CAREER: Integrated Computational Optical Framework for Quantitative Space-Variant Imaging in Live-Cell Fluorescence Microscopy

本研究正在开发新的计算方法，将其与一种新型光学非扫描成像系统设计相结合，以实现高各向同性3D分辨率的活细胞荧光显微镜快速成像。PI开创了DIC显微镜的计算方法。这项工作解决了活细胞显微镜的一个关键挑战，即由于厚？生物标本。折射率（RI）的不匹配和不均一性在厚样品产生图像畸变，恶化成像深度在传统显微镜。商业上可用的反褶积方法不能解释这些失真。为了解决这个问题，PI正在利用计算微分干涉对比（DIC）显微镜来开发新的校正方法，并使用计算光学传感和成像（COSI）系统方法将计算开发集成到新的系统设计中。这是自适应光学的一个新颖和创新的应用。具体的研究是开发数学模型，可以准确地预测由宽视场成像系统获得的数据；使用基于模型的数据处理算法来估计3D图像中的准确荧光浓度，并为用户社区开发软件包。新方法的性能和效用正在细胞骨架蛋白上进行测试。更广泛的影响活动是多样化和创新性的。PI正在开发整合成像科学和光学系统的课程，以补充显微镜和COSI系统设计的计算成像研究。PI正在建立跨学科参与她的课程，特别是工程、生物科学和医学预科专业的学生。一个跨学科的证书课程，集中在显微镜将产生。π吗?我们致力于多学科教育和推广，为下一代生物研究人员和工程师做好准备，使他们能够在生物学、计算科学和工程学科的交叉领域工作，在这些领域取得重大进展，有望进一步推动科学革命。

CAREER: Integrated computational optical framework for quantitative space-variant imaging in live-cell fluorescence microscopy This research is developing new computational methods to integrate with a novel optical non-scanning imaging system design to enable fast live-cell fluorescence microscopy imaging with high, isotropic 3D resolution. The PI has pioneered computational methods for DIC microscopy. This work addresses a key challenge in live-cell microscopy of accounting for aberrations due to ?thick? biological specimens. Refractive index (RI) mismatch and heterogeneity within thick samples produce image distortions that worsen with imaging depth in conventional microscopes. Commercially available deconvolution methods do not account for these distortions. To address this issue, the PI is utilizing computational Differential Interference Contrast (DIC) microscopy to develop new corrective methodologies and integrate computational development into a new system design using a computational optical sensing and imaging (COSI) system approach. This is a novel and innovative application of adaptive optics. Specific research is developing mathematical models that can accurately predict data acquired with a wide-field imaging system; using model-based data processing algorithms to estimate accurate fluorescence concentration in 3D images and developing a software package for the user community. Performance and utility of the new methods is being tested on cytoskeletal proteins. The broader impact activities are diverse and innovative. The PI is developing coursework that integrates imaging science and optical systems to complement research in computational imaging for microscopy and COSI system design. The PI is establishing cross-disciplinary participation in her courses, particularly among engineering, biological sciences, and pre-medicine majors. A interdisciplinary certificate program with concentration in Microscopy will result. The PI?s commitment to multidisciplinary education and outreach is preparing the next generation of biological researchers and engineers for work at the intersection of biology, computational science and engineering disciplines where significant advances are expected to further revolutionize science.