University of Illinois

Mikhail Eugene Kandel

Gabriel Popescu

Matthew B Wheeler

Marcello Rubessa

Yuchen He

Tan Huu Nguyen

Nahil A Sobh

A system generates a context mask based on quantitative image data. The system obtains the quantitative image data which was captured via a quantitative imaging of a sample. The quantitative image data is compared to previous quantitative image data through application of the quantitative image data to a neural network trained using the previous quantitative image data and corresponding constructed context masks. The comparison generates the context mask for the quantitative image data. The context mask provides context for the quantitative parameter values that facilities characterization of the sample.

Complex system for contextual mask generation based on quantitative imaging

A system and methods for quantitative optical phase imaging of a sample. First second replica field of an image field are generated, characterized by a respective optical phase, cross-polarized and shifted in a shift direction transverse to a normal to the surface of the sample. The replica fields are Fourier transformed, the second replica field is retarded by four successive phase shifts, and, after inverse Fourier transforming, the first and second replica fields pass through an analyzer polarizer and superposing the first and second replica fields on a detector array to create four successive detector signals. The four successive detector signals are solved to derive a gradient of the optical phase of the image field, which may be integrated to obtain a quantitative phase image.

Gradient light interference microscopy for 3D imaging of unlabeled specimens

Growing community of inventors

Champaign, IL, United States of America

Mikhail Eugene Kandel