LazySlide: accessible and interoperable whole-slide image analysis.

Abstract

Histopathological data are foundational in both biological research and clinical diagnostics but remain siloed from modern multimodal and single-cell frameworks. Here we introduce LazySlide, an open-source Python package built on the scverse ecosystem for efficient whole-slide image analysis and multimodal integration. By leveraging vision-language foundation models and adhering to scverse data standards, LazySlide bridges histopathology with omics workflows. It supports tissue and cell segmentation, feature extraction, cross-modal querying and zero-shot classification, with minimal setup.