A global unimodal thresholding based on probabilistic reference maps for the segmentation of muscle images
作者: Laurence Sifre-MaunierRichard G. TaylorPhilippe BergeJoseph CulioliJean-Marie Bonny
作者单位: 1INRA, Meat Research Unit, Centre de Theix, 63122 Saint Genes Champanelle, France
刊名: Image and Vision Computing, 2006, Vol.24 (10), pp.1080-1089
来源数据库: Elsevier Journal
DOI: 10.1016/j.imavis.2006.03.004
关键词: Unimodal thresholdingSegmentationMuscle
英文摘要: Abstract(#br)A global probabilistic maps thresholding (PMT) method was applied to characterise intramuscular connective tissue (IMCT) distribution on images of muscle histological sections exhibiting unimodal histograms. Probabilistic reference maps were defined and then used to set-up thresholding rules, derived from linear combinations of parameters calculated from the intensity histogram of the images. This PMT method was objectively compared to Rosin's unimodal thresholding algorithm (RT) and validated by a histochemical quantification of IMCT collagen. Morphometrical parameters of the IMCT (area, length and thickness of the extracted network) were determined for different muscles and used to quantify IMCT distribution differences.
全文获取路径: Elsevier  (合作)
影响因子:1.959 (2012)

  • thresholding 阈值
  • segmentation 分段
  • probabilistic 概率的
  • unimodal 单峰的
  • reference 基准电压源
  • global 球状的
  • based 基于
  • muscle 肌肉