GANscan:continuous scanning microscopy using deep learning deblurring

作     者：Michael John Fanous Gabriel Popescu Michael John Fanous;Gabriel Popescu

作者机构：Quantitative Light Imaging LaboratoryBeckman Institute for Advanced Science and TechnologyUniversity of Illinois at Urbana-ChampaignUrbanaIL 61801USA Department of BioengineeringUniversity of Illinois at Urbana-Champaign306 N.Wright StreetUrbanaIL 61801USA Department of Electrical and Computer EngineeringUniversity of Illinois at Urbana-Champaign306 N.Wright StreetUrbanaIL 61801USA 

出 版 物：《Light(Science & Applications)》 (光（科学与应用)（英文版）)

年 卷 期：2022年第11卷第10期

页      面：2378-2387页

核心收录：

学科分类：08[工学] 0803[工学-光学工程] 

基　　金：This work was funded bythe National Institute of Health(R01CA238191 R01GM129709) 

主　　题：hardware continuous image 

摘      要：Most whole slide imaging(WSI)systems today rely on thestop-and-stareapproach,where,at each field of view,the scanning stage is brought to a complete stop before the camera snaps a *** procedure ensures that each image is free of motion blur,which comes at the expense of long acquisition *** order to speed up the acquisition process,especially for large scanning areas,such as pathology slides,we developed an acquisition method in which the data is acquired continuously while the stage is moving at high *** generative adversarial networks(GANs),we demonstrate this ultra-fast imaging approach,referred to as GANscan,which restores sharp images from motion blurred *** allows us to complete image acquisitions at 30x the throughput of stop-and-stare *** method is implemented on a Zeiss Axio Observer Z1 microscope,requires no specialized hardware,and accomplishes successful reconstructions at stage speeds of up to 5000 μm/*** validate the proposed method by imaging H&E stained tissue *** method not only retrieves crisp images from fast,continuous scans,but also adjusts for defocusing that occurs during scanning within+/-5 μ*** a consumer GPU,the inference runs at20 ms/image.