Automatic CT Liver segmentation based on deep learning

Automatic CT Liver segmentation based on deep learning


Fast and reproducible method for segmenting the liver

Hepatic VCAR provides automated segmentation and assessment of liver, liver lesions, and vasculature which helps enable an efficient and consistent workflow.

CT Liver volumetry

Challenge in CT LIVER volumetry

Hepatic VCAR*

Automatic CT Liver segmentation
based on deep learning

Complete reading workflow solution featuring:

Supporting Materials

Watch

Hepatic VCAR Video

* Not available for sales in all regions.

  1. Byass, P. The global burden of liver disease: a challenge for methods and for public health. BMC Med. 2014; 12: 159.
  2. Golse, N. Should We Have Blind Faith in Liver Volumetry? SurgicalCase Reports doi: 10.31487/j.SCR.2019.01.003.
  3. Gotra, A. Liver segmentation: indications, techniques and future directions. Insights Imaging (2017) 8:377–392.
  4. Favelier, S. Anatomy of liver arteries for interventional radiology. Diagnostic and Interventional Imaging (2015) 96, 537—546.
  5. Suzuki, K. Quantitative Radiology: Automated CT Liver Volumetry Compared With Interactive Volumetry and Manual Volumetry. AJR:197, October 2011.
  6. Lodewick, TM. Fast and accurate  liver volumetry prior to hepatectomy. International Hepato-Pancreato-Biliary Association, HPB 2016, 18, 764–772.
  7. Golse. N. Should We Have Blind Faith in Liver Volumetry? SURGICAL CASE REPORTS | ISSN 2613-5965.
  8. Data on file (GE internal document).
  9. Timing performance based on Z440 hardware.
  10. Clinical evaluation of Hepatic VCAR, GE internal document.
  11. IARC database of 2018.
  12. JAMA Oncol. 2017;3(12):1683-1691. doi:10.1001/jamaoncol.2017.3055Published online October 5, 2017. Corrected on December 14, 2017.