SOURCE-LINKED INTELLIGENCE
Seamless Whole Slide Label-Free Virtual Staining
Label-free virtual staining offers a compelling, non-destructive alternative to standard histopathology; however, its clinical adoption is hindered by the computational bottlenecks inherent to processing gigapixel Whole Slide Images (WSIs). Current deep learning approaches require patch-based inference to avoid memory constraints, which disrupts global tissue continuity and introduces tiling artifacts--displaying visible seams and color shifts. To address this, we introduce the Consistency Memory Bank (COMB), a novel label-free virtual staining framework that enforces spatial and channel consi
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-09T23:59:55.000Z
First collected: 2026-09-20T19:12:12.556Z. This is not the publication date.