San Francisco: A team of researchers has used Artificial Intelligence (AI) to turn two-dimensional (2D) images into stacks of virtual three-dimensional (3D) slices showing activity inside organisms. Using deep learning techniques, the team from University of California, Los Angeles (UCLA) devised a technique that extends the capabilities of fluorescence microscopy, which allows scientists to precisely label parts of living cells and tissue with dyes that glow under special lighting. In a study published in the journal Nature Methods, the scientists also reported that their framework, called "Deep-Z," was able to fix errors or aberrations in images, such as when a sample is tilted or curved. Further, they demonstrated that the system could take 2D images from one type of microscope and virtually create 3D images of the sample as if they were obtained by another, more advanced microscope. "This is a very powerful new method that is enabled by deep learning to perform 3D imaging of live specimens, with the least exposure to light, which can be toxic to samples," said senior author Aydogan Ozcan, UCLA chancellor s professor of electrical and computer engineering.

An illustration representing Deep-Z, an artificial intelligence-based framework that can digitally refocus a 2D fluorescence microscope image (at bottom) to produce 3D slices (at left). A University of California, Los Angeles research team has devised a technique that extends the capabilities of fluorescence microscopy, which allows scientists to precisely label parts of living cells and tissue with dyes that glow under special lighting. The researchers use artificial intelligence to turn two-dimensional images into stacks of virtual three-dimensional slices showing activity inside organisms. In a study published in Nature Methods on November 4, 2019, the scientists also reported that their framework, called "Deep-Z," was able to fix errors or aberrations in images, such as when a sample is tilted or curved. Further, they demonstrated that the system could take 2D images from one type of microscope and virtually create 3D images of the sample as if they were obtained by another, more advanced microscope.

A UCLA research team has devised a technique that extends the capabilities of fluorescence microscopy, which allows scientists to precisely label parts of living cells and tissue with dyes that glow under special lighting. The researchers use artificial intelligence to turn two-dimensional images into stacks of virtual three-dimensional slices showing activity inside organisms. In a study published in Nature Methods, the scientists also reported that their framework, called "Deep-Z," was able to fix errors or aberrations in images, such as when a sample is tilted or curved. Further, they demonstrated that the system could take 2-D images from one type of microscope and virtually create 3-D images of the sample as if they were obtained by another, more advanced microscope. "This is a very powerful new method that is enabled by deep learning to perform 3-D imaging of live specimens, with the least exposure to light, which can be toxic to samples," said senior author Aydogan Ozcan, UCLA chancellor's professor of electrical and computer engineering and associate director of the California NanoSystems Institute at UCLA.