Newsletter
Advancing brain imaging with high-throughput aberration sensing and correction method
Xi Chen won the NIH Pathway to Independence Award (K99/R00). The funded project aims to develop a new adaptive optics tool for improving multiphoton imaging in live animals.
We are hiring postdocs and PhD students to continue this exciting work, please refer to the open positions for more information.
AI-enhanced quantitative imaging of living cancer organoids
Artificial Confocal Microscopy (ACM) provides label-free imaging with confocal-level resolution and chemical specificity, eliminating photobleaching and photodamage. It enables long-term, 3D monitoring of organoids and spheroids, allowing fluorescence signal and dry mass measurements. ACM also supports cell counting, size analysis, and other tasks in complex medical samples, such as those used in tissue engineering, embryology, drug discovery, and personalized medicine.
High-throughput cancer imaging and phenotypic screening
Tissue refractive index (RI) can act as an intrinsic marker for cancer diagnosis by revealing nanoscale morphological changes. While extracting 3D refractive index distributions from transparent structures is challenging, our Wolf Phase Tomography (WPT) method overcomes this. It is label-free, decouples RI from sample thickness, and offers a degree of specificity. This breakthrough opens up new possibilities for medical applications, including phenotypic screening, cancer histopathology, and label-free 3D imaging of tumor microenvironments.