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Automated Decision Support for Bone Scintigraphy

Ohlsson, Mattias LU ; Sjostrand, Karl; Richter, Jens; Kaboteh, Reza; Sadik, May and Edenbrandt, Lars LU (2009) 22nd IEEE International Symposium on Computer-Based Medical Systems In 2009 22nd IEEE International Symposium on Computer-Based Medical Systems p.298-303
Abstract
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... (More)
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. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
in
2009 22nd IEEE International Symposium on Computer-Based Medical Systems
pages
298 - 303
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
22nd IEEE International Symposium on Computer-Based Medical Systems
external identifiers
  • wos:000278974800049
  • scopus:70449638283
ISSN
1063-7125
ISBN
978-1-4244-4879-1
DOI
10.1109/CBMS.2009.5255270
language
English
LU publication?
yes
id
3f1f189a-b2ea-4a28-ae09-83b2437dc257 (old id 1628617)
date added to LUP
2010-07-23 09:46:50
date last changed
2017-06-11 04:04:12
@inproceedings{3f1f189a-b2ea-4a28-ae09-83b2437dc257,
  abstract     = {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.},
  author       = {Ohlsson, Mattias and Sjostrand, Karl and Richter, Jens and Kaboteh, Reza and Sadik, May and Edenbrandt, Lars},
  booktitle    = {2009 22nd IEEE International Symposium on Computer-Based Medical Systems},
  isbn         = {978-1-4244-4879-1},
  issn         = {1063-7125},
  language     = {eng},
  pages        = {298--303},
  publisher    = {IEEE--Institute of Electrical and Electronics Engineers Inc.},
  title        = {Automated Decision Support for Bone Scintigraphy},
  url          = {http://dx.doi.org/10.1109/CBMS.2009.5255270},
  year         = {2009},
}