title: Ultrasound B-scan image simulation, segmentation, and analysis of the equine tendon.
abstract: OBJECTIVE
  The hypothesis is that an imaging technique based on decompression and segmentation of B-scan images with morphological operators can provide a measurement of the integrity of equine tendons.
  
  
  METHODS
  Two complementary approaches were used: (i) Simulation of B-scan images to better understand the relationship between image properties and their underlying biological structural contents and (ii) extraction and quantification from B-scan images of tendon structures identified in step (i) to diagnose the status of the superficial digital flexor tendon (SDFT) by using the proposed imaging technique.
  
  
  RESULTS
  The simulation results revealed that the interfascicular spaces surrounding fiber fascicle bundles were the source of ultrasound reflection and scattering. By extracting these fascicle bundles with the proposed imaging technique, quantitative results from clinical B-scan images of eight normal and five injured SDFTs revealed significant differences in fiber bundle number and areas: mean values were 50 (+/- 11) and 1.33(+/- 0.36) mm2 for the normal SDFT data set. Different values were observed for injured SDFTs where the intact mean fiber bundle number decreased to 40 (+/- 7) (p = 0.016); inversely, mean fiber bundle areas increased to 1.83 (+/- 0.25) mm2 (p = 0.008), which indicate disruption of the thinnest interfascicular spaces and of their corresponding fiber fascicle bundles where lesions occurred.
  
  
  CONCLUSIONS
  To conclude, this technique may provide a tool for the rapid assessment and characterization of tendon structures to enable clinical identification of the integrity of the SDFT.
authors.affiliation: Laboratoire de Recherche en Imagerie et Orthopédic, University of Montreal Hospital (CRCHUM), Montréal, Québec H2L 2W5, Canada. ali.meghoufel@etsmtl.ca
authors.forename: Ali
authors.initials: A
authors.lastname: Meghoufel
authors.forename: Guy
authors.initials: G
authors.lastname: Cloutier
authors.forename: Nathalie
authors.initials: N
authors.lastname: Crevier-Denoix
authors.forename: Jacques A
authors.initials: JA
authors.lastname: de Guise
mesh_terms: D000465:Algorithms; D000818:Animals; D001185:Artificial Intelligence; D003198:Computer Simulation; D006736:Horses; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008954:Models, Biological; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013710:Tendons / Q000000981:diagnostic imaging* / Q000502:physiology*; D014463:Ultrasonography