BUS-Set: A benchmark for quantitative evaluation of breast ultrasound segmentation networks with public datasets.

Journal: Medical physics

Published Date: Feb 28, 2023

Abstract

PURPOSE: BUS-Set is a reproducible benchmark for breast ultrasound (BUS) lesion segmentation, comprising of publicly available images with the aim of improving future comparisons between machine learning models within the field of BUS.

Authors

Cory Thomas

Department of Computer Science, Aberystwyth University, Aberystwyth, UK.
Michał Byra

Department of Ultrasound, Institute of Fundamental Technological Research, Polish Academy of Sciences, Pawińskiego 5B, 02-106, Warsaw, Poland. mbyra@ippt.pan.pl.
Robert Marti
Moi Hoon Yap
Reyer Zwiggelaar

Department of Computer Science, Aberystwyth University, Ceredigion, United Kingdom.

Keywords

Benchmarking Female Humans Image Processing, Computer-Assisted Machine Learning Neural Networks, Computer Ultrasonography, Mammary

External Resources

View on PubMed Access via DOI PubMed (36794706)

BUS-Set: A benchmark for quantitative evaluation of breast ultrasound segmentation networks with public datasets.

Abstract

Authors

Keywords

External Resources

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