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Model-based Automatic AC/PC Detection on Three-dimensional MRI Scans

Model-based Automatic AC/PC Detection on Three-dimensional MRI Scans. Babak A. Ardekani, Ph.D., Alvin H. Bachman, Ph.D., Ali Tabesh, Ph.D. The Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY.

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Model-based Automatic AC/PC Detection on Three-dimensional MRI Scans

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  1. Model-based Automatic AC/PC Detection on Three-dimensional MRI Scans Babak A. Ardekani, Ph.D., Alvin H. Bachman, Ph.D., Ali Tabesh, Ph.D. The Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY

  2. The anterior and posterior commissures are bundles of transverse white matter fibers that connect the two cerebral hemispheres

  3. AC PC The AC and PC landmarks are intersection points of these fibers with the mid-sagittal plane

  4. Aim To develop an algorithm for automatic detection of the AC/PC on 3D structural MRI scans

  5. Applications • Orientation of the human brain for computerized image analysis • Definition of coordinate systems in brain atlases (Talairach-Tournoux; Schaltenbrand-Wahren) • Placement and orientation of the imaging FOV in MRI acquisition • Image registration

  6. Example application FOV placement for MRI acquisition

  7. Method • 3D template matching • Normalized cross-correlation (NCC) similarity measure

  8. Template definition AC/PC and MPJ landmarks are manually placed on example images by an expert

  9. Algorithm MRI volume Detect the mid-sagittal plane (MSP) Detect midbrain-pons junction (MPJ) MPJ template AC/PC templates Save AC/PD Detect AC/PC Save MSP Update MSP

  10. MSP detection Ax + By + Cz = 1 Ardekani et al., IEEE Trans. Medical Imaging, 1997.

  11. Algorithm MRI volume Detect the mid-sagittal plane (MSP) Detect midbrain-pons junction (MPJ) MPJ template AC/PC templates Save AC/PD Detect AC/PC Save MSP Update MSP

  12. MPJ detection Candidate MPJ points are detection on a circular search region by template matching using NCC

  13. Algorithm MRI volume Detect the mid-sagittal plane (MSP) Detect midbrain-pons junction (MPJ) MPJ template AC/PC templates Save AC/PD Detect AC/PC Save MSP Update MSP

  14. AC/PC detection The AC/PC are detected based on each possible MPJ location

  15. AC/PC detection The final decision is made by adding the NCC’s of all three landmarks

  16. Algorithm MRI volume Detect the mid-sagittal plane (MSP) Detect midbrain-pons junction (MPJ) MPJ template AC/PC templates Save AC/PD Detect AC/PC Save MSP Update MSP

  17. MRI data • 36 healthy volunteers, 17 patients with chronic schizophrenia (total: 53 scans) • Siemens Vision 1.5T • 3D T1-weighted MPRAGE structural MRI scans • TR=11.6 ms, TE=4.9 ms, =8, Matrix=256×256×190, 1 mm3 voxels

  18. Template definition 3 patient (top row) and 3 control (bottom row) scans were used to construct templates for AC/PC and MPJ

  19. Results Qualitatively correct AC/PC locations were detected on 52 of the 53 cases.

  20. Results The 1 scan on which the algorithm failed

  21. Results 5 of 53 scans had severe artifacts

  22. Results Processing time: 6 s on Pentium 4, 3.2 GHz (4.5 s MSP detection + 1.5 s AC/PC detection); 2 s on Quad Core Intel Xeon E5430, 2.66 GHz

  23. Results: Manual vs. automatic detection 3D Euclidean distance (error) between manually and automatically detected AC/PC in 42 scans (53-6-5=42)

  24. Summary • Fast, accurate, robust, and fully automatic AC/PC detection • Algorithm can be trained for contrasts other than T1 (e.g., T2-weighted FSE) • Algorithm shows robustness with respect to field strength, pulse sequence parameters, subject population • Available on www.nitrc.org

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