Technion researchers have demonstrated an innovative method that substantially improves the resolution (the ability to distinguish between details) of microscopes. This was reported by the prestigious scientific journal Nature Materials. The method is based on innovative concepts, and scientists hail it as being a “breakthrough with the potential to change the world of microscopy, imaging systems, and other optical measurement systems”. The method is attracting great interest, both in the scientific world and in industry.
“When you look through an optical microscope at an object with features (optical information) smaller than one half the wavelength of light – you necessarily see a blurred image”, explains Distinguished Prof. Mordechai (Moti) Segev of the Technion’s Department of Physics. “The reason for this is that the information about the structure of very small features does not propagate through space and thus does not reach the eye or the microscope camera. Today, a number of methods are used to achieve a resolution under one half of the wavelength of light, but they all require point-by-point scanning of the object. Hence, these methods may be used only for a static object, which does not change during the scan”.
Scientists have attempted for many years to find algorithms to reconstruct the sub-wavelength information lost between the object and the microscope camera. But thus far all such attempts were largely unsuccessful. The main reason is noise: random scattering of light (for example, from reflections off non-ideal surfaces), which is inevitable in optical systems, has thus far prevented algorithmic reconstruction of features smaller than one half the wavelength of light from measurements of the blurred image.
Now a team of Technion researchers presented a breakthrough algorithmic method for improving the resolution of microscopes to considerably under one half the wavelength of light. To a great extent, the project was successful thanks to the collaboration between several research groups from four different Technion faculties (the groups of Prof. Moti Segev and of Dr. Oren Cohen of the Department of Physics, Prof. Yonina Eldar of the Department of Electrical Engineering, Prof. Irad Yavneh and Dr. Michael Zibulevsky of the Computer Science Department, and Prof. Shy Shoham of the Department of Biomedical Engineering).
“The algorithmic method relies on finding the most suitable reconstruction that meets two criteria: the reconstructed high-resolution image must conform to the blurred image, and it must minimize of the number of the degrees of freedom”, explains Prof. Segev. “The second criterion has to do with understanding compact (sparse) representation of information and with the effect caused by noise in the measurement system. Random noise occupies all degrees of freedom, whereas information has some structure, hence it occupies a given number of degrees of freedom and never all of them. In many cases, there is some sort of a priori knowledge about the information. In principle, in such a case the information may be presented compactly, such that mathematically it is represented by a small number of projections onto basis functions that cover all the possibilities of spatial information. It is then said that the information is sparsely represented, and the number of degrees of freedom it occupies is small. In general, there are many cases where information can be represented compactly. A well known example is file compression using JPEG, a method of compact representation through projection onto a basis where the information in the file is represented sparsely (compactly)”.
This innovative concept of improving resolution in microscopy through representation of the image in the correct basis in which the image is sparse, was developed by Prof. Moti Segev of the Department of Physics and Prof. Yonina Eldar of the Department of Electrical Engineering, graduate students Snir Gazit and Yoav Shechtman and postdoctoral researcher Alex Szameit, currently a professor at the University of Jena, Germany. The idea was initially demonstrated in 2009. However, exhausting the full potential of the resolution improvement necessitated measuring the phase of the light reaching the microscope camera. Phase measurement requires interference-based methods (interferometric methods) which increase the complexity of the system substantially and limit the applications of this method.
About two years ago, Dr. Oren Cohen proposed adding an important layer to the algorithm, which in effect replaces the need for phase measurement, and to thus obtain image reconstruction at a higher resolution than one half the wavelength of light, through intensity measurement only (using a regular camera). In fact, Dr. Cohen proposed that two research directions be combined – Profs. Segev and Eldar’s idea of sub-wavelength imaging and “lensless imaging”, in which images are algorithmically (computationally) reconstructed from measurements of the intensity of the light at a very far distance from the image. This area – of lensless imaging – has recently become an extremely important field of science. On completion of the construction of three short pulse X-ray lasers (in the USA, Germany and Japan) at a cost of one billion dollars per laser, researchers intend to use lensless imaging to measure the structure of hundreds of thousands of single molecules (molecules that cannot be assembled into a crystallized structure). Understanding the structure of these molecules will pave the way for chemists, biologists and doctors to understand many biological processes at the molecular level. Until now, the resolution of all “lensless imaging” methods has been limited to features bigger than a wavelength. However, the methods developed by the Technion researchers could bring about a revolutionary improvement of the entire “lensless imaging” field, and allow measurement of dynamically changing molecules.
The Technion research team has demonstrated in experiments the reconstruction of details at least five times smaller than the wavelength of light, in a single-shot measurement of the light intensity at the focal plane of the microscope lens. The research work was published in the prestigious journal Nature Materials. The majority of the research work was done by postdoctoral researcher Alex Szameit and graduate students Yoav Shechtman and Eli Osherovich. The experiments, conducted by Alex Szameit and Hod Dana (graduate student at the Department of Biomedical Engineering), demonstrated reconstructions of objects with optical features 100 nanometers in size using radiation with a wavelength of 530 nanometers. In comparison, without using the new method, the resolution of this microscope is limited to features bigger than 300 nanometers.
As described above, the main part of the research is the development of the algorithm for the reconstruction of missing information: (a) reconstruction of the phase of light measured by the camera and (b) reconstruction of the part of the optical information which never reached the camera (information on features smaller than one half the wavelength of light). The initial algorithm, developed by Elad Bullkich, an undergraduate student at the time the research was conducted, and Yoav Shechtman, was based on performing the phase reconstruction algorithm followed by the algorithm for the reconstruction of sub-wavelength information. Some time later, Eli Osherovich developed a far better algorithm that reconstructs both types of “missing information” concurrently, thereby substantially increasing performance and allowing handling a wide range of images.
Technion researchers are now working on the development of similar methods for improving the resolution of other measurement systems. For example, graduate student Pavel Sidorenko has recently demonstrated breaking the resolution barrier of spectroscopic resolution: he has reconstructed spectral information at a higher resolution than the fundamental limit on spectroscopy (the time duration a photon spends in the measuring instrument). The researchers hope that these developments will lead to the improvement of spectral systems used, as an example, for the measurement of pollutants in the air of in water, detection of explosives, etc.