Computational imaging involves the joint design of imaging system hardware and software, optimizing across the entire pipeline from acquisition to reconstruction. Computers can replace bulky and expensive optics by solving computational inverse problems. This talk will describe new microscopes that use computational imaging to enable 3D, aberration and phase measurement using simple hardware that is easily adoptable and advanced image reconstruction algorithms based on large-scale optimization and learning.

The sharp rise in cancer due to an ageing society and the rapid spread of life-threatening infectious diseases and antibiotic-resistant germs are areas of unmet medical need. An effective and early diagnosis and personalized therapy of cancer and infections requires new methods for a targeted and early diagnosis of these diseases. During the last years spectroscopic methods have shown their potential to provide a clinician with clinically relevant information to meet the aforementioned challenges. Within this contribution we will highlight our recent efforts in translating spectroscopic approaches with focus on Raman spectroscopy towards routine clinical applications. We will introduce a series of innovative multi-contrast marker free spectroscopy approaches for (I) rapid diagnosis of infectious diseases for targeted antibiotic administration, which is crucial for the survival of patients; (II) precise intraoperative tumor margin control, because reliable tumor margin recognition during an intervention is the key to effective tumor treatment; and (III) early diagnosis of neurodegenerative diseases of the fundus of the eye. The challenges to overcome the valley of death to apply such spectroscopic approaches for clinical routine requires novel infrastructures. To reach this goal, we established the research campus InfectoGnostics to safeguard the transfer from fundamental research into diagnostic systems. ---------------------- Acknowledgements: Financial support of the EU, the ”Thüringer Ministerium für Wirtschaft, Wissenschaft und Digitale Gesellschaft”, the ”Thüringer Aufbaubank”, the Federal Ministry of Education and Research, Germany (BMBF), the German Science Foundation, the Fonds der Chemischen Industrie and the Carl-Zeiss Foundation are greatly acknowledged.

The interface of deep learning and imaging has seen extraordinary progress in the past few years as computational power now enables image processing that can exceed human capability. Much of the recent work at this interface involves the application of variants of convolutional neural networks, for a wide variety of techniques including image enhancement, style transfer and labelling. However, whilst deep learning can unlock extremely powerful capabilities, the collection and processing of appropriate training data remains a significant challenge. In this talk, a brief tutorial on the practical application of neural networks for image processing will be presented, followed by experimental results associated with optical and scanning electron microscopy. The focus of this talk will be on the demonstration of image enhancement of optical microscopy from 20x resolution to 1500x, whilst simultaneously identifying the objects present and hence enabling automated labelling, colour-enhancing and removal of specific objects in the magnified image.

We have recently developed single molecule light field microscopy (SMLFM), a new approach to 3D single molecule localisation that is capable of up to 20 nm lateral and axial precision across a 6 micrometre depth of field. SMLFM can be readily implemented by installing a refractive microlens array into the conjugate back focal plane of a widefield single molecule localisation microscope. We have benchmarked the performance of SMLFM and showcased its capabilities by imaging fluorescently labeled membranes of fixed eukaryotic cells below the diffraction limit. In this presentation I will describe the concept of light field imaging as it is applied to single molecule localisation, its advantages, limitations and future possibilities.

It is crucial to visualize biomolecules and their molecular-interaction complexes directly within cells, to show precisely where these interactions occur and thus improve our understanding of cellular regulation. In this presentation I will present new approaches to image proteins and protein-protein interactions that are based on synthetic DNA interactions and allow localisation with ~10 nm precision. Two schemes will be presented, called PD-PAINT (proximity-dependent PAINT) and Repeat DNA-PAINT which are improvements of the localisation microscopy technique called DNA-PAINT. I will describe the basis of these approaches and demonstrate their application to biophysical questions in cardiac biophysics. We show that these schemes can be straightforwardly integrated in a multiplexed super-resolution imaging protocol and benefit from advantages of DNA-based super-resolution localization microscopy, such as high specificity, high resolution and the ability to image quantitatively.

Near-Infrared Spectroscopy (or NIRS) is an optical technique that uses near-infrared (NIR) light that can penetrate deep into the tissue. NIR light is transmitted to the head, non-invasively most often with the use of fibre optics. The collected, reflected NIR light from as deep as the cortex of the brain has been attenuated due to absorption of the oxygen dependent chromophore in the blood, the hemoglobin. NIRS most often measures the reflected NIR attenuation at a couple of wavelengths, to quantify the concentration of the oxygenated and deoxygenated hemoglobin ([HbO2], [HHb]) and provide information about the brain oxygen levels. Of particular interest are the changes in brain oxygenation due to neuronal activity as they can provide us with an indirect measurement of brain function. This can be measured with functional NIRS or fNIRS. For several years now we have been developing technology that extend fNIRS instrumentation by allowing measuring hundreds of NIR wavelengths instead of just two. The technique is called broadband near-infrared spectroscopy (or bNIRS). The bNIRS system measures changes in light attenuation, reflected back from the head, over 308 near-infrared (NIR) wavelengths (610nm to 918nm). This allow us to quantify the changes in brain tissue [HbO2], [HHb] and the concentration changes in the oxidation state of cerebral cytochrome-c-oxidase ([oxCCO]). In my talk I will discuss how we have been using bNIRS both in our preclinical and clinical investigations in neonatal hypoxic-ischemic injury to quantify brain injury severity and neurodevelopmental outcome.

Brillouin spectroscopy, based on the inelastic scattering of light from thermally driven acoustic waves or phonons, holds great promise in the field of life sciences as it provides functionally relevant micro-mechanical information. Due to the complexity of biological systems such as cells and tissues, which present spatio-temporal heterogeneities, interpretation of Brillouin spectra can be difficult. This talk is aimed to introduce Brillouin microscopy as an emerging form of optical elastography and to give an insight into the biophysical quantities retrieved from Brillouin spectra of biological samples. Applications in biosciences will also be covered with an emphasis to clinically relevant studies.

What makes a good optical “measurement” in biology? The optical resolution performance of a microscope is only half the story. We want to be able to acquire images that a biologist can analyze and draw meaningful conclusions from. Other considerations include: the statistical benefits (but optical challenges) of longitudinal imaging; minimally-invasive imaging that does not cause physical, photochemical or thermal damage to a sample; motion-stabilized imaging. I will discuss the challenges, present some approaches to overcome them, and pose open questions. Finally, I will consider whether image formation is needed at all, in order to make a complex optical measurement.

Light-sheet fluorescence microscopy allows minimally invasive 3D imaging of biological samples. Unlike other microscopes, a light-sheet illuminates the focal plane from the side. To uniformly illuminate a wide field-of-view, propagation-invariant light-fields have been proposed. While the propagation-invariant Airy beam is particularly advantageous for single-photon excitation, its multi-photon performance is limited by its intricate transversal structure and curvature. Here we demonstrate the first planar Airy beam light-sheet. Its uniform and symmetric illumination enables rapid two-photon excitation across a wide field-of-view. Moreover, it eliminates the need for deconvolution and it can significantly simplify a dual-use, single and two-photon, imaging instrument.

Measurements in a microscope

Photoacoustic imaging is a high-resolution and high-contrast technique, which combines optical contrast with ultrasonic detection to map the distribution of the absorbing pigments in biological tissues. As an important branch of photoacoustic imaging, optical-resolution photoacoustic microscopy (OR-PAM) suffers from narrow depth-of-field (DoF), since the lateral resolution is determined by tight optical focusing. The small DoF will prevent OR-PAM to achieve large volumetric imaging. Here, we developed a parallel multifocus optical-resolution photoacoustic microscope with large depth-of-field based on a tunable acoustic gradient lens (TAG) and fiber delay network. The TAG lens is used to high -speed focus-shift. And a fiber delay network consists of three optical fibers with different lengths is used to split a single laser pulse into three sub-pulses with different delay time. A function generator generates a sinusoidal signal to drive the TAG lens at an eigenmode. The focusing power of the TAG lens will exhibit a sinusoidal oscillation at the frequency of the driving signal. Then, the three sub-pulses synchronizes with three vibration states of the TAG lens, respectively. Finally, we can obtain three focuses with different depth in one A-line data acquisition to improve the DoF. The DoF we measured by a vertically tilted carbon fiber is eatimated to larger than 775 μm, which is ~ three times of that of single-focus PAM. The large DoF of large volumetric PAM was also verified by imaging a tungsten wire network. This system can achieve rapid and large-scale monitoring of physiological activities, which could expand the application of OR-PAM in biomedical researches.

The study of the interaction between laser and brain tissue has important theoretical and practical significance for brain imaging. A two-dimensional simulation model that studies the propagation of light and heat transfer in brain tissue based on finite element has been developed by using the commercial finite element simulation software COMSOL Multiphysics. In this study, the model consists of three parts of 1) a layer of water on the surface of the brain, 2) brain tissue and 3) short pulsed laser source (the wavelength is 840nm). The laser point source is located in the middle of the layer of water above the brain tissue and irradiates the brain tissue. The propagation of light in brain tissue was simulated by solving the diffusion equation. And the temperature changes of gray matter and blood vessels were achieved by solving the biological heat transfer equation. The simulation results show that the light energy in the brain tissue decreases exponentially with the increase of penetration depth. Since the cerebral blood vessels have a stronger absorption on light compared with the surrounding tissues, the remaining light energy of the blood vessels in the cerebral cortex is ~ 85.8% of the remaining light energy in the surrounding gray matter. In the process of biological heat transfer, due to more light deposition in blood vessels, the temperature of blood vessels is 0.15 K higher than that of gray matter, and the temperature of gray matter hardly changes. This research is helpful to understand the propagation of light in the brain and the interaction between them, and has certain theoretical guiding for the optical imaging of the brain.

The brain is composed of the cerebrum, cerebellum, diencephalon and brainstem. The cerebrum is the superlative part of the central nervous system and also the main part of the brain. There are differences and similarities between humans and mouse. The study of mouse brain model is helpful to understand the process in clinical trials and also has reference significance for the study of human brain. Therefore, the study of mouse brain is particularly important. As the skull has a large scattering effect on light, it is difficult for us to image the brain through the skull directly. Therefore, we often use methods such as optical clearing or thin skull to reduce or remove the influence of the skull on imaging. In this paper, the transmission of photons in mouse brain was studied using Monte Carlo method. In the study of photon trajectories, the photon distribution without intact skull went farther in both longitudinal and transverse directions compared with that of with intact skull. In terms of the optical absorption density and fluence rate. On the condition of with intact skull, the distribution of optical absorption density and fluence rate was fusiform and rounder on the whole. The radial distribution range of optical absorption density and fluence rate was 0.25 cm, which was approximately 2.5 times of that of with intact skull. In the depth direction, due to the strong scattering and absorption of the scalp and skull, the optical absorption density dropped sharply from 0.890 cm^-1 to 0.415 cm^-1. When the photons arrived at the gray matter layer, only a few photons were reserved. Due to the strong absorption and scattering effect of the gray matter layer, only a few photons left, the optical absorption density increased from 0.415 cm^-1 to 0.592 cm^-1, and then decreased again. When the depth was 1.35 cm, the optical absorption density dropped to 0 cm^-1. After removing the skull, due to the weak absorption and scattering effect of normal saline and cerebrospinal fluid, the optical absorption density was low (0.119 cm^-1) and dropped slowly. When the photons arrived at the gray matter layer, most of the photons were reserved. Due to the strong absorption and scattering effect of the gray matter layer, the optical absorption density increased from 0.117 cm^-1 to 0.812 cm^-1, then the optical absorption density decreased to 0 cm^-1 at a depth of 1.35 cm. The distribution of radiant fluence rate is similar to that of optical absorption density. This study will provide reference and theoretical guidance for the optical imaging of mouse brain and the study of the mouse and human brain.

The measurement of surface roughness of biological tissue at microscale and nanoscale is significant to investigate the surface topography, which has been done through contact or non-contact profilometer. Although the contact profilometers provide quantitative analysis, they can easily scratch the biological tissue. While the noncontact profilometer like optical techniques can provide qualitative nondestructive measurements of the surface topography. Biospeckle imaging is a fast and powerful optical method that can only quantitatively evaluate the structure of the illuminated surface if valuable features are extracted from the biospeckle pattern. This study introduces a new fast biospeckle-based quantitative analysis method to measure the nanoscale average surface roughness of bovine articular cartilage tissue. The proposed method comprises feature extraction through local texture analysis by applying morphological operations by dilation and erosion, at different neighborhoods. The efficiency of the proposed method is evaluated on twelve articular cartilage tissue samples having different average surface roughness values.

Photoacoustic imaging is a new imaging technology in recent years, which combines the advantages of high resolution and rich contrast of optical imaging with the advantages of high penetration depth of acoustic imaging. Photoacoustic imaging has been widely used in biomedical fields, such as brain imaging, tumor detection and so on. The signal-tonoise ratio (SNR) of image signals in photoacoustic imaging is generally low due to the limitation of laser pulse energy, electromagnetic interference in the external environment and system noise. In order to solve the problem of low SNR of photoacoustic images, we use feedforward denoising convolutional neural network to further process the obtained images, so as to obtain higher SNR images and improve image quality. We use Python language to manage the referenced Python external library through Anaconda, and build a feedforward noise-reducing convolutional neural network on Pycharm platform.We first processed and segmated a training set containing 400 images, and then used it for network training. Finally, we tested it with a series of cerebrovascular photoacoustic microscopy images.The results show that the peak signal-to-noise ratio (PSNR) of the image increases significantly before and after denoising.The experimental results verify that the feed-forward noise reduction convolutional neural network can effectively improve the quality of photoacoustic microscopic images, which provides a good foundation for the subsequent biomedical research.