Computerized Prediction of Radiological Observations Based on Quantitative Feature Analysis: Initial Experience in Liver Lesions

We propose a computerized framework that, given a region of interest (ROI) circumscribing a lesion, not only predicts radiological observations related to the lesion characteristics with 83.2% average prediction accuracy but also derives explicit association between low-level imaging features and hi...

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Detalles Bibliográficos
Autores principales: Banerjee, Imon, Beaulieu, Christopher F., Rubin, Daniel L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2017
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5537098/
https://www.ncbi.nlm.nih.gov/pubmed/28639186
http://dx.doi.org/10.1007/s10278-017-9987-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5537098/
https://www.ncbi.nlm.nih.gov/pubmed/28639186
http://dx.doi.org/10.1007/s10278-017-9987-0

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