A Veterinary Digital Anatomical Database James R. Snell, DVM, MSt, Ron Green, DVM, MSt George Stott, DVM, PhDt, Susan Van Baerle, BS, MA'
tDepartment of Veterinary Anatomy and Public Health 'Department of Large Animal Medicine and Surgery Vepartment of Architecture - Visualization Lab Texas A&M University The objectives of the Veterinary Digital Anatomical Database Project are:
Abstract
This paper describes the Veterinary Digital Anatomical Database Project. The purpose of the project is to investigate the construction and use of digitally stored anatomical models. We will be discussing the overall project goals and the results to date. Digital anatomical models are 3 dimensional, solid model representations of normal anatomy. The digital representations are electronically stored and can be manipulated and displayed on a computer A digital database of graphics workstation. anatomical structures can be used in conjunction with gross dissection in teaching normal anatomy to first year students in the professional curriculum. The computer model gives students the opportunity to "discover" relationships between anatomical structures that may have been destroyed or may not be obvious in the gross dissection. By using a digital database, the student will have the ability to view and manipulate anatomical structures in ways that are not available through interactive video disk (IVD). IVD constrains the student to preselected views and sections stored on the disk.
Introduction Anatomical knowledge is fundamental to solving problems in biomedical research, education, and patient care. Based on the concept of Structural formatics[l], anatomical knowledge can be clasified into two components: spatal and symbolic. Spatial knowledge deals with geometrical attributes of biological objects, such as their shape, size, volume and the 3 dimensional (3-D) inter-relationships. Symbolic knowledge deals with the non-spatial attributes and relationships of biological objects, such as their functional, developmental, hierarchical, and taxonomic relationships. The purpose of Structural Inforatics is to apply both spatial and symbolic knowledge to solve problems in biomedical research, education, and patient management. This project focuses on developing the techniques for building the spatial component of anatomical knowledge. 0195-4210/91/$5.00 C) 1992 AMIA, Inc.
762
*
Refme the techniques required to obtain digital, 3-D coordinates of selected anatomical structures of the canine foreleg. These techniques can then be applied to other anatomical strucures.
*
Utilize the collected 3-D coordinates to construct a volumetric rendering of the selected
anatomical structures. Volumetric rendering allows for random sectioning through structures without the loss of any anatomic information. *
Test the usefulness of digital anatomical structres in leaming normal anatomy.
Materials and Methods The canine forelimb was chosen as the first anatomical structure to be studied. The forelimb provides representative tissue densities for skin, muscle, fat, and bone. The project consists of two The first element involves the components. collection of data to be used to construct 3-D, volumetric models of anatomic strucres. Database Collection and Construction Two methods of collecting 3-D data are proposed. We are currently investigating the use of X-ray computerized tomography (CT) to collect serial slices of the structure under study. The data in each slice is comprised of a two-dimensional array of values. These values represent density information. The 2 dimensional (2-D) slices are then combined to produce a 3-D model (Figure 1). Once the slices have been combined into a volume, the resulting data is referred to as voxel data. A voxel is a volume element - a value that has a x,y,z location within the volume. The voxel is the 3-D equivalent of a pixel. The CT data is collected with a Technicare Deltscan 2010 CT scan machine. The Deltascan 2010 produces a 2-D image that has a resolution of 256 x 256 picture elements (pixels). Each pixel
Figure 1. Combination of 2-D slices to form a 3-D model
intensity is represented by a 16 bit, unsigned integer number. Therefore, the pixel intensity will range from 0 to 65,535. Preliminary cadaver scans are made to determine which technique will provide the best data These preliminary tests are used in deterining the optimum number of samples needed to obtain the desired resolution. The resulting digitized data from multiple sections through the limb are saved to 1/2 inch, nine track magnetic tape. The data is then transferred to a graphics workstation for additional processing. The second method of data collection to be evaluated is the video digitization of cross sections of the limb. The limb is embedded in a block of supping medium and sectioned in a large cryotome. The cross-sectional view can then be photographed. The Vesalius Project[2] at Colorado State University has taken this approach. They utilize skilled anatomist to hand trace the structures on a digiing pad. This method provides accurate digitzing, but is extremely time consuming. We are proposing to use a high resolution camera to digitize cryotome slices. These slices will be digitized, at a 512 x 512 resolution, directly into the computer. Image processing techniques will be developed to select regions of interest (ROI). A ROI, representing an aomical structure, for each 2D image can then be stored in a computer file. The files can then be stacked in the computer to reconstruct a 3-D volume rendering of the structure under study.
Image Generation and Display The second element of the project involves the generation and display of the 3-D models based on
the digital information stored in the database. A Sun Microsystems SPARCstation 1+ GX graphics workstation is used for processing and displaying the models. The workstation has a high resolution color monitor and is configured with 24 megabytes of RAM and 669 megabytes of storage. Additional data storage is available on other networked workstations. The Sun workstation, in conjunction with Sun software (SunVision[3]), provides a windowing environment and the visualiions tools required to construct and display 3-D volumetric models. The SunVision Volume Rendering software, SunVoxel, supports three volume viewing modes: cube viewing mode presents volume data as a 3-D cube, lightbox viewing mode allows for viewing the volume as a series of 2-D slices, point cloud viewing mode provides a means of displaying data that has been extracted from a volume data set. The cube viewing mode satisfies our criteria for an interactive means of manipulating volume rendered anatomical structures. SunVoxel provides an interactive interface for selecting volume orientation, rendering modes, rendering options, scaling, orthogonal clipping planes in x-axis (left and right), y-axis (top and bottom), zaxis (front and back), and the creation of an oblique plane that can be pushed into the volume. SunVision also includes a set of C libraries that provide image processing functions that can be utilized in user written software. Results
To date, the project has been working only with CT data. The CT data was collected from a medium sized, male cadaver forelimb that was prepared for normal anatomical dissection. The limb was placed on the gantry with the distal portion extending over the edge. A bean bag was used to secure the limb and prevent it from falling off. The limb was scanned from the scapula to the proximal phalanges. The scans were taken on 4mm intervals which generated 104 slices. The slice data was then saved on nine inch magnetic tape. A magnetic tape utility was used to read the slice data from the tape, strip the tape headers and write the individual image data into files on a Digital Equipment Corporation VAX 8800. The files were then transferred over ethernet to a Sun workstation using FbP (File Transfer Protocol) binary mode. Each image file contained a 2048 byte Image Information Block (UB). The actual image data consists of 256 columns and 256 rows of 16 bit data. Custom software was written to process the files for use by SunVoxel. The program stripped the IIB, performed a byte swap, scaled the data from 16 bit to 8 bit and concatenated the files to produce a single file containing the volume data for the "stacked" slices. The resulting file could be processed and displayed by SunVoxel.
763
One problem encountered was the conversion of 16 bit density infonnation that the CT machine generates to 8 bit data that SunVoxel could use. Initially a linear interpolation was done. The range represented by 16 bits (65,536) was evenly divided into 256 intervals (number of densities that can be represented by 8 bits). This method did not produce acceptable images because linear interpolation does not tae into account the distribution of the density values in the image. Image information was lost because a high frequency of density values was contained in a single interval. We were able to generate acceptable images by using a look-up-table (LUT) for the interpolation. The LUT is based on the histogram for the image. A histogram provides a frequency distribution of densities for the image. The LUT can then be constructed to provide more intervals in areas where the histogram contains more data points. Discussion The project is expected to produce a set of techniques that can be used for acquiring the 3-D data necessary to construct volume rendered anatomical models. At this time the project's emphasis has been in evaluating the use of CT for volume reconstruction. CT imaging technology has been used to visualize anatomical structures in small and large animal veterinary medicine[4,5]. These studies have involved only the 2-D aspect of anatomy. We believe tha 3-D volumetric rendering offers a better means of visualizing anatomic structures. In the past, standard 3-D reconstruction used threshholding (surface rendering technique) as a required preprocessing step in data extraction[6]. Using surface rendering or edge detection programs, only the boundaries of a given structure are presented to create the image. This binary function had been one of the major limitations in 3-D image quality. The display of soft tissues or muscles was nearly impossible by using theshholding techniques[7]. We feel that current volume rendering techniques provide high-quality images that preserve all the information from the CT scans (object thickness and transparency) not just surface edges. The same volumetric rendering techniques that have proved useful in producing images with unrivaled detail and accuracy for routine clinical use[8] can be used in the digital anatomical database project. The technique of video digitizing cross-sections to collect data has not been explored at the time of this writing. We feel that the use of a high resolution digital camera will yield suitable images. Image processing algorithms to assist in identifying anatomical regions of interest will be explored. The image quality obtained by the two data collection procedures will be compared. The data collection
764
technique that proves to be versatile, efficient, and produce a quality image will be used for the remainder of the project. There is an increasing number of opportunities for the use of computer-based visulization in higher education[9]. The computer generated display of anatomical strucures has the potential to reduce the number of animals used in gross lab and become the basis for computer assisted instructional systems. A digital database of anatomical structures can be used in conjunction with gross dissection in teaching normal anatomy to first year students in the professional curriculum. The computer model gives students the opportunity to "discover" relationships between aatomical structures that may have been destroyed or may not be obvious in the gross dissection. Through the use of the digital database the student has the ability to interactively manipulate, on the computer screen, a realistic model of the anatomical structure in question. Since volumetric rendering techniques utilize all the anatomic information, structures can be viewed through any user defined plane. By using a digital database, the student has the ability to view and manipulate anatomical structures in ways that are not available through interactive video disk (IVD). IVD constrains the student to preselected views and sections that are stored on disk. Any updating or changes to a IVD also requires the additional expense of mastering. The digital database can be modified and/or updated easily. As part of the project, preliminary data will be gathered to test the usefulness of the system to teaching anatomy. The digital anatomical database can be used to enhance the visualization of approaches to certain surgical procedures. Prior to surgery, senior students can display the area in question and exam the anatomy to find the best approach to the surgical site. An extension of this project is the construction of "fractured" limb models. The fractured limb models could be used by students to study the approach and proper mode of fixation for the fracture. Through the use of finite element modeling (engineering technique for analyzing the strength of structures), the "repaired" fractures could be evaluated as to the stresses that would be applied to the fracture and the probable outcome of the procedure. The techniques learned in the construction of the digital anatomical datbase can be applied to the development of visualizations tools that will allow for 3-D modelling of fractures. Such tools will allow the surgeon to better visualize the fracture and the relationship of its components. Conclusions The Digital Anatomical Database Project is still in its infancy. The next step in the project will be to explore the technique of video digitizing cross-
sections for data collection. MRI data may also be explored. We are also in the process of building surface models (as opposed to volume models) that will be used in a real-time "walk through" mode for nteractive voyages though body systems (i.e. vascular, urinary, gastrointestinal).
[3]
Sun Microsystems, Mountain View, Califonia.
[4]
J. R. Fike, et al,"Canine Anatomy as Assessed by Computerized Tomography," American Journal of Veterinary Research, November 1980.
Acknowledgments
[5]
P. R. Peterson, K. F. Bowman,"Computed Tomographic Anatomy of the Distal Extremity of the Horse," Veterinary Radiology, Vol 29, No. 4, 1988.
[6]
E. K. Fishman, et al,"Three-Dimensional Imaging and Display of Musculoskeletal
We would like to thank Pandu Jai Prakash
(graduate student in computer science) and Laurie Mar l (graduate stdent in visualization) for their contributions to the project. Ihe authors are also
eful to Kipp Aldrich (Visualiztion Laboraoy) for his assistance. This work was suppoit by a competitive grant from the Texas Veterinary Medical Center. Dr. Snell is the director of the Veteinary Knowledge Engineering aboratory.
Anatomy," Journal of Computer Assisted Tomography, Vol. 12, No. 3, 1988. [7]
References
E. K. Fishman, et al,"Three-Dimensional Reconstruction of the Human Body," AJR, June
1988.
[1] C. Rosse, J. Brinldey, and J. Prothero,"Structual nformatics: The Representation of Anatomical Knowledge In Computer Redable From," Proceedings of the Ist American Medical Informatics Association Educational and Research Conference, June 1990.
[8]
IEEE Computer Graphics and Applications, March 1990.
[9]
[2] S. Roper,"The Vesalius Project," Academic Computing, October 1989.
765
D. R. Ney, E. K. Fishman, D. Magid, R. A. Drebin,"Volumetric Rendering of Computed Tomography Data: Principles and Techniques,"
J. R. Brown and S. Culningham,"Visualization in Higher Education," Academic Computing, March 1990.
tDepartment of Veterinary Anatomy and Public Health 'Department of Large Animal Medicine and Surgery Vepartment of Architecture - Visualization Lab Texas A&M University The objectives of the Veterinary Digital Anatomical Database Project are:
Abstract
This paper describes the Veterinary Digital Anatomical Database Project. The purpose of the project is to investigate the construction and use of digitally stored anatomical models. We will be discussing the overall project goals and the results to date. Digital anatomical models are 3 dimensional, solid model representations of normal anatomy. The digital representations are electronically stored and can be manipulated and displayed on a computer A digital database of graphics workstation. anatomical structures can be used in conjunction with gross dissection in teaching normal anatomy to first year students in the professional curriculum. The computer model gives students the opportunity to "discover" relationships between anatomical structures that may have been destroyed or may not be obvious in the gross dissection. By using a digital database, the student will have the ability to view and manipulate anatomical structures in ways that are not available through interactive video disk (IVD). IVD constrains the student to preselected views and sections stored on the disk.
Introduction Anatomical knowledge is fundamental to solving problems in biomedical research, education, and patient care. Based on the concept of Structural formatics[l], anatomical knowledge can be clasified into two components: spatal and symbolic. Spatial knowledge deals with geometrical attributes of biological objects, such as their shape, size, volume and the 3 dimensional (3-D) inter-relationships. Symbolic knowledge deals with the non-spatial attributes and relationships of biological objects, such as their functional, developmental, hierarchical, and taxonomic relationships. The purpose of Structural Inforatics is to apply both spatial and symbolic knowledge to solve problems in biomedical research, education, and patient management. This project focuses on developing the techniques for building the spatial component of anatomical knowledge. 0195-4210/91/$5.00 C) 1992 AMIA, Inc.
762
*
Refme the techniques required to obtain digital, 3-D coordinates of selected anatomical structures of the canine foreleg. These techniques can then be applied to other anatomical strucures.
*
Utilize the collected 3-D coordinates to construct a volumetric rendering of the selected
anatomical structures. Volumetric rendering allows for random sectioning through structures without the loss of any anatomic information. *
Test the usefulness of digital anatomical structres in leaming normal anatomy.
Materials and Methods The canine forelimb was chosen as the first anatomical structure to be studied. The forelimb provides representative tissue densities for skin, muscle, fat, and bone. The project consists of two The first element involves the components. collection of data to be used to construct 3-D, volumetric models of anatomic strucres. Database Collection and Construction Two methods of collecting 3-D data are proposed. We are currently investigating the use of X-ray computerized tomography (CT) to collect serial slices of the structure under study. The data in each slice is comprised of a two-dimensional array of values. These values represent density information. The 2 dimensional (2-D) slices are then combined to produce a 3-D model (Figure 1). Once the slices have been combined into a volume, the resulting data is referred to as voxel data. A voxel is a volume element - a value that has a x,y,z location within the volume. The voxel is the 3-D equivalent of a pixel. The CT data is collected with a Technicare Deltscan 2010 CT scan machine. The Deltascan 2010 produces a 2-D image that has a resolution of 256 x 256 picture elements (pixels). Each pixel
Figure 1. Combination of 2-D slices to form a 3-D model
intensity is represented by a 16 bit, unsigned integer number. Therefore, the pixel intensity will range from 0 to 65,535. Preliminary cadaver scans are made to determine which technique will provide the best data These preliminary tests are used in deterining the optimum number of samples needed to obtain the desired resolution. The resulting digitized data from multiple sections through the limb are saved to 1/2 inch, nine track magnetic tape. The data is then transferred to a graphics workstation for additional processing. The second method of data collection to be evaluated is the video digitization of cross sections of the limb. The limb is embedded in a block of supping medium and sectioned in a large cryotome. The cross-sectional view can then be photographed. The Vesalius Project[2] at Colorado State University has taken this approach. They utilize skilled anatomist to hand trace the structures on a digiing pad. This method provides accurate digitzing, but is extremely time consuming. We are proposing to use a high resolution camera to digitize cryotome slices. These slices will be digitized, at a 512 x 512 resolution, directly into the computer. Image processing techniques will be developed to select regions of interest (ROI). A ROI, representing an aomical structure, for each 2D image can then be stored in a computer file. The files can then be stacked in the computer to reconstruct a 3-D volume rendering of the structure under study.
Image Generation and Display The second element of the project involves the generation and display of the 3-D models based on
the digital information stored in the database. A Sun Microsystems SPARCstation 1+ GX graphics workstation is used for processing and displaying the models. The workstation has a high resolution color monitor and is configured with 24 megabytes of RAM and 669 megabytes of storage. Additional data storage is available on other networked workstations. The Sun workstation, in conjunction with Sun software (SunVision[3]), provides a windowing environment and the visualiions tools required to construct and display 3-D volumetric models. The SunVision Volume Rendering software, SunVoxel, supports three volume viewing modes: cube viewing mode presents volume data as a 3-D cube, lightbox viewing mode allows for viewing the volume as a series of 2-D slices, point cloud viewing mode provides a means of displaying data that has been extracted from a volume data set. The cube viewing mode satisfies our criteria for an interactive means of manipulating volume rendered anatomical structures. SunVoxel provides an interactive interface for selecting volume orientation, rendering modes, rendering options, scaling, orthogonal clipping planes in x-axis (left and right), y-axis (top and bottom), zaxis (front and back), and the creation of an oblique plane that can be pushed into the volume. SunVision also includes a set of C libraries that provide image processing functions that can be utilized in user written software. Results
To date, the project has been working only with CT data. The CT data was collected from a medium sized, male cadaver forelimb that was prepared for normal anatomical dissection. The limb was placed on the gantry with the distal portion extending over the edge. A bean bag was used to secure the limb and prevent it from falling off. The limb was scanned from the scapula to the proximal phalanges. The scans were taken on 4mm intervals which generated 104 slices. The slice data was then saved on nine inch magnetic tape. A magnetic tape utility was used to read the slice data from the tape, strip the tape headers and write the individual image data into files on a Digital Equipment Corporation VAX 8800. The files were then transferred over ethernet to a Sun workstation using FbP (File Transfer Protocol) binary mode. Each image file contained a 2048 byte Image Information Block (UB). The actual image data consists of 256 columns and 256 rows of 16 bit data. Custom software was written to process the files for use by SunVoxel. The program stripped the IIB, performed a byte swap, scaled the data from 16 bit to 8 bit and concatenated the files to produce a single file containing the volume data for the "stacked" slices. The resulting file could be processed and displayed by SunVoxel.
763
One problem encountered was the conversion of 16 bit density infonnation that the CT machine generates to 8 bit data that SunVoxel could use. Initially a linear interpolation was done. The range represented by 16 bits (65,536) was evenly divided into 256 intervals (number of densities that can be represented by 8 bits). This method did not produce acceptable images because linear interpolation does not tae into account the distribution of the density values in the image. Image information was lost because a high frequency of density values was contained in a single interval. We were able to generate acceptable images by using a look-up-table (LUT) for the interpolation. The LUT is based on the histogram for the image. A histogram provides a frequency distribution of densities for the image. The LUT can then be constructed to provide more intervals in areas where the histogram contains more data points. Discussion The project is expected to produce a set of techniques that can be used for acquiring the 3-D data necessary to construct volume rendered anatomical models. At this time the project's emphasis has been in evaluating the use of CT for volume reconstruction. CT imaging technology has been used to visualize anatomical structures in small and large animal veterinary medicine[4,5]. These studies have involved only the 2-D aspect of anatomy. We believe tha 3-D volumetric rendering offers a better means of visualizing anatomic structures. In the past, standard 3-D reconstruction used threshholding (surface rendering technique) as a required preprocessing step in data extraction[6]. Using surface rendering or edge detection programs, only the boundaries of a given structure are presented to create the image. This binary function had been one of the major limitations in 3-D image quality. The display of soft tissues or muscles was nearly impossible by using theshholding techniques[7]. We feel that current volume rendering techniques provide high-quality images that preserve all the information from the CT scans (object thickness and transparency) not just surface edges. The same volumetric rendering techniques that have proved useful in producing images with unrivaled detail and accuracy for routine clinical use[8] can be used in the digital anatomical database project. The technique of video digitizing cross-sections to collect data has not been explored at the time of this writing. We feel that the use of a high resolution digital camera will yield suitable images. Image processing algorithms to assist in identifying anatomical regions of interest will be explored. The image quality obtained by the two data collection procedures will be compared. The data collection
764
technique that proves to be versatile, efficient, and produce a quality image will be used for the remainder of the project. There is an increasing number of opportunities for the use of computer-based visulization in higher education[9]. The computer generated display of anatomical strucures has the potential to reduce the number of animals used in gross lab and become the basis for computer assisted instructional systems. A digital database of anatomical structures can be used in conjunction with gross dissection in teaching normal anatomy to first year students in the professional curriculum. The computer model gives students the opportunity to "discover" relationships between aatomical structures that may have been destroyed or may not be obvious in the gross dissection. Through the use of the digital database the student has the ability to interactively manipulate, on the computer screen, a realistic model of the anatomical structure in question. Since volumetric rendering techniques utilize all the anatomic information, structures can be viewed through any user defined plane. By using a digital database, the student has the ability to view and manipulate anatomical structures in ways that are not available through interactive video disk (IVD). IVD constrains the student to preselected views and sections that are stored on disk. Any updating or changes to a IVD also requires the additional expense of mastering. The digital database can be modified and/or updated easily. As part of the project, preliminary data will be gathered to test the usefulness of the system to teaching anatomy. The digital anatomical database can be used to enhance the visualization of approaches to certain surgical procedures. Prior to surgery, senior students can display the area in question and exam the anatomy to find the best approach to the surgical site. An extension of this project is the construction of "fractured" limb models. The fractured limb models could be used by students to study the approach and proper mode of fixation for the fracture. Through the use of finite element modeling (engineering technique for analyzing the strength of structures), the "repaired" fractures could be evaluated as to the stresses that would be applied to the fracture and the probable outcome of the procedure. The techniques learned in the construction of the digital anatomical datbase can be applied to the development of visualizations tools that will allow for 3-D modelling of fractures. Such tools will allow the surgeon to better visualize the fracture and the relationship of its components. Conclusions The Digital Anatomical Database Project is still in its infancy. The next step in the project will be to explore the technique of video digitizing cross-
sections for data collection. MRI data may also be explored. We are also in the process of building surface models (as opposed to volume models) that will be used in a real-time "walk through" mode for nteractive voyages though body systems (i.e. vascular, urinary, gastrointestinal).
[3]
Sun Microsystems, Mountain View, Califonia.
[4]
J. R. Fike, et al,"Canine Anatomy as Assessed by Computerized Tomography," American Journal of Veterinary Research, November 1980.
Acknowledgments
[5]
P. R. Peterson, K. F. Bowman,"Computed Tomographic Anatomy of the Distal Extremity of the Horse," Veterinary Radiology, Vol 29, No. 4, 1988.
[6]
E. K. Fishman, et al,"Three-Dimensional Imaging and Display of Musculoskeletal
We would like to thank Pandu Jai Prakash
(graduate student in computer science) and Laurie Mar l (graduate stdent in visualization) for their contributions to the project. Ihe authors are also
eful to Kipp Aldrich (Visualiztion Laboraoy) for his assistance. This work was suppoit by a competitive grant from the Texas Veterinary Medical Center. Dr. Snell is the director of the Veteinary Knowledge Engineering aboratory.
Anatomy," Journal of Computer Assisted Tomography, Vol. 12, No. 3, 1988. [7]
References
E. K. Fishman, et al,"Three-Dimensional Reconstruction of the Human Body," AJR, June
1988.
[1] C. Rosse, J. Brinldey, and J. Prothero,"Structual nformatics: The Representation of Anatomical Knowledge In Computer Redable From," Proceedings of the Ist American Medical Informatics Association Educational and Research Conference, June 1990.
[8]
IEEE Computer Graphics and Applications, March 1990.
[9]
[2] S. Roper,"The Vesalius Project," Academic Computing, October 1989.
765
D. R. Ney, E. K. Fishman, D. Magid, R. A. Drebin,"Volumetric Rendering of Computed Tomography Data: Principles and Techniques,"
J. R. Brown and S. Culningham,"Visualization in Higher Education," Academic Computing, March 1990.
