The number of colors in fluorescence microscopy is far less than the types of intracellular compartments. I will present our recent progress in super resolution imaging and deep convolutional neuronal networks to segment 15 subcellular structures. This approach bypasses the limitations of multi-color imaging, accelerates the imaging speed by one order of magnitude, and can accurately segment vesicle organelles with similar shapes and sizes. The super-resolution advantages were demonstrated in resolving the 3D anatomic nanostructures at different mitotic phases and tracking the fast dynamic interactions among nine intracellular compartments in live cell. We show transfer learning ability of our networks among different microscopes, different cell types, and even complexed system of living tissues.
Professor Dayong Jin FTSE obtained his PhD from Macquarie University in 2007. He joined UTS in 2015, established the Australian Industry Transformation Research Hub (ARC IDEAL Hub) in 2016, and the UTS Institute for Biomedical Materials & Devices (IBMD) in 2018, to transform advances in phonics and materials into disruptive biotechnologies.
He is a Clarivate Highly Cited Researcher, an Australian Laureate Fellow, and a Fellow of Australian Academy of Technology and Engineering, with expertise covering biomedical engineering, photonics, nanotechnology, microscopy, and analytical chemistry, to enable rapid detection and super resolution imaging of cells and molecules. He won the 2017 Prime Minister’s Prize for Science as the Physical Scientist of the Year.
Clean water and clean air are vital for public health. This project focuses on developing high-efficiency and environmentally sustainable filters for removing harmful air/water pollutants. The team has developed novel architectures and functionalities for the filters to achieve high permeance, high removal efficiency, and excellent reusability.
