Automated CT Based Liver Volume Assessment - Definiens

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Methods • 30 consecutive <strong>CT</strong> scans from distinct patients with liver metastases were obtained. Patients had tumor burdens form minimal to heavily occupying much of the liver – 320 slice Toshiba <strong>CT</strong> scanner – Study details: • 1mm collimation • Portal venous phase contrast-enhanced scans of the abdomen • All scans were manually segmented to define reference standard for liver boundaries (including metastatic lesions) using in- house software – Parts of the inferior vena cava and portal vein were included within the liver boundary when enclosed by liver parenchyma in order to make the liver contour smooth Medical Imaging – Princess Margaret Hospital – University Health Network – Mount Sinai Hospital – University of Toronto
Methods • Five representative cases were selected as a training set for the automatic segmentation algorithm • The remaining 25 cases were used to test the refined algorithm • Resultant automatic segmentations generated were compared to the manually generated reference segmentations and deviations were measured 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: Purpose To evaluate the accuracy of
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 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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