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Wilms’ Tumor in Childhood: Can Pattern Recognition Help for Classification?

  • Sabine MüllerEmail author
  • Joachim Weickert
  • Norbert Graf
Conference paper
  • 107 Downloads
Part of the Communications in Computer and Information Science book series (CCIS, volume 1065)

Abstract

Wilms’ tumor or nephroblastoma is a kidney tumor and the most common renal malignancy in childhood. Clinicians assume that these tumors develop from embryonic renal precursor cells - sometimes via nephrogenic rests or nephroblastomatosis. In Europe, chemotherapy is carried out prior to surgery, which downstages the tumor. This results in various pathological subtypes with differences in their prognosis and treatment.

First, we demonstrate that the classical distinction between nephroblastoma and its precursor lesion is error prone with an accuracy of 0.824. We tackle this issue with appropriate texture features and improve the classification accuracy to 0.932.

Second, we are the first to predict the development of nephroblastoma under chemotherapy. We use a bag of visual model and show that visual clues are present that help to approximate the developing subtype.

Last but not least, we provide our data set of 54 kidneys with nephroblastomatosis in conjunction with 148 Wilms’ tumors.

Notes

Acknowledgements

J. Weickert has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 741215, ERC Advanced Grant INCOVID).

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Sabine Müller
    • 1
    • 2
    Email author
  • Joachim Weickert
    • 2
  • Norbert Graf
    • 1
  1. 1.Department of Pediatric Oncology and HematologySaarland University Medical CenterHomburgGermany
  2. 2.Mathematical Image Analysis GroupSaarland UniversitySaarbrückenGermany

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