Ting-Wei Su

Imaging without lenses: achievements and remaining challenges of wide-field on-chip microscopy

We discuss unique features of lens-free computational imaging tools and report some of their emerging results for wide-field on-chip microscopy, such as the achievement of a numerical aperture (NA) of ∼0.8–0.9 across a field of view (FOV) of more than 20 mm2 or an NA of ∼0.1 across a FOV of ∼18 cm2, which corresponds to an image with more than 1.5 gigapixels. We also discuss the current challenges that these computational on-chip microscopes face, shedding light on their future directions and applications.

Lensfree on-chip microscopy over a wide field-of-view using pixel super-resolution

We demonstrate lensfree holographic microscopy on a chip to achieve ~0.6 µm spatial resolution corresponding to a numerical aperture of ~0.5 over a large field-of-view of ~24 mm2. By using partially coherent illumination from a large aperture (~50 µm), we acquire lower resolution lensfree in-line holograms of the objects with unit fringe magnification. For each lensfree hologram, the pixel size at the sensor chip limits the spatial resolution of the reconstructed image. To circumvent this limitation, we implement a sub-pixel shifting based super-resolution algorithm to effectively recover much higher resolution digital holograms of the objects, permitting sub-micron spatial resolution to be achieved across the entire sensor chip active area, which is also equivalent to the imaging field-of-view (24 mm2) due to unit magnification. We demonstrate the success of this pixel super-resolution approach by imaging patterned transparent substrates, blood smear samples, as well as Caenoharbditis Elegans.

High-throughput lensfree 3D tracking of human sperms reveals rare statistics of helical trajectories

Dynamic tracking of human sperms across a large volume is a challenging task. To provide a high-throughput solution to this important need, here we describe a lensfree on-chip imaging technique that can track the three-dimensional (3D) trajectories of > 1,500 individual human sperms within an observation volume of approximately 8–17 mm3. This computational imaging platform relies on holographic lensfree shadows of sperms that are simultaneously acquired at two different wavelengths, emanating from two partially-coherent sources that are placed at 45° with respect to each other. This multiangle and multicolor illumination scheme permits us to dynamically track the 3D motion of human sperms across a field-of-view of > 17 mm2 and depth-of-field of approximately 0.5–1 mm with submicron positioning accuracy. The large statistics provided by this lensfree imaging platform revealed that only approximately 4–5% of the motile human sperms swim along well-defined helices and that this percentage can be significantly suppressed under seminal plasma. Furthermore, among these observed helical human sperms, a significant majority (approximately 90%) preferred right-handed helices over left-handed ones, with a helix radius of approximately 0.5–3 μm, a helical rotation speed of approximately 3–20 rotations/s and a linear speed of approximately 20–100 μm/s. This high-throughput 3D imaging platform could in general be quite valuable for observing the statistical swimming patterns of various other microorganisms, leading to new insights in their 3D motion and the underlying biophysics.

Lensless wide-field fluorescent imaging on a chip using compressive decoding of sparse objects

We demonstrate the use of a compressive sampling algorithm for on-chip fluorescent imaging of sparse objects over an ultra-large field-of-view (>8 cm2) without the need for any lenses or mechanical scanning. In this lensfree imaging technique, fluorescent samples placed on a chip are excited through a prism interface, where the pump light is filtered out by total internal reflection after exciting the entire sample volume. The emitted fluorescent light from the specimen is collected through an on-chip fiber-optic faceplate and is delivered to a wide field-of-view opto-electronic sensor array for lensless recording of fluorescent spots corresponding to the samples. A compressive sampling based optimization algorithm is then used to rapidly reconstruct the sparse distribution of fluorescent sources to achieve ~10 µm spatial resolution over the entire active region of the sensor-array, i.e., over an imaging field-of-view of >8 cm2. Such a wide-field lensless fluorescent imaging platform could especially be significant for high-throughput imaging cytometry, rare cell analysis, as well as for micro-array research.

High-Throughput Lens-Free Blood Analysis on a Chip

We present a detailed investigation of the performance of lens-free holographic microscopy toward high-throughput on-chip blood analysis. Using a spatially incoherent source that is emanating from a large aperture, automated counting of red blood cells with minimal sample preparation steps at densities reaching up to approximately 0.4 x 10(6) cells/muL is presented. Using the same lens-free holographic microscopy platform, we also characterize the volume of the red blood cells at the single-cell level through recovery of the optical phase information of each cell. We further demonstrate the measurement of the hemoglobin concentration of whole blood samples as well as automated counting of white blood cells, also yielding spatial resolution at the subcellular level sufficient to differentiate granulocytes, monocytes, and lymphocytes from each other. These results uncover the prospects of lens-free holographic on-chip imaging to provide a useful tool for global health problems, especially by facilitating whole blood analysis in resource-poor environments.

Compact and Light-Weight Automated Semen Analysis Platform Using Lensfree on-Chip Microscopy

We demonstrate a compact and lightweight platform to conduct automated semen analysis using a lensfree on-chip microscope. This holographic on-chip imaging platform weighs ∼46 g, measures ∼4.2 × 4.2 × 5.8 cm, and does not require any lenses, lasers or other bulky optical components to achieve phase and amplitude imaging of sperms over ∼24 mm(2) field-of-view with an effective numerical aperture of ∼0.2. Using this wide-field lensfree on-chip microscope, semen samples are imaged for ∼10 s, capturing a total of ∼20 holographic frames. Digital subtraction of these consecutive lensfree frames, followed by appropriate processing of the reconstructed images, enables automated quantification of the count, the speed and the dynamic trajectories of motile sperms, while summation of the same frames permits counting of immotile sperms. Such a compact and lightweight automated semen analysis platform running on a wide-field lensfree on-chip microscope could be especially important for fertility clinics, personal male fertility tests, as well as for field use in veterinary medicine such as in stud farming and animal breeding applications.

Wide field-of-view lens-free fluorescent imaging on a chip

We demonstrate an on-chip fluorescent detection platform that can simultaneously image fluorescent micro-objects or labeled cells over an ultra-large field-of-view of 2.5 cm x 3.5 cm without the use of any lenses, thin-film filters and mechanical scanners. Such a wide field-of-view lensless fluorescent imaging modality, despite its limited resolution, might be very important for high-throughput screening applications as well as for detection and counting of rare cells within large-area microfluidic devices.

Increased space-bandwidth product in pixel super-resolved lensfree on-chip microscopy

Pixel-size limitation of lensfree on-chip microscopy can be circumvented by utilizing pixel-super-resolution techniques to synthesize a smaller effective pixel, improving the resolution. Here we report that by using the two-dimensional pixel-function of an image sensor-array as an input to lensfree image reconstruction, pixel-super-resolution can improve the numerical aperture of the reconstructed image by ~3 fold compared to a raw lensfree image. This improvement was confirmed using two different sensor-arrays that significantly vary in their pixel-sizes, circuit architectures and digital/optical readout mechanisms, empirically pointing to roughly the same space-bandwidth improvement factor regardless of the sensor-array employed in our set-up. Furthermore, such a pixel-count increase also renders our on-chip microscope into a Giga-pixel imager, where an effective pixel count of ~1.6–2.5 billion can be obtained with different sensors. Finally, using an ultra-violet light-emitting-diode, this platform resolves 225 nm grating lines and can be useful for wide-field on-chip imaging of nano-scale objects, e.g., multi-walled-carbon-nanotubes.

Lensfree Fluorescent On-Chip Imaging of Transgenic Caenorhabditis elegans Over an Ultra-Wide Field-of-View

We demonstrate lensfree on-chip fluorescent imaging of transgenic Caenorhabditis elegans (C. elegans) over an ultra-wide field-of-view (FOV) of e.g., >2–8 cm2 with a spatial resolution of ∼10µm. This is the first time that a lensfree on-chip platform has successfully imaged fluorescent C. elegans samples. In our wide-field lensfree imaging platform, the transgenic samples are excited using a prism interface from the side, where the pump light is rejected through total internal reflection occurring at the bottom facet of the substrate. The emitted fluorescent signal from C. elegans samples is then recorded on a large area opto-electronic sensor-array over an FOV of e.g., >2–8 cm2, without the use of any lenses, thin-film interference filters or mechanical scanners. Because fluorescent emission rapidly diverges, such lensfree fluorescent images recorded on a chip look blurred due to broad point-spread-function of our platform. To combat this resolution challenge, we use a compressive sampling algorithm to uniquely decode the recorded lensfree fluorescent patterns into higher resolution images, demonstrating ∼10 µm resolution. We tested the efficacy of this compressive decoding approach with different types of opto-electronic sensors to achieve a similar resolution level, independent of the imaging chip. We further demonstrate that this wide FOV lensfree fluorescent imaging platform can also perform sequential bright-field imaging of the same samples using partially-coherent lensfree digital in-line holography that is coupled from the top facet of the same prism used in fluorescent excitation. This unique combination permits ultra-wide field dual-mode imaging of C. elegans on a chip which could especially provide a useful tool for high-throughput screening applications in biomedical research.

High-Throughput Lensfree Imaging and Characterization of a Heterogeneous Cell Solution On a Chip

A high‐throughput on‐chip imaging platform that can rapidly monitor and characterize various cell types within a heterogeneous solution over a depth‐of‐field of ∼4 mm and a field‐of‐view of ∼10 cm2 is introduced. This powerful system can rapidly image/monitor multiple layers of cells, within a volume of ∼4 mL all in parallel without the need for any lenses, microscope‐objectives or any mechanical scanning. In this high‐throughput lensless imaging scheme, the classical diffraction pattern (i.e., the shadow) of each micro‐particle within the entire sample volume is detected in less than a second using an opto‐electronic sensor chip. The acquired shadow image is then digitally processed using a custom developed “decision algorithm” to enable both the identification of the particle location in 3D and the characterization of each micro‐particle type within the sample volume. Through experimental results, we show that different cell types (e.g., red blood cells, fibroblasts, etc.) or other micro‐particles all exhibit uniquely different shadow patterns and therefore can be rapidly identified without any ambiguity using the developed decision algorithm, enabling high‐throughput characterization of a heterogeneous solution. This lensfree on chip cell imaging platform shows a significant promise especially for medical diagnostic applications relevant to global health problems, where compact and cost‐effective diagnostic tools are urgently needed in resource limited settings. Biotechnol. Bioeng. 2009; 102: 856–868.