title: Fully automated MR liver volumetry using watershed segmentation coupled with active contouring.
abstract: OBJECTIVE
  Our purpose is to develop a fully automated scheme for liver volume measurement in abdominal MR images, without requiring any user input or interaction.
  
  
  METHODS
  The proposed scheme is fully automatic for liver volumetry from 3D abdominal MR images, and it consists of three main stages: preprocessing, rough liver shape generation, and liver extraction. The preprocessing stage reduced noise and enhanced the liver boundaries in 3D abdominal MR images. The rough liver shape was revealed fully automatically by using the watershed segmentation, thresholding transform, morphological operations, and statistical properties of the liver. An active contour model was applied to refine the rough liver shape to precisely obtain the liver boundaries. The liver volumes calculated by the proposed scheme were compared to the "gold standard" references which were estimated by an expert abdominal radiologist.
  
  
  RESULTS
  The liver volumes computed by using our developed scheme excellently agreed (Intra-class correlation coefficient was 0.94) with the "gold standard" manual volumes by the radiologist in the evaluation with 27 cases from multiple medical centers. The running time was 8.4 min per case on average.
  
  
  CONCLUSIONS
  We developed a fully automated liver volumetry scheme in MR, which does not require any interaction by users. It was evaluated with cases from multiple medical centers. The liver volumetry performance of our developed system was comparable to that of the gold standard manual volumetry, and it saved radiologists' time for manual liver volumetry of 24.7 min per case.
authors.affiliation: Faculty of Information Technology, Industrial University of Ho Chi Minh City, Ho Chi Minh City, Vietnam. hthieu@ieee.org.
authors.forename: Hieu Trung
authors.identifier: http://orcid.org/0000-0002-2097-0704
authors.initials: HT
authors.lastname: Huynh
authors.affiliation: Faculty of Information Technology, Industrial University of Ho Chi Minh City, Ho Chi Minh City, Vietnam.|Faculty of Information Technology, University of Science, Ho Chi Minh City, Vietnam.
authors.forename: Ngoc
authors.initials: N
authors.lastname: Le-Trong
authors.affiliation: Faculty of Information Technology, University of Science, Ho Chi Minh City, Vietnam.|Faculty of Mathematics and Computer Science, University of Science, Ho Chi Minh City, Vietnam.
authors.forename: Pham The
authors.initials: PT
authors.lastname: Bao
authors.affiliation: Department of Radiology, The University of Chicago, Chicago, IL, 60637, USA.
authors.forename: Aytek
authors.initials: A
authors.lastname: Oto
authors.affiliation: Medical Imaging Research Center, Illinois Institute of Technology, Chicago, IL, 60616, USA.
authors.forename: Kenji
authors.initials: K
authors.lastname: Suzuki
mesh_terms: D001331:Automation; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008099:Liver / Q000000981:diagnostic imaging*; D016031:Liver Transplantation; D019520:Living Donors; D008279:Magnetic Resonance Imaging / Q000379:methods; D009929:Organ Size; D013997:Time Factors
keywords: Fully automated segmentation scheme; Liver volumetry; MR liver volumetry; Quantitative radiology; Transplantation