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Automated Decision Support for Bone Scintigraphy

Ohlsson, Mattias LU orcid ; Sjostrand, Karl ; Richter, Jens ; Kaboteh, Reza ; Sadik, May and Edenbrandt, Lars LU (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
; ; ; ; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
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
conference dates
2009-08-03 - 2009-08-04
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
2016-04-01 13:26:07
date last changed
2024-01-09 13:37:52
@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}},
  doi          = {{10.1109/CBMS.2009.5255270}},
  year         = {{2009}},
}