Differential phase contrast (DPC) is a non-interference quantitative phase imaging method achieved by asymmetric optical systems. Quantitative DPC images are achieved previously with asymmetric illumination systems. However, it works well for on-focus thin samples only. Considering the limitation, we develop a pupil modulation differential phase contrast (PMDPC) imaging method. Instead of modulating the illumination, we use a spatial light modulator (SLM) to modulate a 4f imaging system’s pupil plane. When half of the pupil plane is blocked by the SLM, a phase gradient image forms on the image plane. Using two such phase gradient images captured separately by applying complementary half-circle pupils on SLM, a DPC image can be constructed that carries the sample’s phase information. A quantitative phase image of the sample can be reconstructed after a deconvolution procedure. Further, we are able to combine this quantitative phase with the sample’s intensity image to obtain the complete complex object field which then allows us to post-process the image. We report experimentally that aberrations arising from the optical elements in the system can be corrected by deconvolving the reconstructed image with a pre-calibrated pupil function. We can also digitally extend the depth of field using angular spectrum propagation algorithm. With our PMDPC imaging setup where NA equals to 0.36, a quantitative phase image with periodic resolution of 1.73µm is obtained. The depth of field for a 20x, 0.4NA objective is extended digitally by 20 times to -50~50 micrometers.
We present a method to acquire both fluorescence and high-resolution bright-field images with correction for the spatially varying aberrations over a microscope’s wide field-of-view (FOV). First, the procedure applies Fourier ptychographic microscopy (FPM) to retrieve the amplitude and phase of a sample, at a resolution that significantly exceeds the cutoff frequency of the microscope objective lens. At the same time, FPM algorithm is able to leverage on the redundancy within the set of acquired FPM bright-field images to estimate the microscope aberrations, which usually deteriorate in regions further away from the FOV’s center. Second, the procedure acquires a raw wide-FOV fluorescence image within the same setup. Lack of moving parts allows us to use the FPM-estimated aberration map to computationally correct for the aberrations in the fluorescence image through deconvolution. Overlaying the aberration-corrected fluorescence image on top of the high-resolution bright-field image can be done with accurate spatial correspondence. This can provide means to identifying fluorescent regions of interest within the context of the sample’s bright-field information. An experimental demonstration successfully improves the bright-field resolution of fixed, stained and fluorescently tagged HeLa cells by a factor of 4.9, and reduces the error caused by aberrations in a fluorescence image by 31%, over a field of view of 6.2 mm by 9.3 mm. For optimal deconvolution, we show the fluorescence image needs to have a signal-to-noise ratio of ~18.
Circulating tumor cells (CTCs) are recognized as a candidate biomarker with strong prognostic and predictive potential in metastatic disease. Filtration-based enrichment technologies have been used for CTC characterization, and our group has previously developed a membrane microfilter device that demonstrates efficacy in model systems and clinical blood samples. However, uneven filtration surfaces make the use of standard microscopic techniques a difficult task, limiting the performance of automated imaging using commercially available technologies. Here, we report the use of Fourier ptychographic microscopy (FPM) to tackle this challenge. Employing this method, we were able to obtain high-resolution color images, including amplitude and phase, of the microfilter samples over large areas. FPM’s ability to perform digital refocusing on complex images is particularly useful in this setting as, in contrast to other imaging platforms, we can focus samples on multiple focal planes within the same frame despite surface unevenness. In model systems, FPM demonstrates high image quality, efficiency, and consistency in detection of tumor cells when comparing corresponding microfilter samples to standard microscopy with high correlation (R2=0.99932). Based on these results, we believe that FPM will have important implications for improved, high throughput, filtration-based CTC analysis, and, more generally, image analysis of uneven surfaces.
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