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Paper · arXiv

BigCell: Generating Gigapixel Whole-Slide Images

Whole-slide images (WSIs) are gigapixel-scale digital scans of histopathology tissue and serve as the primary basis for cancer diagnosis. Existing histopathology generative models operate at the patch scale, producing fixed-size tiles of at most 1024times1024 pixels which encompass only a small fraction of the WSI. In contrast, text reports for clinical diagnoses and slide-level diagnostic labels -- the supervision that exists at scale -- operate at the whole-slide level. We present BigCell, the first approach to generate coherent whole-slide histopathology images at native gigapixel resolution. BigCell trains a flow-matching transformer at 2048times2048 pixels on over 120,000 publicly avail

AuthorsSrikar Yellapragada, Alexandros Graikos, Zilinghan Li et al.
Primary category
Published9 October 2026
Last updated at source—
hf-daily-papersflow-matching transformerpathology foundation modelssliding-window pipelineadaptive schedulingtext-to-image synthesisdense conditioning grids
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