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

  • Matilda Landgren
  • Karl Sjöstrand
  • Mattias Ohlsson
  • Daniel Ståhl
  • Niels Christian Overgaard
  • Kalle Åström
  • Rune Sixt
  • Lars Edenbrandt
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6688)

Abstract

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.

Keywords

Computer Aided Diagnosis Nuclear Imaging Active Shape Models Artificial Neural Networks 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Matilda Landgren
    • 1
    • 2
  • Karl Sjöstrand
    • 1
    • 3
  • Mattias Ohlsson
    • 1
    • 4
  • Daniel Ståhl
    • 1
    • 2
  • Niels Christian Overgaard
    • 2
  • Kalle Åström
    • 2
  • Rune Sixt
    • 5
  • Lars Edenbrandt
    • 1
  1. 1.EXINI Diagnostics ABLundSweden
  2. 2.Centre for Mathematical SciencesLund UniversityLundSweden
  3. 3.Department of Informatics and Mathematical ModellingTechnical University of DenmarkKgs. LyngbyDenmark
  4. 4.Department of Theoretical PhysicsLund UniversityLundSweden
  5. 5.Queen Silvia Children’s HospitalGöteborgSweden

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