML scene graph to visualize the images in the 3-D scene.The first part of the program (written in C++) uses VTK ob-jects to generate 2-D images from the volume. The programwas integrated with the 3-D reconstruction program. In a sim-ilar manner to the reconstruction program, a data processingpipeline was set up as shown in Fig. 9. Referring to the figure,in the pipeline DICOM image data are first stored as a volume.Three orthogonal planes are then defined (i.e., Planes 1–3). Formedical images, the planes are referred to as the Coronal, Sagit-tal and Axial planes, respectively. Slicing along the three-planesis carried out by using the vtkImageReslice object provided byVTK. 2-D images are created by assigning values to each 2-Dpixel in the plane by interpolating the voxels of the volume datawhere they are intersected by the plane. The resulting pixels areinterpolated using cubic interpolation. A series of 2-D images,in JPEG format (using the VTK JPEG export function) are gen-erated for each plane. (The JPEG format was chosen becauseDICOM image format is not currently supported by a VRMLplug-in.) Two sets of images are stored, 2-D lossy JPEG im-ages and DICOM images. The JPEG images are stacked in theform of a 3-D model under VRML. This stack can be rotatedand orthogonally sliced as if it were a full 3-D model. Thisis geometrically linked to three orthogonal views (i.e., the fullresolution DICOM images) (see Fig. 11).

A VRML scene graph was written to allow the JPEG imagesto be displayed in the 3-D scene and manipulated for the pur-poses of viewing. A bounding box is defined, based on the sizeof the 3-D model, so that the images can be synchronized withthe model. The purpose of the bounding box is to define the3-D space that the voxels of the volume data occupy. Three or-thogonal planes were created using the VRML dragging sensor(i.e., PlaneSensor). This allows the planes to be dragged with apointing device (here, a mouse). The planes are restricted withinthe bounding box. Based on the coordinates of the mouse po-sition, when a plane is dragged the new location of the planeis calculated and updated. Each set of 2-D images are derivedfrom one orthogonal plane. Hence, the slicing plane movementis restricted to only one axis and bounded by the bounding box.The coronal plane is only allowed to slide in the anterior andposterior directions within the bounding box limits.

The images are then mapped to the planes using the VRMLtexture mapping feature and inline function. Based on the po-sition of the plane, the images are updated. An array of texturelinks is stored for each plane. By calculating the array number,



Fig. 8. Sample screenshots of user interface for selection of images using image thumbnails. (a) Screenshot showing the MR knee images thumbnails.(b) Screenshot showing the related set of histology images of the cartilage.

using the new position of the plane, the respective image textureis updated. In addition, the slice number is displayed to providea reference for the user in relation to the 2-D images in theviewer. Finally, the slice number for each plane is updated bymeans of the same calculation as used for the texture updating.

H. 2-D DICOM Viewer

It is important that the client application is portable so thatit can be used on different platforms. The Java programming

language was chosen for the viewer because of its portability.The result is a viewer that can display 2-D DICOM images ona Web browser. In addition, Java provides a set of image pro-cessing classes that can be used to manipulate 2-D images. Theapplet for this viewer was developed for a PC using NetBeanIDE (Integrated Development Environment) version 3.6. It uti-lizes the standard AWT (abstract window toolkit) and API, aswell as custom classes developed by our group for the project. Itreads the standard DICOM images that reside on the server and



Fig. 9. Pipeline of VRML 3-D Slicing. The DICOM image data are either original or following standards conversion (see Fig. 3).

renders the images on the client. The Java applet is embedded inthe Web browser. This enables DICOM images to be decodedand displayed. Three applet viewers are embedded into threeseparate frames and placed below the 3-D viewer. The framedisplays DICOM images from the axial, sagittal and coronalplanes, respectively.

Different brightness and contrast values are used in clinicalpractice to view different types of tissue, e.g., bone and softtissue. Hence, windowing and leveling (i.e., changing the con-trast and brightness of an image) is an important feature of anyDICOM viewer. The viewer allows the gray levels of the imageto be displayed on the monitor. These can be changed by drag-ging the mouse in the image window—i.e., dragging the mousein the vertical direction controls the window value; whereas,movement in the horizontal direction changes the level. Themouse position co-ordinates are displayed. These are updatedwhen the user moves the mouse pointer over the image. Thisoperation allows the user to note points of interest on the image.In addition, the window and level values and the name of theimage are displayed.

III. RESULTS

The user interface developed in the project allows the user toview both 2-D images and 3-D models. Standard HTML wasused to create the layout of the viewing interface. In the standardlayout, a large 3-D view is created, together with three 2-Dimages from the three orthogonal planes. The GUI is viewedon a Java enabled Web browser, i.e., Internet Explorer, witha third party VRML plug-in, i.e., Cortona, on a standard PC.Most VRML plug-ins take advantage of client-side graphics

Fig. 10. Two rendered scenes from 3-D slicing displaying images from threeorthogonal planes. (a) MR knee volume images from a normal volunteer.(b) MR knee volume images from a patient with OA.



Fig. 11. Viewing interface with a 3-D window showing the surface ren-dered 3-D models aligned with images from VRML 3-D slicing and threewindows displaying MR images from the three orthogonal planes. (a) Kneedata from the volunteer with normal knee. (b) Knee data from a patient withOA.

hardware, if present. This helps to tackle the server-load problemand the interaction lag time.

A. Visceral Level—Knee Osteoarthritis

As previously described, users can visualize volume datathrough 3-D slicing in Web browser. Fig. 10(a) shows a ren-dered scene of the 3-D slicing performed on MR knee imagesfrom a normal volunteer. Fig. 10(b) shows images from a pa-tient with OA. Two datasets were used in the example. The firstdataset comprised 40 images (slices). The 40 slices were cho-sen from the overall dataset because they showed the cartilage.Similarly, 16 images for the OA dataset were used.

For the data from the normal volunteer, three separate VRMLfiles were generated by the 3-D reconstruction program fromthe three sets of segmented DICOM images (i.e., femur, tibia,and femoral cartilage). The three separate models (the femur,tibia, and femoral cartilage) were combined into a commonscene graph, together with VRML 3-D slicing. This is shownin Fig. 11. For the data from the patient with OA, two separateVRML files were generated from two sets of segmented DICOMimages, i.e., femur and tibia. This allows the flexibility of adding

Fig. 12. (a) 3-D slicing of confocal microscopy images of the arterial wall.(b) 3-D slicing of confocal microscopy images of the endothelial nucleiin red.

Fig. 13. Viewing interface. The top 3-D window shows the surface of thearterial wall and the endothelial nuclei (in red). The bottom three windowsdisplay the images from the three orthogonal planes.

and removing any model from the 3-D scene. Hence, the usercan view and examine the femoral cartilage separately from anyangle, without the femur or tibia. The images are updated basedon the position of the planes. Functions such as zooming and ro-tation can be performed interactively. It is important to note that,as the images in the 3-D scene are in lossy JPEG format, the userneeds to study full resolution 2-D DICOM images to confirm ob-servations from the 3-D scene. The slice number of each imageis displayed so that the user can refer to the DICOM images inthe 2-D viewer simultaneously. Windowing and leveling adjust-ment was achieved by dragging the mouse over the 2-D images.The Java applet is geometrically synchronized with the 3-Dviewer.

In many clinical applications, the ability to view geometri-cally linked 2-D and 3-D images is of considerable benefit todiagnosis. The significance of Figs. 10 and 11 is that we pro-vide this functionality in a Web-based interface, allowing forsignificant benefits in clinical correlation of the 2-D images tothe advanced findings in the 3-D reconstructions, even whenviewing the studies over a Web browser at the clinics or the out-patient department. This takes the clinical benefits of advanced



integrated 2-D and 3-D imaging outside of the reading room tothe point of care in the clinics.

B. Cellular Level—Atherosclerosis

Furthering the clinical benefits of having all of the patient’sclinical and imaging datasets at the physician’s fingertips, oursystem allows for the seamless integration of the imaging at thevisceral level described above down to the cellular level at criti-cal regions of clinical interest. In this example the user was ableto visualize volume data acquired from confocal microscopethrough 3-D slicing. Fig. 12 shows two rendered scenes of the3-D slicing showing the images of the aorta arterial wall andendothelial nuclei. Three orthogonal planes are displayed in the3-D scene and each plane can be dragged individually. Hence,it is possible to view and examine the surface contour of thearterial wall. This allows the location of the endothelial cells tobe identified.

Two separate VRML files were generated from the two setsof converted DICOM images—i.e., the surface of the arterialwall and endothelia nuclei. The images obtained from Plane 1were used for the 3-D reconstruction of the surface of the arterialwall. The two separate models were combined into a commonscene graph, together with images from the orthogonal planes(this is shown in Fig. 13). Referring to the Fig. 13, the locationand shape of the endothelial nuclei can be observed with respectto the surface of the arterial wall. The example illustrates thatwith the viewing interface it is possible to navigate within the3-D scene to examine the endothelial nuclei spatial distribution.In addition, the user can observe the structure of the nuclei—and, particularly, cells that are not perpendicular to the confocalacquisition plane. This allows more accurate measurements tobe performed.

IV. DISCUSSION

In this paper we describe a Web-based multilayered visual-ization interface to view data from multimodalities across theBC. Data from the visceral and cellular level, i.e., MR kneeimages for OA and images acquired from confocal microscopyfor the study of atherosclerosis were successfully visualized.

As VRML and Java were used to create the user interface, theonly software requirement for the user is a Java/VRML capableWeb browser. The advantage of this design is that it can beported to different Web browsers easily as standard Web-basedtechnologies such as HTML, Javascript and VRML were used.Furthermore, in a Web-based architecture, the client does notneed to perform extensive computation. Hence, the client needonly be standard PC.

We have developed the viewing interfaces for 2-D and 3-Dimage data, segmentation [33], 3-D reconstruction and 3-D slic-ing programs. For the viewing interfaces, we have written theVRML scene graphs that make it possible to slide orthogonalimage planes within a 3-D volume using a mouse. An appletDICOM viewer to display DICOM images has also been devel-oped as part of our viewing interfaces. Our 3-D reconstructionand 3-D slicing programs have been implemented using objectsfrom VTK to produce the VRML 3-D model and images re-

quired. The system has been tested using the image data fromthe two examples that are presented.

The 3-D reconstruction process can be either surface or vol-ume rendering. This process should remain common for differ-ent VPs. The reconstruction technique in our implemented ver-sion was based on surface rendering. It is supported by VRMLand is less computationally expensive than volume rendering.The surface rendered models are visualized interactively onstandard PCs. The next step will involve creating a 3-D vol-ume model. However, VRML generally only supports surfacerepresentation. A few studies have been reported in the litera-ture, which describe ways for VRML to support volume ren-dering [25], [26]. The added feature in X3-D, i.e., 3-D texturemapping may allow Web-based volume rendering.

The Java programming language is designed to work on avariety of hardware without recompilation and with high reli-ability. These qualities facilitate the creation of Internet and/ornetwork-based applications. Any machine that has a Java com-patible Web browser can be used to view the applet, regardlessof the operating system. This guarantees that the most currentversion of the system is being used and eliminates the need toinstall software on a client computer. The 2-D DICOM Javaapplet was developed by our group to allow viewing of DI-COM images using a Web browser. The version of 2-D viewerwhich was used for examples in this paper has a limited setof 2-D image viewing tools—additional tools can be easilyimplemented.

The layout of the interface is somewhat similar to that of3-D Slicer [12]. However, our layout allows user to easily com-pare the 2-D images and the 3-D rendered scene. 3-D Sliceris a software package that was primarily designed for image-guided medicine. Our implementation takes a fully Web-basedapproach. This has the major advantage of allowing universalaccess to and visualization of a wide range of patient data acrossthe BC (i.e., at multiple levels). An additional advantage is thatthe client workstation can be platform independent, as long asthe Java compliant Web browser is supported.

Image datasets from two levels of the BC, i.e., visceral andcellular level were successfully visualized. One of the mainobjectives is that the interface developed can be applied to allthe levels of the BC. Data from different imaging modalities forthe rest of the levels are needed to further develop the interfaceso that it can be used across the BC.

An important aspect of the multilayer visualization is to al-low user to navigate from one layer to another seamlessly. Ad-ditional work is required to create the interface between VPsfrom different levels of the BC as shown in Fig. 2. The interfaceallows user to navigate from one level to the other—i.e., in theexample, zooming from the organ level to the tissue level andvice versa. With the increasing number of data types that willbe brought into CISs in the future, a Web-based user interface,which allows clinicians to find and navigate through data withease, will be important to aid the clinical process. This interfacedesign should be as generic as possible, so that it can be usedfor various VPs. This will provide clinicians with the ability tomove seamlessly through the different levels of the BC, whilemaintaining geometric integrity.



The overall aim is that future CIS development should notonly cover the various levels of the BC from an imaging stand-point, but, also, incorporate modeling techniques (e.g., physi-ological systems and systems biology models; as well as, e.g.,3-D models of proteins), as illustrated in Fig. 2. The use ofmodel to compare predicted results with actual results will, webelieve, be an important feature of future clinical informationsystems.

In summary, we believe that more advanced CISs are likely tobe based on the schema illustrated in Fig. 2. The concept of theBC means that clinicians and healthcare systems will be able touse a much broader range of data and information from a singlepoint of access.

ACKNOWLEDGMENT

The authors would like to thank Dr. P. Weinberg and A. Bondfor providing the cellular images used in our study.

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Chueh-Loo Poh was born in Singapore in 1976.He received the B.Eng. degree (first class honors) inelectrical and electronics engineering from NanyangTechnological University (NTU), Singapore, in 2001.Currently, he is working toward the Ph.D. degree inbioengineering with an emphasis on medical imagevisualization in the Department of Bioengineering,Imperial College, London, U.K.

He was an Information Technology (IT) Analystwith Accenture Pte Ltd, specializing in IT consult-ing, until the middle of 2003. He received an NTU

overseas scholarship in 2003.

Richard I. Kitney received the Ph.D. degree fromImperial College, London, U.K., and the D.Sc. de-gree from the University of London, London, U.K.,in 1972 and 1993, respectively, both in electrical en-gineering.

He is currently a Professor of Biomedical Sys-tems Engineering and the Head of the BiomedicalInformation Technology Group, Department of Bio-engineering, Imperial College. During 1991–2001,he was the Founding Head of the Department of Bio-Engineering, Imperial College, and is currently the

Dean of the Faculty of Engineering, Imperial College. Since 1991, he has been aVisiting Professor at Massachusetts Institute of Technology (MIT), Cambridge,and is the Codirector of the Imperial College-MIT International Consortiumfor Medical Information Technology. He has authored over 300 papers in thefields of biomedical signal and image processing, medical informatics, and theapplication of computers to healthcare.

Dr. Kitney was appointed a Fellow of The Royal Academy of Engineering(FREng) in 1999 and is the Chairman of Academy’s UK Focus for BioEngi-neering. He was awarded The Order of the British Empire (OBE) in the Queen’sBirthday Honors List for services to information technology in health carein June 2001. He was appointed a Fellow of the International Academy ofBioMedical Engineering (IAMBE) (this is the highest honor bestowed by theInternational Federation of BioMedical Engineering Societies) in 2003. He wasrecently elected a Fellow of the American Institute of Medical and BiologicalEngineering (AIMBE).

Rasu B. K. Shrestha was born in Banepa, Nepal, in1973. He received the graduate degree in medicinewith a full Colombo Plan Scholarship from LLRMMedical College, CCS University, Meerut, India,in 1997.

He practiced internal medicine and worked to-ward radiology. He was a Resident Doctor in InternalMedicine at the Ram Manohar Lohia Hospital, NewDelhi, India, after completing the Internship. He wasthen a Resident Doctor in Radiology at the RIPASHospital, Bandar Seri Begawan, Brunei. Soon after

that, he joined the University of Southern California, Los Angeles, as a ClinicalResearch Fellow, where he is currently the Radiology Informatics Director. Hisresearch interests include the advancement of radiology and medical informat-ics, and the optimization of clinical workflow using informatics.

Dr. Shrestha has been a Member of the Radiological Society of North America(RSNA) since 2001, and has presented numerous papers at the annual congressin Chicago, where he has been recognized with various awards through theyears. He also received the Roger Bauman Best Scientific Paper Award at theSociety for Computer Applications in Radiology (SCAR) Conference in Van-couver, BC, Canada, in 2004.


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