Multiparametric deep learning tissue signatures for a radiological biomarker of breast cancer: Preliminary results

PURPOSE: Deep learning is emerging in radiology due to the increased computational capabilities available to reading rooms. These computational developments have the ability to mimic the radiologist and may allow for more accurate tissue characterization of normal and pathological lesion tissue to a...

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Detalles Bibliográficos
Autores principales: Parekh, Vishwa S., Macura, Katarzyna J., Harvey, Susan C., Kamel, Ihab R., EI‐Khouli, Riham, Bluemke, David A., Jacobs, Michael A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
QUANTITATIVE IMAGING AND IMAGE PROCESSING
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7003775/
https://www.ncbi.nlm.nih.gov/pubmed/31598978
http://dx.doi.org/10.1002/mp.13849

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7003775/
https://www.ncbi.nlm.nih.gov/pubmed/31598978
http://dx.doi.org/10.1002/mp.13849

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