NA-MIC National Alliance for Medical Image Computing Validation of Bone Models Using 3D Surface...

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?


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”


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


LPX-250 Laser Scanner


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


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


CT Scan


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


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


Proximal Bone Surface Scanning Steps Specimen CA05042125L

Distal Up

Distal End Proximal End

Proximal Up

Distal Merge Proximal Merge

Full Finger Scan


Proximal Bone – CA05042125L


Middle (Green) and Distal (Pink) Bones – CA05042125L


Full Finger – CA05042125L

Full Finger – MD05010306R

Full Finger Surface Scans


Full Finger – MD05042226L

Full Finger – SC05030303R


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


Surface Distance Measurement Tool


Proximal Distance MapLaser scanned surfaceTraced surface

Surface Distances: 1P-SC05030303R


Middle Distance MapLaser scanned surfaceTraced surface

Surface Distances: 1M-SC05030303R


Distal Distance Map Laser scanned surfaceTraced surface

Surface Distances: 1D-SC05030303R


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


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


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?


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

NA-MIC National Alliance for Medical Image Computing Validation of Bone Models Using 3D Surface...

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