The nascent technology of ptychography, employed in high-throughput optical imaging, will see progress in both performance and the range of its applications. Summarizing this review, we outline key areas for future advancement.

Whole slide image (WSI) analysis is now considered an essential method in the field of modern pathology. Deep learning techniques have recently demonstrated top performance in analyzing whole slide images (WSIs), including tasks like classifying, segmenting, and retrieving information from these images. However, the extensive dimensions of WSIs necessitate a considerable investment in computational resources and processing time for WSI analysis. Most existing analysis methods require the full and complete decompression of the entire image, a constraint which curtails their practicality, particularly within deep learning-based processes. This paper showcases WSIs classification analysis workflows, optimized for computational efficiency through compression domain processing, and readily applicable to the most advanced WSI classification models. By drawing on the pyramidal magnification structure of WSI files and compression features available in the raw code stream, these approaches achieve their objectives. WSI patches are assigned distinct decompression depths by the methods based on characteristics preserved within the compressed or partially decompressed patches. The application of attention-based clustering to patches from the low-magnification level generates differing decompression depths for high-magnification patches situated in various locations. Features from the compression domain within the file code stream are used for a more granular selection of high-magnification patches, leading to a smaller set that requires complete decompression. The final classification step involves feeding the resulting patches into the downstream attention network. Unnecessary access to the high-zoom level and the costly full decompression process are eliminated to improve computational efficiency. Decreasing the number of decompressed patches leads to a substantial reduction in the computational time and memory requirements for subsequent training and inference processes. The speed of our approach is 72 times faster, and the memory footprint is reduced by an astounding 11 orders of magnitude, with no compromise to the accuracy of the resulting model, compared to the original workflow.

Accurate and continuous blood flow monitoring is paramount for achieving therapeutic success during many surgical operations. Emerging as a promising method for observing blood flow, laser speckle contrast imaging (LSCI) uses a simple, real-time, and label-free optical approach, however, its ability to deliver reproducible quantitative data is currently lacking. The instrumental intricacy of multi-exposure speckle imaging (MESI), a refinement of laser speckle contrast imaging (LSCI), has hampered its adoption. We detail the design and fabrication of a compact, fiber-coupled MESI illumination system (FCMESI), substantially smaller and less intricate than previous approaches. Microfluidic flow phantoms were utilized to validate the FCMESI system's flow measurement accuracy and repeatability, which proved equivalent to conventional free-space MESI illumination techniques. Within an in vivo stroke model, FCMESI's capacity to monitor fluctuations in cerebral blood flow is also exhibited.

Fundus photography is critical for the diagnosis and treatment of ophthalmic conditions. Low image contrast and a small field of view are significant limitations of conventional fundus photography, making it difficult to identify subtle abnormalities indicative of early-stage eye diseases. Enhanced image contrast and field-of-view coverage are crucial for the prompt diagnosis of early-stage diseases and accurate treatment evaluation. A portable fundus camera with high dynamic range imaging and a broad field of view is the subject of this report. For the development of a portable, nonmydriatic, wide-field fundus photography device, miniaturized indirect ophthalmoscopy illumination was essential. The use of orthogonal polarization control served to abolish illumination reflectance artifacts. GW4869 Three fundus images, sequentially acquired and fused, employing independent power controls, enabled HDR functionality, improving local image contrast. A 101-degree eye angle (67-degree visual angle) field of view was captured for nonmydriatic fundus photography. Employing a fixation target, the effective field of view increased up to 190 eye-angle degrees (134 visual-angle degrees), dispensing with the need for pharmacologic pupillary dilation. HDR imaging's performance was confirmed across a range of normal and pathological eyes, in comparison with a standard fundus camera.

Quantifying the morphology of photoreceptor cells, specifically their diameter and outer segment length, is critical for an early, precise, and sensitive diagnosis and prognosis of retinal neurodegenerative conditions. Utilizing adaptive optics optical coherence tomography (AO-OCT), a three-dimensional (3-D) representation of photoreceptor cells within the living human eye is obtainable. In the current gold standard for extracting cell morphology from AO-OCT images, a 2-D manual marking process is employed, which is a time-consuming procedure. We propose a comprehensive deep learning framework for segmenting individual cone cells in AO-OCT scans, automating this process and enabling 3-D analysis of the volumetric data. By employing an automated methodology, we observed human-level performance in the evaluation of cone photoreceptors in healthy and diseased participants. This assessment spanned three different AO-OCT systems, incorporating both spectral-domain and swept-source point-scanning OCT.

Understanding the complete 3-dimensional geometry of the human crystalline lens is paramount for achieving more effective intraocular lens calculations, particularly in the context of cataract and presbyopia surgical interventions. In a preceding publication, we outlined a novel method for capturing the complete shape of ex vivo crystalline lenses, named 'eigenlenses,' which outperformed existing advanced methods in terms of both compactness and accuracy for quantifying crystalline lens morphology. We exemplify the method of employing eigenlenses to calculate the full shape of the crystalline lens in living subjects, using optical coherence tomography images, where data is limited to the information viewable via the pupil. In a comparison of eigenlenses with preceding crystalline lens shape estimation procedures, we exhibit enhancements in reproducibility, resistance to errors, and more efficient use of computing resources. The crystalline lens's complete shape alterations, influenced by accommodation and refractive error, are efficiently described using eigenlenses, as our research has shown.

Employing a programmable phase-only spatial light modulator in a low-coherence, full-field spectral-domain interferometer, we introduce tunable image-mapping optical coherence tomography (TIM-OCT), thus achieving optimized imaging performance for a given application. A snapshot of the resultant system, devoid of moving parts, can offer either exceptional lateral resolution or exceptional axial resolution. Alternatively, the system can acquire high resolution in all dimensions using a multi-shot approach. TIM-OCT's imaging capabilities were evaluated using both standard targets and biological samples. We also presented the integration of TIM-OCT and computational adaptive optics to compensate for sample-created optical imperfections.

As a buffer material for STORM microscopy, we analyze the potential of the commercially available mounting medium, Slowfade diamond. Our findings reveal that this technique, while proving ineffective with the prevalent far-red dyes frequently used in STORM imaging, such as Alexa Fluor 647, demonstrates outstanding performance with various green-excitable fluorophores, including Alexa Fluor 532, Alexa Fluor 555, or the alternative CF 568. Subsequently, image acquisition is feasible several months after the samples are mounted and stored in this refrigerated environment, providing a convenient method to maintain samples for STORM imaging and to retain calibration samples, for instance in metrology or educational environments, specifically in imaging laboratories.

Due to cataracts, the crystalline lens diffuses more light, resulting in retinal images of reduced contrast and visual impairment. Wave correlation of coherent fields, defining the Optical Memory Effect, enables imaging through scattering media. This research project focuses on the scattering characteristics of excised human crystalline lenses, including assessments of their optical memory effect and various objective scattering parameters, seeking to identify any existing relationships. GW4869 This project is expected to yield improvements in fundus imaging in cases of cataracts, along with the development of non-invasive vision correction strategies relating to cataracts.

Subcortical ischemic stroke pathophysiology research is hampered by the lack of a robust and accurate model of subcortical small vessel occlusion. In this study, a minimally invasive subcortical photothrombotic small vessel occlusion model in mice was developed using in vivo real-time fiber bundle endomicroscopy (FBE). Employing our FBF system, the precise targeting of deep brain blood vessels permitted simultaneous observation of clot formation and blood flow blockage occurring within the target vessel during photochemical reactions. In order to induce a targeted occlusion in small vessels, a fiber bundle probe was surgically implanted directly into the anterior pretectal nucleus of the thalamus in the brains of live mice. A patterned laser was utilized to perform targeted photothrombosis, with the dual-color fluorescence imaging system employed to monitor the procedure. Day one post-occlusion, TTC staining is used to measure the infarct area, followed by histologic analysis. GW4869 FBE, applied to targeted photothrombosis, results in a subcortical small vessel occlusion model of lacunar stroke, as the data shows.