Image-based Heterogeneity Modeling
Image-Based Heterogeneity Modeling is a computational framework that characterizes spatial heterogeneity in imaging data by explicitly modeling local variations in image intensity, texture, or morphology to distinguish underlying biological or pathological states.
26
Publications
1.3K
Citations
138
Authors
74
Institutions
Publications per year
2017–2026
13
Parents
26
Fanny Orlhac, Christophe Nioche, Michaël Soussan et al. · Journal of Nuclear Medicine · 2016 · 118 citations · Full text
1–5 of 26
138
The University of Texas MD Anderson Cancer Center, United States
2 publications · 76 citations
2
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The University of Texas MD Anderson Cancer Center, United States
2 publications · 76 citations
2
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1
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1
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1
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1–5 of 138
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The University of Texas MD Anderson Cancer Center
Houston, United States
2 h-index
10 publications
356 citations
National Cancer Institute
Bethesda, United States
2 h-index
2 publications
39 citations

University of Waterloo
Waterloo, Canada
2 h-index
7 publications
329 citations

University College Cork
Cork, Ireland
2 h-index
5 publications
150 citations

Shanghai Jiao Tong University
Shanghai, China
1 h-index
1 publications
18 citations
Engineering and Physical Sciences Research Council
Swindon, United Kingdom
1 h-index
4 publications
536 citations
Cancer Research UK Cambridge Center
Cambridge, United Kingdom
1 h-index
8 publications
376 citations
Universitat de Barcelona
Barcelona, Spain
1 h-index
2 publications
28 citations
1–8 of 74
MRM · 2 publications · 225 citations
2
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1 publications · 214 citations
1
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1 publications · 12 citations
1
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1 publications · 18 citations
1
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1 publications · 30 citations
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