Automated decision support for bone scintigraphy

M. Ohlsson, R. Kaboteh, M. Sadik, M. Suurkula, M. Lomsky, P. Gjertsson, Karl Sjöstrand, J. Richter, L. Edenbrandt

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-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. ©2009 IEEE.
Original languageEnglish
Title of host publicationProceedings - IEEE Symposium on Computer-Based Medical Systems
Number of pages5255270
Publication date2009
ISBN (Print)9781424448784
Publication statusPublished - 2009
Externally publishedYes
Event2009 22nd IEEE International Symposium on Computer-Based Medical Systems -
Duration: 1 Jan 2009 → …


Conference2009 22nd IEEE International Symposium on Computer-Based Medical Systems
Period01/01/2009 → …


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