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.
|Title of host publication||Proceedings - IEEE Symposium on Computer-Based Medical Systems|
|Number of pages||5255270|
|Publication status||Published - 2009|
|Event||2009 22nd IEEE International Symposium on Computer-Based Medical Systems - |
Duration: 1 Jan 2009 → …
|Conference||2009 22nd IEEE International Symposium on Computer-Based Medical Systems|
|Period||01/01/2009 → …|