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Quantitative Assessment of the Effects of Compression on Deep Learning in Digital Pathology Image Analysis
PURPOSE: Deep learning (DL), a class of approaches involving self-learned discriminative features, is increasingly being applied to digital pathology (DP) images for tasks such as disease identification and segmentation of tissue primitives (eg, nuclei, glands, lymphocytes). One application of DP is...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
American Society of Clinical Oncology
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7113072/ https://www.ncbi.nlm.nih.gov/pubmed/32155093 http://dx.doi.org/10.1200/CCI.19.00068 |