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Discriminative Scale Learning (DiScrn): Applications to Prostate Cancer Detection from MRI and Needle Biopsies

There has been recent substantial interest in extracting sub-visual features from medical images for improved disease characterization compared to what might be achievable via visual inspection alone. Features such as Haralick and Gabor can provide a multi-scale representation of the original image...

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Detalles Bibliográficos
Autores principales: Wang, Haibo, Viswanath, Satish, Madabhushi, Anant
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5620056/
https://www.ncbi.nlm.nih.gov/pubmed/28959011
http://dx.doi.org/10.1038/s41598-017-12569-z

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