The current preoperative vascular imaging methods cannot achieve noninvasive high-resolution imaging of deep-localized vessels. Photoacoustic tomography (PAT) can show microvessels with centimeter depth and submillimeter diameter without the use of contrast agents. Combined with PAT and optical projection technology, the Hessian-matrix-based skin removal algorithm and the target matching method were developed to spatially align the photoacoustic data of subcutaneous blood vessels with the anatomy of real patients and to realize three-dimensional (3D) visualization of blood vessels from the body surface. The optical projection navigation system based on PAT has high spatial resolution (∼135  μm) and temporal resolution (0.1 s). In the rabbit injection experiment, 3D distributions of needle and blood vessel (>100  μm) were obtained by image segmentation, which proved that the method can guide micro plastic injection. Furthermore, healthy volunteers' forehead imaging experiments show that 3D visualization and cross-sectional images of the human forehead clearly show the vascular network and ability of the system to image submillimeter blood vessels with penetration depth (∼10.2 mm). Our work confirms that the method of integrated photoacoustic imaging and optical projection has great potential for noninvasive diagnosis and treatment of clinical blood vessels, opening a path for the application of photonics in medical esthetics.

Accurate localization of blood vessels with image navigation is a key element in vascular-related medical research and vascular surgery. However, current vascular navigation techniques cannot provide naked-eye visualization of deep vascular information noninvasively and with high resolution, resulting in inaccurate vascular anatomy and diminished surgical success rates. Here, we introduce a photoacousticenabled automatic vascular navigation method combining photoacoustic computed tomography with augmented and mixed reality, for the first time, to our knowledge, enabling accurate and noninvasive visualization of the deep microvascular network within the tissues in real time on a real surgical surface. This approach achieves precise vascular localization accuracy (<0.89 mm) and tiny vascular relocation latency (<1 s) through a zero-mean normalization idea-based visual tracking algorithm and a curved surfacefitting algorithm. Further, the subcutaneous vessels of minimum diameter (∼0.15 mm) in rabbit thigh and the maximum depth (∼7 mm) in human arm can be vividly projected on the skin surface with a computer visionbased projection tracking system to simulate preoperative and intraoperative vascular localization. Thereby, this strategy provides a way to visualize deep vessels without damage on the surgical surface and with precise image navigation, opening an avenue for the application of photoacoustic imaging in surgical operations.