Bone-Cancer Assessment and Destruction Pattern Analysis in Long-Bone X-ray Image

J Digit Imaging. 2019 Apr;32(2):300-313. doi: 10.1007/s10278-018-0145-0.

Abstract

Bone cancer originates from bone and rapidly spreads to the rest of the body affecting the patient. A quick and preliminary diagnosis of bone cancer begins with the analysis of bone X-ray or MRI image. Compared to MRI, an X-ray image provides a low-cost diagnostic tool for diagnosis and visualization of bone cancer. In this paper, a novel technique for the assessment of cancer stage and grade in long bones based on X-ray image analysis has been proposed. Cancer-affected bone images usually appear with a variation in bone texture in the affected region. A fusion of different methodologies is used for the purpose of our analysis. In the proposed approach, we extract certain features from bone X-ray images and use support vector machine (SVM) to discriminate healthy and cancerous bones. A technique based on digital geometry is deployed for localizing cancer-affected regions. Characterization of the present stage and grade of the disease and identification of the underlying bone-destruction pattern are performed using a decision tree classifier. Furthermore, the method leads to the development of a computer-aided diagnostic tool that can readily be used by paramedics and doctors. Experimental results on a number of test cases reveal satisfactory diagnostic inferences when compared with ground truth known from clinical findings.

Keywords: Bone X-ray; Bone cancer; Connected component; Decision tree; Ortho-convex cover; Runs-test; Support vector machine.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Bone Neoplasms / diagnostic imaging*
  • Bone Neoplasms / pathology*
  • Humans
  • Magnetic Resonance Imaging
  • Neoplasm Grading
  • Neoplasm Staging
  • Radiographic Image Interpretation, Computer-Assisted / methods*
  • Support Vector Machine*
  • X-Rays