A nonparametric framework detects repeated spatial patterns via constrained clustering followed by MMD-based reassignment and block permutation under stationarity and mixing conditions.
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Cell 174, 1373–1387.e19
2 Pith papers cite this work, alongside 1,195 external citations. Polarity classification is still indexing.
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SegTME-UNI2 pairs a UNI2-based dual-head segmentation model trained via progressive pseudo-labeling with an LLM to produce multiclass cell maps and narrative TME descriptions from H&E images.
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A Robust Nonparametric Framework for Detecting Repeated Spatial Patterns
A nonparametric framework detects repeated spatial patterns via constrained clustering followed by MMD-based reassignment and block permutation under stationarity and mixing conditions.
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SegTME-UNI2: A Foundation Model-Based Framework for Generalisable Multiclass Cell Segmentation and LLM-Driven Tumour Microenvironment Characterisation in Histopathology
SegTME-UNI2 pairs a UNI2-based dual-head segmentation model trained via progressive pseudo-labeling with an LLM to produce multiclass cell maps and narrative TME descriptions from H&E images.