arXiv:2605.22000cs.CVcs.AI2026-05

用相位显微技术生成3D组织切片,实现无需染色的虚拟苏木精-伊红染色。

Virtual 3D H&E Staining from Phase-contrast Back-illumination Interference Tomography

论文配图:Virtual 3D H&E Staining from Phase-contrast Back-illumination Interference Tomography
图 1 · 摘自论文原文
  • 通过双向多尺度一致性与跨域风格复用,将非均匀对比的相位图像转为真实感H&E图像。
  • 在零样本细胞分割评估中,核结构识别准确率显著提升,边界保留更佳。
  • 首个可量化验证的3D虚拟染色数据集,适合病理学与医学影像研究者使用。

无处理组织的三维(3D)组织病理学有望通过全面表征组织微结构和实现体内评估,推动疾病管理变革。背光干涉断层扫描(BIT)是一种新型相位显微技术,可快速、非破坏性地获取未处理组织的体积图像。然而,将BIT体积数据转化为临床可读的H&E图像仍具挑战,尤其因存在移变对比度且缺乏定量验证基准。我们提出HistoBIT3D,首个体素级配对的BIT与荧光标记核数据集,支持在无监督虚拟染色中对结构保真度进行定量评估。基于此数据集,我们构建了一种新型虚拟染色框架,通过引入双向多尺度内容一致性和跨域风格复用,将具有移变对比度的BIT体积转换为逼真的H&E体积,显著提升结构保真度与视觉真实性。该方法在真实感指标上达到当前最优水平,并在零样本Cellpose评估下大幅提高3D核分割准确率与边界保持能力。这些成果共同建立了一个可量化验证、结构忠实且可扩展的3D虚拟H&E染色流程,推动无切片、体积化计算病理学的发展。数据与代码已开源:https://github.com/aasong113/HistoBIT3D_VirtualStaining。

原文摘要 · Abstract (English)

Three-dimensional (3D) histopathology of unprocessed tissues has the potential to transform disease management by enabling volumetric characterization of tissue microarchitecture and in-vivo assessment. Back-illumination Interference Tomography (BIT) is a new phase microscopy technology that provides rapid, non-destructive volumetric imaging of unprocessed tissues. However, translating BIT volumes into clinically interpretable H&E images remains challenging, particularly due to shift-variant contrast and the absence of quantitative validation benchmarks. We introduce HistoBIT3D, the first voxel-wise paired BIT and fluorescence-labeled nuclei dataset, enabling quantitative evaluation of structural preservation in unsupervised virtual staining against ground-truth nuclear distributions. Using this dataset, we present a novel virtual staining framework that translates BIT volumes with shift-variant contrast into realistic H&E volumes by leveraging bidirectional multiscale content consistency and cross-domain style reuse to enhance structural fidelity and perceptual realism. Our method achieves state-of-the-art realism metrics while significantly improving 3D nuclei segmentation accuracy and boundary preservation under zero-shot Cellpose evaluation. Together, these contributions establish a quantitatively validated, structurally faithful, and scalable pipeline for 3D virtual H&E staining, advancing the paradigm of slide-free, volumetric computational histopathology. Our data and code are available at: https://github.com/aasong113/HistoBIT3D_VirtualStaining.

虚拟染色3D病理相位成像深度学习

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