567-HistoSweep：高分辨率数字病理与空间组学质量控制框架

本文介绍了一项名为 HistoSweep 的计算框架，旨在为数字病理学和空间组学提供高分辨率的组织质量控制。研究人员开发了一种可扩展的算法，通过整合色彩统计、纹理描述符和自适应阈值，能够从数十亿像素的图像中自动剔除伪影、无细胞空隙及背景噪声。该工具在处理超大图像时无需 GPU 加速，显著提升了在标准 CPU 硬件上的运算效率。通过对 25 个多样化数据集的验证，HistoSweep 证明了其在识别转录信号泄漏和组织错位方面的卓越能力。最终，该框架通过提供更精准的组织掩码，有效增强了细胞类型预测、图像细分以及下游的空间分析质量。References: Schroeder A, Yu X, Li W, et al. HistoSweep enables cellular-resolution tissue quality control for gigapixel images in digital pathology and spatial omics[J]. bioRxiv, 2026: 2026.01. 30.702675.前往小宇宙评论区与主播互动

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567-HistoSweep：高分辨率数字病理与空间组学质量控制框架

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