title: Optimum fuzzy filters for phase-contrast magnetic resonance imaging segmentation.
abstract: OBJECTIVE
  To develop and validate a multidimensional segmentation and filtering methodology for accurate blood flow velocity field reconstruction from phase-contrast magnetic resonance imaging (PC MRI).
  
  
  METHODS
  The proposed technique consists of two steps: (1) the boundary of the vessel is automatically segmented using the active contour approach; and (2) the noise embedded within the segmented vector field is selectively removed using a novel fuzzy adaptive vector median filtering (FAVMF) technique. This two-step segmentation process was tested and validated on 111 synthetically generated PC MRI slices and on 10 patients with congenital heart disease.
  
  
  RESULTS
  The active contour technique was effective for segmenting blood vessels having a sensitivity and specificity of 93.1% and 92.1% using manual segmentation as a reference standard. FAVMF was the superior technique in filtering out noise vectors, when compared with other commonly used filters in PC MRI (P < 0.05). The peak wall shear rate calculated from the PC MRI data (248 +/- 39 sec(-1)), was significantly decreased to (146 +/- 26 sec(-1)) after the filtering process.
  
  
  CONCLUSIONS
  The proposed two-step segmentation and filtering methodology is more accurate compared to a single-step segmentation process for post-processing of PC MRI data.
authors.affiliation: Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA.
authors.forename: Kartik S
authors.initials: KS
authors.lastname: Sundareswaran
authors.forename: David H
authors.initials: DH
authors.lastname: Frakes
authors.forename: Mark A
authors.initials: MA
authors.lastname: Fogel
authors.forename: Dennis D
authors.initials: DD
authors.lastname: Soerensen
authors.forename: John N
authors.initials: JN
authors.lastname: Oshinski
authors.forename: Ajit P
authors.initials: AP
authors.lastname: Yoganathan
mesh_terms: D000465:Algorithms; D003326:Coronary Circulation / Q000502:physiology*; D003331:Coronary Vessels / Q000033:anatomy & histology / Q000502:physiology*; D017143:Fuzzy Logic; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D018810:Magnetic Resonance Angiography / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted