High-throughput lensless whole slide imaging via continuous height-varying modulation of tilted sensor

TL;DR

This paper introduces a novel lensless microscopy method that uses a tilted sensor and lateral specimen translation to achieve high-throughput, high-resolution whole slide imaging without axial scanning, suitable for point-of-care applications.

Contribution

The work presents a new lensless imaging configuration combining ptychography and multi-height phase retrieval with lateral translation, enabling rapid, large-area imaging with precise height variation estimation.

Findings

Achieved 690 nm resolution with a 1.67-micron pixel sensor.

Captured a 120 mm^2 blood smear in 18 seconds.

Enabled automatic white blood cell counting from the images.

Abstract

We report a new 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 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 a 1.67-micron pixel size, our low-cost and field-portable prototype can resolve 690-nm linewidth on the resolution target. We show that a whole slide image of a blood smear with a 120-mm^2 field of view can be acquired in 18 seconds. 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.