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Enhanced Automated Segmentation for Thalamic Nuclei Using Advanced MRI Techniques

This study explores the benefits of automating the segmentation of thalamic nuclei in MR images, particularly focusing on MS patients' atrophy measurement. The research compares the performance of various algorithms and highlights the effectiveness of local ranking in improving accuracy. Results demonstrate the superiority of the proposed method over competitors, emphasizing the significance of unbiased validation. By optimizing local ranking, the proposed approach offers enhanced segmentation capabilities, particularly evident in phantom simulations and ADNI data analysis.

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Enhanced Automated Segmentation for Thalamic Nuclei Using Advanced MRI Techniques

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Presentation Transcript

  1. Jul 15, 2013 Jason Su

  2. Motivation • Manual segmentation of structures on MR images is an important but often tedious task, requiring the expertise of a radiologist • Automation is highly desirable and can also help remove observer bias • At 7T, we are working on studies that could benefit from this • Manually segmenting thalamic nuclei with the improved contrast of WMn-MPRAGE • Measuring atrophy in MS patients

  3. Background

  4. Similarity Measures

  5. Similarity Measures

  6. STEPS Improvements on STAPLE

  7. Theory: Model

  8. Theory: Model

  9. Improvement: Local Ranking

  10. Improvement : MRF Regularization

  11. Improvement: Unbiasing

  12. Validation

  13. Results: Optimizing Local Ranking • STEPS does best for X=15 but the gain is marginal? • Notably, other algorithms can become much worse with more templates

  14. Results: Simulation • Local ranking in STEPS beats global ranking in STAPLE • Especially when the morphology of the target is very different from atlas raters • This means can get away with less raters to cover more cases

  15. Results: Phantom Simulation • Measure the performance as R, the number of raters or size of the atlas, is reduced • STEPS beats the others with even the smallest R • Performance characteristics can change with R, i.e. optimal X

  16. Results: Phantom Simulation • STEPS is significantly better than all of these competitors • They all seem pretty good though, splitting hairs?

  17. Results: Phantom Simulation

  18. Results: ADNI

  19. Results: MRF Smoothing in Multi-Steps

  20. Discussion

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