Quantitative Ultrasound of Tumor Surrounding Tissue for Enhancement of Breast Cancer Diagnosis

  • Ziemowit KlimondaEmail author
  • Katarzyna Dobruch-Sobczak
  • Hanna Piotrzkowska-Wróblewska
  • Piotr Karwat
  • Jerzy Litniewski
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10814)


Breast cancer is one of the leading causes of cancer-related death in female patients. The quantitative ultrasound techniques being developed recently provide useful information facilitating the classification of tumors as malignant or benign. Quantitative parameters are typically determined on the basis of signals scattered within the tumor. The present paper demonstrates the utility of quantitative data estimated based on signal backscatter in the tissue surrounding the tumor. Two quantitative parameters, weighted entropy and Nakagami shape parameter were calculated from the backscatter signal envelope. The ROC curves and the AUC parameter values were used to assess their ability to classify neoplastic lesions. Results indicate that data from tissue surrounding the tumor may characterize it better than data from within the tumor. AUC values were on average 18% higher for parameters calculated from data collected from the tissue surrounding the lesion than from the data from the lesion itself.


Quantitative ultrasound Tissue characterisation Tumor classification 



This study was supported by the National Science Centre, Poland, grants 2016/23/B/ST8/03391, 2016/21/N/ST7/03029 and 2014/13/B/ST7/01271. The project was implemented using the infrastructure of CePT, Operational Program “Innovative economy” for 2007–2013.


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Institute of Fundamental Technological ResearchPASWarsawPoland
  2. 2.Maria Skłodowska-Curie Memorial Cancer Centre and Institute of OncologyWarsawPoland

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