43 citations · 179 across the 14 of their papers we have counts for
6 papers · 1 filter
Digital staining in optical microscopy using deep learning -- a review
Lucas Kreiss, Shaowei Jiang, Xiang Li +13
Until recently, conventional biochemical staining had the undisputed status as well-established benchmark for most biomedical problems related to clinical diagnostics, fundamental…
Imaging across multiple spatial scales with the multi-camera array microscope
Mark Harfouche, Kanghyun Kim, Kevin C. Zhou +22
This article experimentally examines different configurations of a novel multi-camera array microscope (MCAM) imaging technology. The MCAM is based upon a densely packed array of "…
Transient motion classification through turbid volumes via parallelized single-photon detection and deep contrastive embedding
Shiqi Xu, Wenhui Liu, Xi Yang +11
Fast noninvasive probing of spatially varying decorrelating events, such as cerebral blood flow beneath the human skull, is an essential task in various scientific and clinical set…
Multi-element microscope optimization by a learned sensing network with composite physical layers
Kanghyun Kim, Pavan Chandra Konda, Colin L. Cooke +2
Standard microscopes offer a variety of settings to help improve the visibility of different specimens to the end microscope user. Increasingly, however, digital microscopes are us…
Physics-enhanced machine learning for virtual fluorescence microscopy
Colin L. Cooke, Fanjie Kong, Amey Chaware +7
This paper introduces a new method of data-driven microscope design for virtual fluorescence microscopy. Our results show that by including a model of illumination within the first…
Towards an Intelligent Microscope: adaptively learned illumination for optimal sample classification
Amey Chaware, Colin L. Cooke, Kanghyun Kim +1
Recent machine learning techniques have dramatically changed how we process digital images. However, the way in which we capture images is still largely driven by human intuition a…