title: Automatic detection of arterial input function in dynamic contrast enhanced MRI based on affinity propagation clustering.
abstract: OBJECTIVE
  To automatically and robustly detect the arterial input function (AIF) with high detection accuracy and low computational cost in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).
  
  
  METHODS
  In this study, we developed an automatic AIF detection method using an accelerated version (Fast-AP) of affinity propagation (AP) clustering. The validity of this Fast-AP-based method was proved on two DCE-MRI datasets, i.e., rat kidney and human head and neck. The detailed AIF detection performance of this proposed method was assessed in comparison with other clustering-based methods, namely original AP and K-means, as well as the manual AIF detection method.
  
  
  RESULTS
  Both the automatic AP- and Fast-AP-based methods achieved satisfactory AIF detection accuracy, but the computational cost of Fast-AP could be reduced by 64.37-92.10% on rat dataset and 73.18-90.18% on human dataset compared with the cost of AP. The K-means yielded the lowest computational cost, but resulted in the lowest AIF detection accuracy. The experimental results demonstrated that both the AP- and Fast-AP-based methods were insensitive to the initialization of cluster centers, and had superior robustness compared with K-means method.
  
  
  CONCLUSIONS
  The Fast-AP-based method enables automatic AIF detection with high accuracy and efficiency.
authors.affiliation: Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, NT, Hong Kong SAR, P.R. China; Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, P.R. China.
authors.forename: Lin
authors.initials: L
authors.lastname: Shi
authors.forename: Defeng
authors.initials: D
authors.lastname: Wang
authors.forename: Wen
authors.initials: W
authors.lastname: Liu
authors.forename: Kui
authors.initials: K
authors.lastname: Fang
authors.forename: Yi-Xiang J
authors.initials: YX
authors.lastname: Wang
authors.forename: Wenhua
authors.initials: W
authors.lastname: Huang
authors.forename: Ann D
authors.initials: AD
authors.lastname: King
authors.forename: Pheng Ann
authors.initials: PA
authors.lastname: Heng
authors.forename: Anil T
authors.initials: AT
authors.lastname: Ahuja
mesh_terms: D000465:Algorithms; D000818:Animals; D001158:Arteries / Q000033:anatomy & histology / Q000502:physiology*; D001783:Blood Flow Velocity / Q000502:physiology; D003198:Computer Simulation; D006571:Heterocyclic Compounds / Q000493:pharmacokinetics*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D021621:Imaging, Three-Dimensional / Q000379:methods; D007668:Kidney / Q000098:blood supply; D018810:Magnetic Resonance Angiography / Q000379:methods*; D008954:Models, Biological; D009942:Organometallic Compounds / Q000493:pharmacokinetics*; D010363:Pattern Recognition, Automated / Q000379:methods*; D051381:Rats; D012079:Renal Circulation / Q000502:physiology; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
chemical_list: D006571:Heterocyclic Compounds; D009942:Organometallic Compounds; C050823:gadolinium 1,4,7,10-tetraazacyclododecane-N,N',N'',N'''-tetraacetate
keywords: K-means clustering; affinity propagation clustering; arterial input function; dynamic contrast enhanced magnetic resonance imaging