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Mattias Ohlsson

Mattias Ohlsson

Professor

Mattias Ohlsson

An Automated System for the Detection and Diagnosis of Kidney Lesions in Children from Scintigraphy Images

Author

  • Matilda Landgren
  • Karl Sjöstrand
  • Mattias Ohlsson
  • Daniel Ståhl
  • Niels Christian Overgaard
  • Karl Åström
  • Rune Sixt
  • Lars Edenbrandt

Editor

  • Anders Heyden
  • Fredrik Kahl

Summary, in English

Designing a system for computer aided diagnosis is a complex procedure requiring an understanding of the biology of the disease, insight into hospital workflow and awareness of available technical solutions. This paper aims to show that a valuable system can be designed for diagnosing kidney lesions in children and adolescents from 99m Tc-DMSA scintigraphy images. We present the chain of analysis and provide a discussion of its performance. On a per-lesion basis, the classification reached an ROC-curve area of 0.96 (sensitivity/specificity e.g. 97%/85%) measured using an independent test group consisting of 56 patients with 730 candidate lesions. We conclude that the presented system for diagnostic support has the potential of increasing the quality of care regarding this type of examination.

Department/s

  • Mathematics (Faculty of Engineering)
  • Computational Biology and Biological Physics
  • Nuclear medicine, Malmö
  • Mathematical Imaging Group
  • ELLIIT: the Linköping-Lund initiative on IT and mobile communication
  • eSSENCE: The e-Science Collaboration

Publishing year

2011

Language

English

Pages

489-500

Publication/Series

Lecture Notes in Computer Science

Volume

6688

Document type

Conference paper

Publisher

Springer

Topic

  • Mathematics
  • Computer Vision and Robotics (Autonomous Systems)

Keywords

  • Computer Aided Diagnosis – Nuclear Imaging – Active Shape Models – Artificial Neural Networks

Conference name

17th Scandinavian Conference on Image Analysis (SCIA 2011)

Conference date

2011-05-23 - 2011-05-27

Conference place

Ystad, Sweden

Status

Published

Research group

  • Nuclear medicine, Malmö
  • Mathematical Imaging Group

ISBN/ISSN/Other

  • ISSN: 0302-9743
  • ISSN: 1611-3349
  • ISBN: 978-3-642-21227-7 (online)
  • ISBN: 978-3-642-21226-0 (print)