title: Semi-automatic segmentation software for quantitative clinical brain glioblastoma evaluation.
abstract: OBJECTIVE
  Quantitative measurement provides essential information about disease progression and treatment response in patients with glioblastoma multiforme (GBM). The goal of this article is to present and validate a software pipeline for semi-automatic GBM segmentation, called AFINITI (Assisted Follow-up in NeuroImaging of Therapeutic Intervention), using clinical data from GBM patients.
  
  
  METHODS
  Our software adopts the current state-of-the-art tumor segmentation algorithms and combines them into one clinically usable pipeline. Both the advantages of the traditional voxel-based and the deformable shape-based segmentation are embedded into the software pipeline. The former provides an automatic tumor segmentation scheme based on T1- and T2-weighted magnetic resonance (MR) brain data, and the latter refines the segmentation results with minimal manual input.
  
  
  RESULTS
  Twenty-six clinical MR brain images of GBM patients were processed and compared with manual results. The results can be visualized using the embedded graphic user interface.
  
  
  CONCLUSIONS
  Validation results using clinical GBM data showed high correlation between the AFINITI results and manual annotation. Compared to the voxel-wise segmentation, AFINITI yielded more accurate results in segmenting the enhanced GBM from multimodality MR imaging data. The proposed pipeline could be used as additional information to interpret MR brain images in neuroradiology.
authors.affiliation: Department of Systems Medicine and Bioengineering, The Methodist Hospital Research Institute, Weill Cornell Medical College, Houston, TX, USA.
authors.forename: Ying
authors.initials: Y
authors.lastname: Zhu
authors.forename: Geoffrey S
authors.initials: GS
authors.lastname: Young
authors.forename: Zhong
authors.initials: Z
authors.lastname: Xue
authors.forename: Raymond Y
authors.initials: RY
authors.lastname: Huang
authors.forename: Hui
authors.initials: H
authors.lastname: You
authors.forename: Kian
authors.initials: K
authors.lastname: Setayesh
authors.forename: Hiroto
authors.initials: H
authors.lastname: Hatabu
authors.forename: Fei
authors.initials: F
authors.lastname: Cao
authors.forename: Stephen T
authors.initials: ST
authors.lastname: Wong
mesh_terms: D000465:Algorithms; D001932:Brain Neoplasms / Q000473:pathology*; D005909:Glioblastoma / Q000473:pathology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012984:Software; D012986:Software Validation; D013382:Subtraction Technique