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Portrait of Anders Tingberg. Photo

Anders Tingberg

Associate professor

Portrait of Anders Tingberg. Photo

AI lesion risk score at different exposure settings

Author

  • Anders Tingberg
  • Victor Dahlblom
  • Predrag Bakic
  • Haiko Schurz
  • Fredrik Strand
  • Sophia Zackrisson
  • Magnus Dustler

Editor

  • Maryellen L. Giger
  • Heather M. Whitney
  • Karen Drukker
  • Hui Li

Summary, in English

Purpose: The purpose of this study was to investigate whether the lesion risk score provided by an AI system is influenced by the selection of exposure parameters. Methods: A breast phantom which contains a lesion, was imaged with digital mammography with different imaging conditions. The tube voltage, the dose level and the anode-filter combination were varied based on an exposure obtained with automatic exposure control. The organ dose for each image was extracted from the DICOM header. The images were analyzed with an AI system, which provided a lesion risk score (suspicion for malignancy) for each exposure condition. Correlations between the lesion risk score and the exposure conditions were investigated. Results: The results of the study showed that the organ dose had a strong impact on the lesion risk score. Reducing the organ dose to a low level resulted in that the AI system no longer detected the lesion. Conclusions: Images of suboptimal quality may result in inaccurate AI system performance. In our preliminary analysis, the breast phantom and the lesion were proven to be realistic enough for being analyzed by the AI system.

Department/s

  • LUCC: Lund University Cancer Centre
  • Medical Radiation Physics, Malmö
  • Radiology Diagnostics, Malmö
  • LTH Profile Area: Photon Science and Technology
  • EpiHealth: Epidemiology for Health

Publishing year

2024

Language

English

Publication/Series

Proceedings of SPIE - The International Society for Optical Engineering

Volume

13174

Document type

Conference paper

Publisher

SPIE

Topic

  • Radiology, Nuclear Medicine and Medical Imaging

Keywords

  • Artificial intelligence
  • Breast organ dose
  • Breast phantom
  • Digital mammography
  • Image quality
  • Suspicion for malignancy

Conference name

17th International Workshop on Breast Imaging, IWBI 2024

Conference date

2024-06-09 - 2024-06-12

Conference place

Chicago, United States

Status

Published

Research group

  • Medical Radiation Physics, Malmö
  • Radiology Diagnostics, Malmö

ISBN/ISSN/Other

  • ISSN: 0277-786X
  • ISSN: 1996-756X
  • ISBN: 9781510680203