Biomedical microscopy images with high-resolution (HR) and axial information can help analysis and diagnosis. However, obtaining such images usually takes more time and economic costs, which makes it impractical in most scenarios. In this paper, we first propose a novel Self-texture Transfer Super-resolution and Refocusing Network (STSRNet) to reconstruct HR multi-focal plane (MFP) images from a single 2D low-resolution (LR) wide field image without relying on scanning or any special devices. The proposed STSRNet consists of three parts: the backbone module for extracting features, the self-texture transfer module for transferring and fusing features, and the flexible reconstruction module for SR and refocusing. Specifically, the self-texture transfer module is designed for images with self-similarity such as cytological images and it searches for similar textures within the image and transfers to help MFP reconstruction. As for reconstruction module, it is composed of multiple pluggable components, each of which is responsible for a specific focal plane, so as to performs SR and refocusing all focal planes at one time to reduce computation. We conduct extensive experiments on cytological images and the experiments show that MFP images reconstructed by STSRNet have richer details in the axial and horizontal directions than input images. At the same time, the reconstructed MFP images also perform better than single 2D wide field images on high-level tasks. The proposed method provides relatively high-quality MFP images when real MFP images cannot be obtained, which greatly expands the application potential of LR wide-field images. To further promote the development of this field, we released our cytology dataset named RSDC for more researchers to use.

中文翻译：

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STSRNet：自纹理传输超分辨率和重聚焦网络


具有高分辨率（HR）和轴向信息的生物医学显微镜图像可以帮助分析和诊断。然而，获得此类图像通常需要更多的时间和经济成本，这使得在大多数情况下不切实际。在本文中，我们首先提出了一种新颖的自纹理传输超分辨率和重聚焦网络（STSRNet），用于从单个 2D 低分辨率（LR）宽视场图像重建 HR 多焦平面（MFP）图像，而不依赖于扫描或任何特殊设备。所提出的 STSRNet 由三部分组成：用于提取特征的主干模块、用于传输和融合特征的自纹理传输模块以及用于 SR 和重新聚焦的灵活重建模块。具体来说，自纹理传输模块专为具有自相似性的图像（例如细胞学图像）而设计，它会搜索图像中的相似纹理并进行传输以帮助MFP重建。重建模块由多个可插拔组件组成，每个组件负责一个特定的焦平面，从而一次性进行SR和重新聚焦所有焦平面，以减少计算量。我们对细胞学图像进行了大量的实验，实验表明 STSRNet 重建的 MFP 图像在轴向和水平方向上比输入图像具有更丰富的细节。同时，重建的 MFP 图像在高级任务上也比单个 2D 广域图像表现更好。该方法在无法获取真实MFP图像的情况下提供相对高质量的MFP图像，极大拓展了LR宽视场图像的应用潜力。为了进一步推动该领域的发展，我们发布了名为RSDC的细胞学数据集，供更多研究人员使用。