Detection of breast cancer using machine learning on time-series diffuse optical transillumination data.

Journal: Journal of biomedical optics

PMID: 39529875

Abstract

SIGNIFICANCE: Optical mammography as a promising tool for cancer diagnosis has largely fallen behind expectations. Modern machine learning (ML) methods offer ways to improve cancer detection in diffuse optical transmission data.

Authors

Nils Harnischmacher

HTW - University of Applied Sciences Berlin, Faculty II, KI-Werkstatt, Berlin, Germany.
Erik Rodner

Computer Vision Group, Friedrich-Schiller-Universität Jena, Jena, Germany.
Christoph H Schmitz

HTW - University of Applied Sciences Berlin, Faculty I - Health Electronics, Biomedical Electronics and Applied Research (BEAR) Labs, Berlin, Germany.

Keywords

Area Under Curve Breast Breast Neoplasms Female Humans Image Interpretation, Computer-Assisted Image Processing, Computer-Assisted Machine Learning Optical Imaging ROC Curve Support Vector Machine Transillumination

External Resources

View on PubMed Access via DOI PubMed (39529875)

Detection of breast cancer using machine learning on time-series diffuse optical transillumination data.

Abstract

Authors

Keywords

External Resources

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