Automated decision support for bone scintigraphy
Publication: Research - peer-review › Article in proceedings – Annual report year: 2009
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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 language | English |
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| Title | Proceedings - IEEE Symposium on Computer-Based Medical Systems |
| Number of pages | 5255270 |
| Publisher | IEEE |
| Publication date | 2009 |
| ISBN (print) | 9781424448784 |
| DOIs | |
| State | Published |
Conference
| Conference | 2009 22nd IEEE International Symposium on Computer-Based Medical Systems |
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| Period | 01/01/09 → … |
| Citations | Web of Science® Times Cited: No match on DOI |
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