Automated Decision Support for Bone Scintigraphy

Mattias Ohlsson, Karl Sjostrand, Jens Richter, Reza Kaboteh, May Sadik, Lars Edenbrandt

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceedingpeer-review


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.
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
Publication statusPublished - 2009
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

Subject classification (UKÄ)

  • Radiology, Nuclear Medicine and Medical Imaging


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