NA-MICNational Alliance for Medical Image Computing http://na-mic.org
Validation of Bone Models Using 3D Surface Scanning
Nicole M. Grosland
Vincent A. Magnotta
National Alliance for Medical Image Computing http://na-mic.org
Validation
• True “gold-standard” often very difficult to achieve– Brain imaging often have to live with
manual raters– Established guidelines based on
anatomical experts
• Are there better “gold-standards” for other regions of the body?
National Alliance for Medical Image Computing http://na-mic.org
Orthopaedic Imaging
• Ideas developed out of goal to automate the definition of regions of interest of the upper extremity– How can we validate these automated tools?
• Orthopaedic applications it is possible to dissect the region out of cadeveric specimens– Use specimen itself as the “gold-standard”
National Alliance for Medical Image Computing http://na-mic.org
3D Laser Scanner
• 3D Laser scanners have been used for rapid prototyping and to non- destructively image ancient artifacts
• Roland LPX-250 Scanner Obtained– Planar and rotary scanning modes– 0.008 inch resolution in planar mode– Objects up to 10 inches wide and 16
inches tall can be scanned– Reverse modeling software tools
National Alliance for Medical Image Computing http://na-mic.org
Specimens
• 15 cadaveric specimens were obtained spanning the distal radius to the finger tips – Specimens mounted on a Plexiglas
sheet in the neutral position
• CT images collected on a Siemens Sensation 64 scanner– Images obtained with a 0.2x0.2x0.4mm
resolution
National Alliance for Medical Image Computing http://na-mic.org
Image Post Processing
• Resampled images to 0.2mm3 resolution– Images cropped at the wrist
• Manually defined the proximal, medial, and distal phalanx bones– Two raters defined these regions on 11 fingers– Inter-rater reliability evaluated using relative
overlap (0.91, 0.90, and 0.87 respectively) – Surfaces from the binary masks were
generated
National Alliance for Medical Image Computing http://na-mic.org
Finger Dissection
• Phalanx and metacarpal bones removed– Care taken to avoid tool marks on the bones
• De-fleshing process outlined by Donahue et al (2002) was utilized– Bones allowed to soak in a 5.25% sodium
hypochlorite (bleach) solution for 6 hours
• Degreased via a soapy water solution• Thin layer of white primer was used to
coat the bony surfaces
National Alliance for Medical Image Computing http://na-mic.org
Prepare Specimen for Scanning
Deflesh, Degrease, Paint, Embed in Clay
Scan Long Axis (Distal End Up) Using Dr. PICZA 4-Plane Scanning
Scan Distal End Using Dr. PICZA 1-Plane Scanning
Scan Long Axis (Proximal End Up) Using Dr. PICZA 4-Plane Scanning
Scan Proximal End Using Dr. PICZA 1-Plane Scanning
Edit the Scanned Surface Using Dr. PICZA Editing Tools
Remove Noise, Delete Abnormal Faces, Create Polygon Mesh
Use Pixform Software to Further Edit Surface
Delete Extraneous Vertices, Fill Holes in Surface, Clean Non-manifold and Crossing Faces
Align, Register, and Merge the Long Axis (Distal End Up) and the Distal End
Align, Register, and Merge the Long Axis (Proximal End Up) and the Proximal End
Align, Register, and Merge the Distal and Proximal Ends of the Bone
Smooth Final Surface with a Tolerance of 0.10 mm
National Alliance for Medical Image Computing http://na-mic.org
Proximal Bone Surface Scanning Steps Specimen CA05042125L
Distal Up
Distal End Proximal End
Proximal Up
Distal Merge Proximal Merge
Full Finger Scan
National Alliance for Medical Image Computing http://na-mic.org
Middle (Green) and Distal (Pink) Bones – CA05042125L
National Alliance for Medical Image Computing http://na-mic.org
Full Finger – CA05042125L
Full Finger – MD05010306R
Full Finger Surface Scans
National Alliance for Medical Image Computing http://na-mic.org
Full Finger – MD05042226L
Full Finger – SC05030303R
National Alliance for Medical Image Computing http://na-mic.org
Registration of Surfaces
• Surface scans origin shifted to center of mass and reoriented to have the same orientation as the CT data
• Surfaces registered using a rigid iterative closest point algorithm
• Compute Euclidean distance between the surfaces
National Alliance for Medical Image Computing http://na-mic.org
Proximal Distance MapLaser scanned surfaceTraced surface
Surface Distances: 1P-SC05030303R
National Alliance for Medical Image Computing http://na-mic.org
Middle Distance MapLaser scanned surfaceTraced surface
Surface Distances: 1M-SC05030303R
National Alliance for Medical Image Computing http://na-mic.org
Distal Distance Map Laser scanned surfaceTraced surface
Surface Distances: 1D-SC05030303R
National Alliance for Medical Image Computing http://na-mic.org
Results
Finger ID
Average Distance between Surfaces
1P-SC05030303R 0.145
1M-SC05030303R 0.134
1D-SC05030303R 0.142
1P-MD05010306R 0.142
Average values 0.142
National Alliance for Medical Image Computing http://na-mic.org
Discussion
• Surface scans used to validate regions of interest generated via CT scans– Average distance less than 1 voxel (0.2mm)
• Surface scans can be used to evaluate image processing procedures– Validation of tracing guidelines– Amount of smoothing– Iso-surface threshold – Evaluation of automated segmentation
routines
National Alliance for Medical Image Computing http://na-mic.org
Future Work
• Make regional specific measurement– E.g. articulating surface
• Evaluate ANN segmentation using this technique
• Can this be used to evaluate soft tissue geometry?
National Alliance for Medical Image Computing http://na-mic.org
Thanks
• Nicole Grosland – Project PI• Esther Gassman
– Manual Traces/Surface scanning• Nicole Kallemeyn
– Manual tracing and surface comparison• Nicole Devries
– Finger dissection and specimen prep• Kiran Shivanna
– Software development• Stephanie Powell
– Automated segmentation
Work funded in part by NIH/NIBIB Grant 1R21EB001501-01A2