Automated CT Based Liver Volume Assessment - Definiens

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Results: Sample Segmentation II Statistics • CC 0.94 • MO 89% • 6:29 min (best case) Medical Imaging – Princess Margaret Hospital – University Health Network – Mount Sinai Hospital – University of Toronto
Results: Summary • Correlation coefficient between the measured and estimated volumes: 0.864 ± 0.04 (0.777 – 0.935) • Mean volumetric overlap: 77% ± 6 (64 – 88%) • Mean liver volume measured by the automatic segmentation algorithm: 1820 cm³ ± 788 (710 – 4565 cm³) • Mean liver volume measured by manual segmentation: 1806 cm³ ± 685 (934 – 3460 cm³) • Mean total time for the automatic segmentation: 4.8 minutes ± 1.2 on E6750 @2.66GHz Intel Core 2 Duo CPU with 3.25 GB RAM Medical Imaging – Princess Margaret Hospital – University Health Network – Mount Sinai Hospital – University of Toronto
Page 1 and 2: Automated CT Based Liver Volume Ass
Page 3 and 4: Purpose To evaluate the accuracy of
Page 5 and 6: Methods • Five representative cas
Page 7 and 8: Automatic Segmentation Algorithm Au
Page 9 and 10: Based on intensity and size the bac
Page 11 and 12: Algorithm: Preprocessing Based on s
Page 13 and 14: Algorithm: Liver Seed Liver Seed 1.
Page 15 and 16: Based on size, a single liver seed
Page 17 and 18: Algorithm: Liver refinement/Growing
Page 19 and 20: Algorithm: Liver Refinement/Growing
Page 21 and 22: Algorithm: Update Original Image Re
Page 23: Results: Sample Segmentation I Stat
Page 27 and 28: Conclusion • Fully-automated segm

Automated CT Based Liver Volume Assessment - Definiens

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