41 citations · 90 across the 7 of their papers we have counts for
7 papers
Rapid 3D imaging at cellular resolution for digital cytopathology with a multi-camera array scanner (MCAS)
Kanghyun Kim, Amey Chaware, Clare B. Cook +16
Optical microscopy has long been the standard method for diagnosis in cytopathology. Whole slide scanners can image and digitize large sample areas automatically, but are slow, exp…
Parallelized computational 3D video microscopy of freely moving organisms at multiple gigapixels per second
Kevin C. Zhou, Mark Harfouche, Colin L. Cooke +17
To study the behavior of freely moving model organisms such as zebrafish (Danio rerio) and fruit flies (Drosophila) across multiple spatial scales, it would be ideal to use a light…
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 "…
Increasing a microscope's effective field of view via overlapped imaging and machine learning
Xing Yao, Vinayak Pathak, Haoran Xi +9
This work demonstrates a multi-lens microscopic imaging system that overlaps multiple independent fields of view on a single sensor for high-efficiency automated specimen analysis.…
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…