title: A novel alternative to classify tissues from T 1 and T 2 relaxation times for prostate MRI.
abstract: OBJECTIVE
  To segment and classify the different attenuation regions from MRI at the pelvis level using the T 1 and T 2 relaxation times and anatomical knowledge as a first step towards the creation of PET/MR attenuation maps.
  
  
  METHODS
  Relaxation times were calculated by fitting the pixel-wise intensities of acquired T 1- and T 2-weighted images from eight men with inversion-recovery and multi-echo multi-slice spin-echo sequences. A decision binary tree based on relaxation times was implemented to segment and classify fat, muscle, prostate, and air (within the body). Connected component analysis and an anatomical knowledge-based procedure were implemented to localize the background and bone.
  
  
  RESULTS
  Relaxation times at 3 T are reported for fat (T 1 = 385 ms, T 2 = 121 ms), muscle (T 1 = 1295 ms, T 2 = 40 ms), and prostate (T 1 = 1700 ms, T 2 = 80 ms). The relaxation times allowed the segmentation-classification of fat, prostate, muscle, and air, and combined with anatomical knowledge, they allowed classification of bone. The good segmentation-classification of prostate [mean Dice similarity score (mDSC) = 0.70] suggests a viable implementation in oncology and that of fat (mDSC = 0.99), muscle (mDSC = 0.99), and bone (mDSCs = 0.78) advocates for its implementation in PET/MR attenuation correction.
  
  
  CONCLUSIONS
  Our method allows the segmentation and classification of the attenuation-relevant structures required for the generation of the attenuation map of PET/MR systems in prostate imaging: air, background, bone, fat, muscle, and prostate.
authors.affiliation: LE2I, UMR 6306, CNRS, Arts et Métiers, Université Bourgogne Franche-Comté, 21000, Dijon, France. Jorge-Arturo.Zavala-Bojorquez@u-bourgogne.fr.
authors.forename: Jorge Zavala
authors.initials: JZ
authors.lastname: Bojorquez
authors.affiliation: LE2I, UMR 6306, CNRS, Arts et Métiers, Université Bourgogne Franche-Comté, 21000, Dijon, France.
authors.forename: Stéphanie
authors.initials: S
authors.lastname: Bricq
authors.affiliation: LE2I, UMR 6306, CNRS, Arts et Métiers, Université Bourgogne Franche-Comté, 21000, Dijon, France.
authors.forename: François
authors.initials: F
authors.lastname: Brunotte
authors.affiliation: LE2I, UMR 6306, CNRS, Arts et Métiers, Université Bourgogne Franche-Comté, 21000, Dijon, France.
authors.forename: Paul M
authors.initials: PM
authors.lastname: Walker
authors.affiliation: LE2I, UMR 6306, CNRS, Arts et Métiers, Université Bourgogne Franche-Comté, 21000, Dijon, France.
authors.forename: Alain
authors.initials: A
authors.lastname: Lalande
mesh_terms: D000465:Algorithms; D016477:Artifacts; D003663:Decision Trees; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging; D008297:Male; D009132:Muscles / Q000000981:diagnostic imaging; D049268:Positron-Emission Tomography; D011467:Prostate / Q000000981:diagnostic imaging*; D011471:Prostatic Neoplasms / Q000000981:diagnostic imaging*; D013997:Time Factors
keywords: Attenuation correction; Classification; MRI; Prostate; T 1 and T 2 relaxation times