Adaptive pixel-super-resolved lensfree in-line digital holography for wide-field on-chip microscopy

Abstract

High-resolution wide field-of-view (FOV) microscopic imaging plays an essential role in various fields of biomedicine, engineering, and physical sciences. As an alternative to conventional lens-based scanning techniques, lensfree holography provides a new way to effectively bypass the intrinsical trade-off between the spatial resolution and FOV of conventional microscopes. Unfortunately, due to the limited sensor pixel-size, unpredictable disturbance during image acquisition, and sub-optimum solution to the phase retrieval problem, typical lensfree microscopes only produce compromised imaging quality in terms of lateral resolution and signal-to-noise ratio (SNR). Here, we propose an adaptive pixel-super-resolved lensfree imaging (APLI) method which can solve, or at least partially alleviate these limitations. Our approach addresses the pixel aliasing problem by Z-scanning only, without resorting to subpixel shifting or beam-angle manipulation. Automatic positional error correction algorithm and adaptive relaxation strategy are introduced to enhance the robustness and SNR of reconstruction significantly. Based on APLI, we perform full-FOV reconstruction of a USAF resolution target (~29.85 mm2) and achieve half-pitch lateral resolution of 770 nm, surpassing 2.17 times of the theoretical Nyquist–Shannon sampling resolution limit imposed by the sensor pixel-size (1.67µm). Full-FOV imaging result of a typical dicot root is also provided to demonstrate its promising potential applications in biologic imaging.

A super-resolution scanning algorithm for lensless microfluidic imaging using the dual-line array image sensor

“…As the angle is 10 degrees, the equivalent pixel size is 0.382μm. It is smaller than the equivalent pixel size of 0.775μm in paper [8] and 0.770μm in paper [20] by the pixel size image sensor (1.67μm).…”

“…Finally, the super-resolution image of the cells can be reconstructed. When the pixel size of the linear array sensor is 2.2μm and the angle is 21 degrees, the equivalent pixel size is 0.79μm (Improved 2.8 times, and improved 2.15 times in paper [8,20]). After de-diffraction, the size error of 20μm microsphere was 3.249%, and the PSNR was improved 1.62 times, the SSIM was improved 3.96 times.…”

Three-Dimensional High-Resolution Digital Inline Hologram Reconstruction with a Volumetric Deconvolution Method

“…Both the subpixel super-resolution hologram and Z -stacked phase retrieval approach reduce reconstruction artifacts and enhance the resolution by up to two times. However, one of the promising results, concerning the resolution enhancement and phase recovery effects of these approaches, is reported by the Zuo group [ 23 ], who reported that only a Z -stacked image set was needed to achieve both super subpixel resolution and phase recovery. The approach makes the imaging apparatus a simple and a mobile platform compared with other 3D image generation methods, such as multi-angle [ 22 ] and multi-wavelength [ 30 ] holographic image generation to minimize the movable parts of an apparatus.…”

“…The Zuo group introduced Z -stacked hologram images to obtain high-resolution holographic images, with sub-pixel super-resolution and phase recovery, without a sub-pixel shift [ 23 ]. This approach can be adapted for simplifying the apparatus without using the nanometer resolution of the XY stage to obtain a sub-pixel hologram image.…”

“…Based on the 2D DIHM technology and its various merits, 3D section imaging technologies relating to volumetric samples have been suggested for a thick clear tissue, widespread whole blood cells, and polystyrene beads on a sliding glass, i.e., 3D imaging of CLARITY tissue [ 14 ], three-dimensional profiling and tracking [ 15 , 16 ], angled tomography [ 17 ], 3D image distortion compensation [ 18 ], and wide-field pathology slide imaging [ 19 ]. There are two significant challenges that must be overcome to achieve a wide FOV high resolution 3D image: Phase recovery and spatial under-sampling, based on an iterative reconstruction with a single shot hologram [ 20 , 21 ], multi-angle [ 22 ], multi-height [ 23 ], spatial shift [ 24 ], colorization [ 25 ] for color artifacts [ 26 ], a scattering medium [ 27 ], a diffuser [ 28 ], a scattering mask [ 29 ], and multi-wavelength [ 30 ]. In this 2D image reconstruction and phase recovery, twin image and spatial aliasing signals, along with other digital artifacts, were solved using each separate technology or an integrated propagating phaser approach based on this idea [ 31 ].…”