近日我校电子工程与光电技术学院陈钱、左超教授课题组提出了一种全新的无标记、高通量“明暗场混合光强传输”（HBDTI）定量相位成像技术。研究成果以“Hybrid brightfield and darkfield transport of intensity approach for high-throughput quantitative phase microscopy”（用于高通量定量相位显微
Structured illumination microscopy, or SIM, has become a primary technique for imaging live cells given its full-field imaging and low photodamage. This method, however, requires at least nine raw ima
Transport of intensity promotes a new diffraction tomography technique in three-dimensional refractive index imaging. As an example demonstrated by the cover image, the phase information encoded in th
Researchers from Nanjing University of Science and Technology (NJUST) and the University of Hong Kong have developed a new approach for high-throughput quantitative phase microscopy that shows potenti
A hybrid bright/dark field intensity transport (HBDTI) approach for high-throughput quantitative phase microscopy significantly extends the space-bandwidth product of a conventional microscope and ext
The hybrid bright/dark field intensity transfer (HBDTI) approach for high-throughput quantitative phase microscopy greatly expands the spatial bandwidth product of a conventional microscope, extending
Cell organelles are involved in a variety of cellular life activities. Their dysfunction is closely related to the development and metastasis of cancer. Exploration of subcellular structures and their
Numerous cellular life processes include the organelles of cells. Their malfunction and the growth and spread of cancer are strongly connected. Understanding the mechanisms underlying diseases is made
Cell organelles perform a range of cellular tasks. Their impairment is closely associated with cancer development and metastasis. Analysis of subcellular structures and their impaired states offers in
近期，我校电子工程与光电技术学院陈钱、左超教授团队与新加坡南洋理工大学钱克矛教授在国际顶尖期刊《光：科学与应用》（Light: Science & Applications）上发表题为“Deep learning in optical metrology: a review”的综述文章，并被选为当期封面论文。电光学院左超教授、博士生钱佳铭是该论文共同第一作者，左超、陈钱、钱克矛教授为共同通讯...
Deep learning is currently leading to a paradigm shift from physics-based modeling to data-driven learning in optical metrology. In such a context, we present an overview of the current status and the
