A CAD System for Long-Bone Segmentation and Fracture Detection

  • Authors:
  • Martin Donnelley;Greg Knowles;Trevor Hearn

  • Affiliations:
  • Flinders University, Adelaide, South Australia 5001;Flinders University, Adelaide, South Australia 5001;Flinders University, Adelaide, South Australia 5001

  • Venue:
  • ICISP '08 Proceedings of the 3rd international conference on Image and Signal Processing
  • Year:
  • 2008

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Abstract

Medical imaging has advanced at a tremendous rate since x-rays were discovered in 1895. Today, x-ray machines produce extremely high-quality images for radiologists to interpret. However, the methods of interpretation have only recently begun to be augmented by advances in computer technology. Computer aided diagnosis (CAD) systems that guide healthcare professionals in making the correct diagnosis are slowly becoming more prevalent throughout the medical field. Detection of long-bone fractures is an important orthopaedic and radiologic problem, and it is proposed that a novel CAD system could help reduce the number of fractures missed during x-ray diagnosis. A number of image processing software algorithms useful for assisting the fracture detection process are described, and their accuracy evaluated on a database of fracture images from trauma patients. Incorporating these methods will further expand the capabilities of today's CAD systems, and result in more accurate diagnosis of fractures and a reduction of the fracture miss rate.