In a new development, a team of researchers at UCLA have devised a technique that expands the capabilities of fluorescence microscopy. This allows researchers to label parts of living cells and tissues precisely using dyes that illuminate under special lighting.
Researchers employed artificial intelligence to convert two-dimensional images into vertical assembly of virtual three-dimensional slices. This slicing displays activities inside organisms.
Not only this, the framework for the study called Deep-Z was able to correct errors in images. The errors that happen when a sample is slant or curved. Furthermore, the apparatus could use 2-D images from one type of microscope and construct 3-D images of samples virtually. The quality of 3-D images such as akin to one obtained from an advanced microscope.
Deep Z Apparatus obstructs Exposure to Light
The new method is very powerful. The method employs deep learning to carry out 3-D imaging of living specimens. The apparatus involves least exposure to light that can be toxic to samples. The details of the study and features of the framework were provided by senior author of the study.
The framework provides other advantages too. It not only spares specimen from potential damage of doses of light, the system serves as a new tool for 3-D imaging. A tool for life science researchers and biologists that is simpler, speedier, and less expensive than current methods.
The feature to correct aberrations thus provides further scope for study of live organisms. This allows to gather data from images that were otherwise unusable. The virtual access to expensive and complicated equipment is also possible.
The research reinstates a method developed earlier. The method allows to render super resolution 2-D fluorescence microscopic images. Deep learning enhances usability of both techniques.
Deep Z is learned using experimental images from scanning fluorescence microscope.