Confocal microscopy¹ remains a major workhorse in biomedical optical microscopy owing to its reliability and flexibility in imaging various samples, but suffers from substantial point spread function anisotropy, diffraction-limited resolution, depth-dependent degradation in scattering samples and volumetric bleaching². Here we address these problems, enhancing confocal microscopy performance from the sub-micrometre to millimetre spatial scale and the millisecond to hour temporal scale, improving both lateral and axial resolution more than twofold while simultaneously reducing phototoxicity. We achieve these gains using an integrated, four-pronged approach: (1) developing compact line scanners that enable sensitive, rapid, diffraction-limited imaging over large areas; (2) combining line-scanning with multiview imaging, developing reconstruction algorithms that improve resolution isotropy and recover signal otherwise lost to scattering; (3) adapting techniques from structured illumination microscopy, achieving super-resolution imaging in densely labelled, thick samples; (4) synergizing deep learning with these advances, further improving imaging speed, resolution and duration. We demonstrate these capabilities on more than 20 distinct fixed and live samples, including protein distributions in single cells; nuclei and developing neurons in Caenorhabditis elegans embryos, larvae and adults; myoblasts in imaginal disks of Drosophila wings; and mouse renal, oesophageal, cardiac and brain tissues.

共焦显微镜¹由于其对各种样品成像的可靠性和灵活性，仍然是生物医学光学显微镜的主要主力，但也存在大量的点扩散函数各向异性、衍射极限分辨率、散射样品的深度依赖性退化和体积漂白² 。在这里，我们解决了这些问题，从亚微米到毫米的空间尺度和毫秒到小时的时间尺度增强共焦显微镜的性能，将横向和轴向分辨率提高两倍以上，同时降低光毒性。我们通过综合的、四管齐下的方法实现了这些成果：（1）开发紧凑的线扫描仪，能够在大面积上进行灵敏、快速、衍射极限的成像； (2) 将线扫描与多视图成像相结合，开发重建算法，以提高分辨率各向同性并恢复因散射而丢失的信号； （3）采用结构照明显微镜技术，在密集标记的厚样品中实现超分辨率成像； (4)将深度学习与这些进步相结合，进一步提高成像速度、分辨率和持续时间。我们在 20 多个不同的固定样本和活样本上展示了这些功能，包括单细胞中的蛋白质分布；秀丽隐杆线虫胚胎、幼虫和成虫的细胞核和发育中的神经元；果蝇翅膀成虫盘中的成肌细胞；以及小鼠肾、食道、心脏和脑组织。