Purdue Research Foundation

Sheng Liu

Fang Huang

Peiyi Zhang

A fluorescent single molecule emitter simultaneously transmits its identity, location, and cellular context through its emission patterns. A deep neural network (DNN) performs multiplexed single-molecule analysis to enable retrieving such information with high accuracy. The DNN can extract three-dimensional molecule location, orientation, and wavefront distortion with precision approaching the theoretical limit of information content of the image which will allow multiplexed measurements through the emission patterns of a single molecule.

Analyzing complex single molecule emission patterns with deep learning

A system for reducing noise in a camera image is disclosed. The system includes one or more processors, and a camera operatively coupled to the processor, the processors are configured to reduce noise of camera images, the processors are configured to receive input image data from the camera representing pixel data from a plurality of pixels, segment the input image data to a plurality of segments and for each segment establish an initial segment image, pre-correct pixel data by modifying the pixel data to account for voltage offset and gain of each pixel based on a predetermined map of gain and offset, and obtain an estimate of an output image by minimizing a cost function and output and stitch the estimated image to other estimated and outputted image segments, and output a noise reduced image including the stitched estimated images.

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Lafayette, IN, United States of America

Sheng Liu