Automated decision support for bone scintigraphy

Publication: Research - peer-reviewArticle in proceedings – Annual report year: 2009

Without internal affiliation

  • Author: Ohlsson, M.

  • Author: Kaboteh, R.

  • Author: Sadik, M.

  • Author: Suurkula, M.

  • Author: Lomsky, M.

  • Author: Gjertsson, P.

  • Author: Sjöstrand, Karl

    EXINI Diagnostics AB

  • Author: Richter, J.

  • Author: Edenbrandt, L.

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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
StatePublished - 2009
Externally publishedYes
Event2009 22nd IEEE International Symposium on Computer-Based Medical Systems -


Conference2009 22nd IEEE International Symposium on Computer-Based Medical Systems
Period01/01/2009 → …
CitationsWeb of Science® Times Cited: No match on DOI
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ID: 5670689