Automated CT Based Liver Volume Assessment - Definiens

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Automatic Segmentation Algorithm Preprocessing 1. Background is separated from the body 2. Right and left lungs are identified as context objects 3. <strong>Based</strong> on size and intensity (HU), additional context objects are generated (e.g. fat, muscle, other organs, bones) 4. Within the bone objects, spine and ribs are identified as additional context objects based on ROI (using lungs) and shape 5. An additional layer of 3D edge information is calculated Note: Context objects do not have to be 100% perfectly segmented to guide the analysis. Medical Imaging – Princess Margaret Hospital – University Health Network – Mount Sinai Hospital – University of Toronto
<strong>Based</strong> on intensity and size the background is separated from the body Algorithm: Preprocessing 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: Automatic Segmentation Algorithm Au
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 and 24: Results: Sample Segmentation I Stat
Page 25 and 26: Results: Summary • Correlation co
Page 27 and 28: Conclusion • Fully-automated segm

Automated CT Based Liver Volume Assessment - Definiens

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