Segmentation of Image Data from Complex Organotypic 3D Models of Cancer Tissues with Markov Random Fields.
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A high-content image analysis approach for quantitative measurements of chemosensitivity in patient-derived tumor microtissues.Development of a 3D Tissue Culture-Based High-Content Screening Platform That Uses Phenotypic Profiling to Discriminate Selective Inhibitors of Receptor Tyrosine Kinases.Comprehensive high-throughput image analysis for therapeutic efficacy of architecturally complex heterotypic organoids.Incorporating interaction networks into the determination of functionally related hit genes in genomic experiments with Markov random fields.Machine learning and image-based profiling in drug discovery
P2860
Segmentation of Image Data from Complex Organotypic 3D Models of Cancer Tissues with Markov Random Fields.
description
2015 nî lūn-bûn
@nan
2015 թուականի Դեկտեմբերին հրատարակուած գիտական յօդուած
@hyw
2015 թվականի դեկտեմբերին հրատարակված գիտական հոդված
@hy
2015年の論文
@ja
2015年論文
@yue
2015年論文
@zh-hant
2015年論文
@zh-hk
2015年論文
@zh-mo
2015年論文
@zh-tw
2015年论文
@wuu
name
Segmentation of Image Data fro ...... sues with Markov Random Fields
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Segmentation of Image Data fro ...... ues with Markov Random Fields.
@ast
Segmentation of Image Data fro ...... ues with Markov Random Fields.
@en
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label
Segmentation of Image Data fro ...... sues with Markov Random Fields
@nl
Segmentation of Image Data fro ...... ues with Markov Random Fields.
@ast
Segmentation of Image Data fro ...... ues with Markov Random Fields.
@en
prefLabel
Segmentation of Image Data fro ...... sues with Markov Random Fields
@nl
Segmentation of Image Data fro ...... ues with Markov Random Fields.
@ast
Segmentation of Image Data fro ...... ues with Markov Random Fields.
@en
P2860
P50
P3181
P1433
P1476
Segmentation of Image Data fro ...... ues with Markov Random Fields.
@en
P2093
Matthias Nees
Sean Robinson
P2860
P304
P3181
P356
10.1371/JOURNAL.PONE.0143798
P407
P577
2015-12-02T00:00:00Z