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Programmable illumination control is essential for many computational microscopy techniques. Conventional light source array is often arranged on a fixed grid of a planar surface for providing programmable sample illumination. Here, we report the development of a freeform illuminator that can be arranged at arbitrary 2-dimensional or 3-dimensional (3D) surface structures for computational microscopy. The freeform illuminator can be designed in a small form factor with a dense light source arrangement in 3D. It can be placed closer to the sample for providing angle-varied illumination with higher optical flux and smaller angular increment. With the freeform illuminators, we develop a calibration process using a low-cost Raspberry-Pi image sensor coated with a monolayer of blood cells. By tracking the positional shift of the blood-cell diffraction patterns at 2 distinct regions of the coded sensor, we can infer the 3D positions of the light source elements in a way similar to the stereo vision reconstruction approach. To demonstrate the applications for computational microscopy, we validate the freeform illuminators for Fourier ptychographic microscopy, 3D tomographic imaging, and on-chip microscopy. We also present a longitudinal study by tracking the growth of live bacterial cultures over a large field of view. The reported freeform illuminators and the related calibration process offer flexibilities and extended scope for imaging innovations in computational microscopy. 

The applications of conventional ptychography are limited by its relatively low resolution and throughput in the visible light regime. The new development of coded ptychography (CP) has addressed these issues and achieved the highest numerical aperture for large-area optical imaging in a lensless configuration. A high-quality reconstruction of CP relies on precise tracking of the coded sensor’s positional shifts. The coded layer on the sensor, however, prevents the use of cross correlation analysis for motion tracking. Here we derive and analyze the motion tracking model of CP. A novel, to the best of our knowledge, remote referencing scheme and its subsequent refinement pipeline are developed for blind image acquisition. By using this approach, we can suppress the correlation peak caused by the coded surface and recover the positional shifts with deep sub-pixel accuracy. In contrast with common positional refinement methods, the reported approach can be disentangled from the iterative phase retrieval process and is computationally efficient. It allows blind image acquisition without motion feedback from the scanning process. It also provides a robust and reliable solution for implementing ptychography with high imaging throughput. We validate this approach by performing high-resolution whole slide imaging of bio-specimens. 

The recent advent of whole slide imaging (WSI) systems has moved digital pathology closer to diagnostic applications and clinical practices. Integrating WSI with machine learning promises the growth of this field in upcoming years. Here we report the design and implementation of a handheld, colour-multiplexed, and AI-powered ptychographic whole slide scanner for digital pathology applications. This handheld scanner is built using low-cost and off-the-shelf components, including red, green, and blue laser diodes for sample illumination, a modified stage for programmable sample positioning, and a synchronized image sensor pair for data acquisition. We smear a monolayer of goat blood cells on the main sensor for high-resolution lensless coded ptychographic imaging. The synchronized secondary sensor acts as a non-contact encoder for precisely tracking the absolute object position for ptychographic reconstruction. For WSI, we introduce a new phase-contrast-based focus metric for post-acquisition autofocusing of both stained and unstained specimens. We show that the scanner can resolve the 388-nm linewidth on the resolution target and acquire gigapixel images with a 14 mm × 11 mm area in ∼70 seconds. The imaging performance is validated with regular stained pathology slides, unstained thyroid smears, and malaria-infected blood smears. The deep neural network developed in this study further enables high-throughput cytometric analysis using the recovered complex amplitude. The reported do-it-yourself scanner offers a portable solution to transform the high-end WSI system into one that can be made widely available at a low cost. The capability of high-throughput quantitative phase imaging may also find applications in rapid on-site evaluations. 

We report the implementation of a fully on-chip, lensless microscopy technique termed optofluidic ptychography. This imaging modality complements the miniaturization provided by microfluidics and allows the integration of ptychographic microscopy into various lab-on-a-chip devices. In our prototype, we place a microfluidic channel on the top surface of a coverslip and coat the bottom surface with a scattering layer. The channel and the coated coverslip substrate are then placed on top of an image sensor for diffraction data acquisition. Similar to the operation of a flow cytometer, the device utilizes microfluidic flow to deliver specimens across the channel. The diffracted light from the flowing objects is modulated by the scattering layer and recorded by the image sensor for ptychographic reconstruction, where high-resolution quantitative complex images are recovered from the diffraction measurements. By using an image sensor with a 1.85 μm pixel size, our device can resolve the 550 nm linewidth on the resolution target. We validate the device by imaging different types of biospecimens, including C. elegans , yeast cells, paramecium , and closterium sp . We also demonstrate a high-resolution ptychographic reconstruction at a video framerate of 30 frames per second. The reported technique can address a wide range of biomedical needs and engenders new ptychographic imaging innovations in a flow cytometer configuration. 

We report a new, to the best of our knowledge, lensless microscopy configuration by integrating the concepts of transverse translational ptychography and defocus multi-height phase retrieval. In this approach, we place a tilted image sensor under the specimen for introducing linearly increasing phase modulation along one lateral direction. Similar to the operation of ptychography, we laterally translate the specimen and acquire the diffraction images for reconstruction. Since the axial distance between the specimen and the sensor varies at different lateral positions, laterally translating the specimen effectively introduces defocus multi-height measurements while eliminating axial scanning. Lateral translation further introduces sub-pixel shift for pixel super-resolution imaging and naturally expands the field of view for rapid whole slide imaging. We show that the equivalent height variation can be precisely estimated from the lateral shift of the specimen, thereby addressing the challenge of precise axial positioning in conventional multi-height phase retrieval. Using a sensor with 1.67 µm pixel size, our low-cost and field-portable prototype can resolve the 690 nm linewidth on the resolution target. We show that a whole slide image of a blood smear with a $120{\mathrm{m}\mathrm{m}}^2$field of view can be acquired in 18 s. We also demonstrate accurate automatic white blood cell counting from the recovered image. The reported approach may provide a turnkey solution for addressing point-of-care and telemedicine-related challenges. 

We report a novel lensless on-chip microscopy platform based on near-field blind ptychographic modulation. In this platform, we place a thin diffuser in between the object and the image sensor for light wave modulation. By blindly scanning the unknown diffuser to different x – y positions, we acquire a sequence of modulated intensity images for quantitative object recovery. Different from previous ptychographic implementations, we employ a unit magnification configuration with a Fresnel number of ∼50 000, which is orders of magnitude higher than those of previous ptychographic setups. The unit magnification configuration allows us to have the entire sensor area, 6.4 mm by 4.6 mm, as the imaging field of view. The ultra-high Fresnel number enables us to directly recover the positional shift of the diffuser in the phase retrieval process, addressing the positioning accuracy issue plaguing regular ptychographic experiments. In our implementation, we use a low-cost, DIY scanning stage to perform blind diffuser modulation. Precise mechanical scanning that is critical in conventional ptychography experiments is no longer needed in our setup. We further employ an up-sampling phase retrieval scheme to bypass the resolution limit set by the imager pixel size and demonstrate a half-pitch resolution of 0.78 μm. We validate the imaging performance via in vitro cell cultures, transparent and stained tissue sections, and a thick biological sample. We show that the recovered quantitative phase map can be used to perform effective cell segmentation of a dense yeast culture. We also demonstrate 3D digital refocusing of the thick biological sample based on the recovered wavefront. The reported platform provides a cost-effective and turnkey solution for large field-of-view, high-resolution, and quantitative on-chip microscopy. It is adaptable for a wide range of point-of-care-, global-health-, and telemedicine-related applications.