Automatic lower limb bone segmentation in radiographs with different orientations and fields of view based on a contextual network.

Journal: International journal of computer assisted radiology and surgery
Published Date:

Abstract

PURPOSE: Bone identification and segmentation in X-ray images are crucial in orthopedics for the automation of clinical procedures, but it often involves some manual operations. In this work, using a modified SegNet neural network, we automatically identify and segment lower limb bone structures on radiographs presenting various fields of view and different patient orientations.

Authors

  • Roseline Olory Agomma
    Laboratoire de recherche en imagerie et orthopédie, 900 Saint-Denis Street, Montreal, QC, Canada. roseline.olory-agomma.1@ens.etsmtl.ca.
  • Thierry Cresson
    Laboratoire de recherche en imagerie et orthopédie, 900 Saint-Denis Street, Montreal, QC, Canada.
  • Jacques de Guise
    Laboratoire de recherche en imagerie et orthopédie, 900 Saint-Denis Street, Montreal, QC, Canada.
  • Carlos Vazquez
    Laboratoire de recherche en imagerie et orthopédie, 900 Saint-Denis Street, Montreal, QC, Canada.