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BigCell generates gigapixel histopathology images from text reports

By PulseAugur Editorial · [1 sources] ·

Researchers have developed BigCell, a novel approach capable of generating gigapixel-resolution whole-slide images (WSIs) of histopathology tissue. Unlike previous models that operated on smaller image patches, BigCell generates coherent images at native gigapixel scale by training a flow-matching transformer on over 120,000 WSIs. The system can produce images up to 32,768x32,768 pixels and incorporates an adaptive scheduling strategy to accelerate generation. Additionally, BigCell introduces text-to-image synthesis at 8k resolution, directly from pathology text reports, which has been shown to improve slide-level classification performance. AI

IMPACT Enables generation of high-resolution medical images from text, potentially improving diagnostic accuracy and training data availability.

RANK_REASON The cluster describes a new research paper detailing a novel AI model for generating high-resolution medical images. [lever_c_demoted from research: ic=1 ai=1.0]

Read on Hugging Face Daily Papers →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

BigCell generates gigapixel histopathology images from text reports

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The cluster describes a new research paper detailing a novel AI model for generating high-resolution medical images. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. Hugging Face Daily Papers TIER_1 Deutsch(DE) ·

    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 encompa…

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