title: A new automatic algorithm to extract craniofacial measurements from fetal three-dimensional volumes.
abstract: OBJECTIVE
  Three-dimensional (3D) ultrasound is useful in the prenatal evaluation of fetal craniofacial structures, particularly as it provides a multiplanar view. However, an expert must designate the area of interest and the appropriate view, making measurement of fetal structures using 3D ultrasound both time-consuming and subjective. In this study we propose an image analysis system that measures automatically and precisely the fetal craniofacial structures and evaluate its performance in the second trimester of pregnancy using a new 3D volume analysis algorithm.
  
  
  METHODS
  A universal facial surface template model containing the geometric shape information of a fetal craniofacial structure was constructed from a fetal phantom. Using the proposed image analysis system we fitted this stored template model using a model deformation approach to individual fetal 3D facial volumes from 11 mid-trimester fetuses, and extracted automatically the following standard measurements: biparietal diameter (BPD), occipitofrontal diameter (OFD), interorbital diameter (IOD), bilateral orbital diameter (BOD) and distance between vertex and nasion (VN). The same five parameters were measured manually by an expert and the results compared.
  
  
  RESULTS
  Comparison of the algorithm-based automatic measurements with manual measurements made by an expert gave correlation coefficients of 0.99 for BPD, 0.98 for OFD, 0.80 for BOD, 0.83 for IOD and 0.99 for VN. There were no significant differences between automatic and manual measurements.
  
  
  CONCLUSIONS
  Our proposed system measures precisely the fetal craniofacial structures using 3D ultrasound, making it potentially useful for clinical service. This system could also be applied to other clinical fields in future testing.
authors.affiliation: Department of Obstetrics and Gynecology, National Cheng Kung University Medical College and Hospital, Tainan, Taiwan.
authors.forename: P-Y
authors.initials: PY
authors.lastname: Tsai
authors.forename: H-C
authors.initials: HC
authors.lastname: Chen
authors.forename: H-H
authors.initials: HH
authors.lastname: Huang
authors.forename: C-H
authors.initials: CH
authors.lastname: Chang
authors.forename: P-S
authors.initials: PS
authors.lastname: Fan
authors.forename: C-I
authors.initials: CI
authors.lastname: Huang
authors.forename: Y-C
authors.initials: YC
authors.lastname: Cheng
authors.forename: F-M
authors.initials: FM
authors.lastname: Chang
authors.forename: Y-N
authors.initials: YN
authors.lastname: Sun
mesh_terms: D000465:Algorithms; D005145:Face / Q000000981:diagnostic imaging* / Q000473:pathology; D005260:Female; D005865:Gestational Age; D006257:Head / Q000000981:diagnostic imaging* / Q000473:pathology; D006801:Humans; D021621:Imaging, Three-Dimensional; D010363:Pattern Recognition, Automated; D011247:Pregnancy; D011262:Pregnancy Trimester, Second; D012016:Reference Values; D015203:Reproducibility of Results; D016216:Ultrasonography, Prenatal / Q000379:methods*