Diagnostic performance of machine learning applied to texture analysis-derived features for breast lesion characterisation at automated breast ultrasound: a pilot study

BACKGROUND: Our aims were to determine if features derived from texture analysis (TA) can distinguish normal, benign, and malignant tissue on automated breast ultrasound (ABUS); to evaluate whether machine learning (ML) applied to TA can categorise ABUS findings; and to compare ML to the analysis of...

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Detalles Bibliográficos
Autores principales: Marcon, Magda, Ciritsis, Alexander, Rossi, Cristina, Becker, Anton S., Berger, Nicole, Wurnig, Moritz C., Wagner, Matthias W., Frauenfelder, Thomas, Boss, Andreas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2019
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6825080/
https://www.ncbi.nlm.nih.gov/pubmed/31676937
http://dx.doi.org/10.1186/s41747-019-0121-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6825080/
https://www.ncbi.nlm.nih.gov/pubmed/31676937
http://dx.doi.org/10.1186/s41747-019-0121-6

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