Automated Decision Support for Bone Scintigraphy

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceeding


A quantitative analysis of metastatic bone involvement can be an important prognostic indicator of survival or a tool in monitoring treatment response in patients with cancer The purpose of this study was to develop a completely automated decision support system for whole-body bone scans using image analysis and artificial neural networks. The study population consisted of 795 whole-body bone scans. The decision support system first detects and classifies individual hotspots as being metastatic or not. A second prediction model then classifies the scan regarding metastatic disease on a patient level. The test set sensitivity and specificity was 95% and 64% respectively, corresponding to 95% area under the receiver operating characteristics curve.


  • Mattias Ohlsson
  • Karl Sjostrand
  • Jens Richter
  • Reza Kaboteh
  • May Sadik
  • Lars Edenbrandt
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Radiology, Nuclear Medicine and Medical Imaging
Original languageEnglish
Title of host publication2009 22nd IEEE International Symposium on Computer-Based Medical Systems
PublisherIEEE--Institute of Electrical and Electronics Engineers Inc.
ISBN (Print)978-1-4244-4879-1
StatePublished - 2009
Publication categoryResearch
Event22nd IEEE International Symposium on Computer-Based Medical Systems - Albuquerque, NM
Duration: 2009 Aug 32009 Aug 4

Publication series

ISSN (Print)1063-7125


Conference22nd IEEE International Symposium on Computer-Based Medical Systems