Photoacoustic microscopy with 7.6-μm axial resolution

The axial resolution of photoacoustic microscopy (PAM) is much lower than its lateral resolution, which resolves down to the submicron level. Here we achieved so far the highest axial resolution of 7.6 μm by using a commercial 125 MHz ultrasonic transducer for signal detection, followed by the Wiener deconvolution for signal processing. The axial resolution was validated by imaging two layers of red ink in a wedge shape. Melanoma cells were imaged ex vivo with high axial resolution. Compared with a PAM system with a 50 MHz ultrasonic transducer, our high-axial-resolution PAM system resolved the blood vessels in mouse ears in vivo much more clearly in the depth direction

In vivophotoacoustic microscopy with 7.6-µm axial resolution using a commercial 125-MHz ultrasonic transducer

Photoacoustic microscopy has achieved submicron lateral resolution, but its axial resolution is much lower. Here an axial resolution of 7.6 μm, the highest axial resolution validated by experimental data, has been achieved by using a commercial 125 MHz ultrasonic transducer for signal detection followed by the Wiener deconvolution for signal processing. Limited by the working distance, the high-frequency ultrasonic transducer can penetrate 1.2 mm into biological tissue from the ultrasound detection side. At this depth, the signal-to-noise ratio decreases by 11 dB, and the axial resolution degrades by 36%. The new system was demonstrated in imaging melanoma cells ex vivo and mouse ears in vivo

Photoimprint Photoacoustic Microscopy for Three-Dimensional Label-Free Subdiffraction Imaging

Subdiffraction optical microscopy allows the imaging of cellular and subcellular structures with a resolution finer than the diffraction limit. Here, combining the absorption-based photoacoustic effect and intensity-dependent photobleaching effect, we demonstrate a simple method for subdiffraction photoacoustic imaging of both fluorescent and nonfluorescent samples. Our method is based on a double-excitation process, where the first excitation pulse partially and inhomogeneously bleaches the molecules in the diffraction-limited excitation volume, thus biasing the signal contributions from a second excitation pulse striking the same region. The differential signal between the two excitations preserves the signal contribution mostly from the center of the excitation volume, and dramatically sharpens the lateral resolution. Moreover, due to the nonlinear nature of the signal, our method offers an inherent optical sectioning capability, which is lacking in conventional photoacoustic microscopy. By scanning the excitation beam, we performed three-dimensional subdiffraction imaging of varied fluorescent and nonfluorescent species. As any molecules have absorption, this technique has the potential to enable label-free subdiffraction imaging, and can be transferred to other optical imaging modalities or combined with other subdiffraction methods

Photo-imprint super-resolution photoacoustic microscopy

Combining the absorption-based photoacoustic effect and intensity-dependent photobleaching effect, we demonstrate a simple method for super-resolution photoacoustic imaging of both fluorescent and non-fluorescent samples. Our method is based on a double-excitation process, where the first excitation pulse partially and inhomogeneously bleaches the molecules in the diffraction-limited excitation volume, thus biasing the signal contributions from a second excitation pulse striking the same region. By scanning the excitation beam, we performed three-dimensional sub-diffraction imaging of varied fluorescent and non-fluorescent species. A lateral resolution of 80 nm and an axial resolution of 370 nm have been demonstrated. This technique has the potential to enable label-free super-resolution imaging, and can be transferred to other optical imaging modalities or combined with other super-resolution methods

Fuzzing Deep Learning Compilers with HirGen

Deep Learning (DL) compilers are widely adopted to optimize advanced DL models for efficient deployment on diverse hardware. Their quality has profound effect on the quality of compiled DL models. A recent bug study shows that the optimization of high-level intermediate representation (IR) is the most error-prone compilation stage. Bugs in this stage are accountable for 44.92% of the whole collected ones. However, existing testing techniques do not consider high-level optimization related features (e.g. high-level IR), and are therefore weak in exposing bugs at this stage. To bridge this gap, we propose HirGen, an automated testing technique that aims to effectively expose coding mistakes in the optimization of high-level IR. The design of HirGen includes 1) three coverage criteria to generate diverse and valid computational graphs; 2) full use of high-level IRs language features to generate diverse IRs; 3) three test oracles inspired from both differential testing and metamorphic testing. HirGen has successfully detected 21 bugs that occur at TVM, with 17 bugs confirmed and 12 fixed. Further, we construct four baselines using the state-of-the-art DL compiler fuzzers that can cover the high-level optimization stage. Our experiment results show that HirGen can detect 10 crashes and inconsistencies that cannot be detected by the baselines in 48 hours. We further validate the usefulness of our proposed coverage criteria and test oracles in evaluation

Label-free photoacoustic microscopy of myocardial sheet architecture

Cardiac myofibers are organized into sheet architectures, which contribute to up to 40% of the heart wall thickening for ejection of blood for circulation. It is important to delineate the sheet architecture for a better understanding of cardiac mechanisms. However, current sheet imaging technologies are limited by fixation-induced dehydration/deformation and low spatial resolution. Here we implemented high-resolution label-free photoacoustic microscopy (PAM) of the myocardial sheet architecture. With high endogenous optical-absorption contrast originating mainly from cytochrome, myoglobin, and melanin, PAM can image the unfixed, unstained and unsliced heart without introducing deformation artifacts. A fresh blood-free mouse heart was imaged by PAM ex vivo. The three-dimensional branching sheets were clearly identified within 150 µm depth. Various morphological parameters were derived from the PAM image. The sheet thickness (80±10  μm) and the cleavage height (11±1  μm) were derived from an undehydrated heart for the first time. Therefore, PAM has the potential for the functional imaging of sheet architecture in ex vivo perfused and viable hearts

Generative Quanta Color Imaging

The astonishing development of single-photon cameras has created an unprecedented opportunity for scientific and industrial imaging. However, the high data throughput generated by these 1-bit sensors creates a significant bottleneck for low-power applications. In this paper, we explore the possibility of generating a color image from a single binary frame of a single-photon camera. We evidently find this problem being particularly difficult to standard colorization approaches due to the substantial degree of exposure variation. The core innovation of our paper is an exposure synthesis model framed under a neural ordinary differential equation (Neural ODE) that allows us to generate a continuum of exposures from a single observation. This innovation ensures consistent exposure in binary images that colorizers take on, resulting in notably enhanced colorization. We demonstrate applications of the method in single-image and burst colorization and show superior generative performance over baselines. Project website can be found at https://vishal-s-p.github.io/projects/2023/generative_quanta_color.html.Comment: Accepted at IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 202