A large-field-of-view, high-throughput and high-resolution pathological section analyzer includes an image collector for collecting a set of computing microscopic images of a pathological section sample; a data preprocessing circuit for iteratively updating the set of computing microscopic images by a multi-height phase recovery algorithm to obtain a low-resolution reconstructed image; an image super-resolution circuit for super-resolving the low-resolution reconstructed image according to a pre-trained super-resolution model to obtain a high-resolution reconstructed image; and an image analysis circuit for automatically analyzing the high-resolution reconstructed image according to different tasks, and specifically selecting different analysis models according to the different tasks to obtain corresponding auxiliary diagnosis results. Imaging visual field of the pathological section analyzer is hundreds of times that of the traditional optical microscope, a deep learning network is adopted to analyze pathological conditions of unstained pathological sections, so that the analysis process of pathological sections is simplified.

A machine vision system uses lensless near-contact imaging with coherent illumination, or incoherent illumination, and high pixel count large format sensors (e.g., equivalent to at least 20 to 65 mega-pixels) to produce diffraction patterns of the micro-objects or the gray scale images of the micro-objects over a large overall field-of-view of the machine vision system. The machine vision system provides feedback to a microassembler system to position, orient, and assemble microscale devices, such as micro-LEDs, over large working areas. The effective resolution of the machine vision system can be further improved by using grayscale and super-resolution image processing techniques.

A machine vision system uses lensless near-contact imaging with coherent illumination, or incoherent illumination, and high pixel count large format sensors (e.g., equivalent to at least 20 to 65 mega-pixels) to produce diffraction patterns of the micro-objects or the gray scale images of the micro-objects over a large overall field-of-view of the machine vision system. The machine vision system provides feedback to a microassembler system to position, orient, and assemble microscale devices, such as micro-LEDs, over large working areas. The effective resolution of the machine vision system can be further improved by using grayscale and super-resolution image processing techniques.