Li-cor, Inc.

Other

Patrick G Humphrey

Systems and methods for automatically identifying and characterizing one or more lanes in image data for one or more electrophoresed samples. The method includes receiving data representing an image of one or more electrophoresed samples, segmenting the data into one or multiple data segments or portions within a region of interest (ROI), wherein the one or multiple data segments represent (e.g., when visually displayed) one or multiple lane segments along a first axis in the ROI, each of the one or multiple lane segments traversing one or multiple lanes in the image data, generating an intensity profile for at least a first data segment of the one or multiple data segments along a second axis orthogonal to the first axis, and processing the intensity profile to determine a location and parameters for each of one or multiple lanes in the first data segment.

Adaptive lane detection systems and methods

Systems and methods for detecting, decoupling and quantifying unresolved signals in trace signal data in the presence of noise with no prior knowledge of the signal characteristics (e.g., signal peak location, intensity and width) of the unresolved signals. The systems and methods are useful for analyzing any trace data signals having one or multiple constituent signals, including overlapping constituent signals, and particularly useful for analyzing data signals which often contain an unknown number of constituent signals with varying signal characteristics, such as peak location, peak intensity and peak width, and varying resolutions and varying amounts of asymmetry. A general signal model function is assumed for each unknown, constituent signal in the trace signal data.

Adaptive asymmetrical signal detection and synthesis methods and systems

Systems and method for processing image data of an image to determine a signal quantification value for a signal of interest in the image data. The method includes identifying a first region of the image including a plurality of pixels, each pixel having a pixel intensity value, said first region including the signal of interest and a background signal component; determining, using the image data, a total number of discrete pixel intensity values for the plurality of pixels in the first region; calculating, for each discrete pixel intensity value, a total number of the pixels in the first region having that discrete pixel intensity value; determining a mean value of the background signal component based on the total number of pixels for each discrete pixel intensity value; and calculating a signal quantification value, for the signal of interest, that represents the signal of interest with the background signal component removed.

Adaptive background detection and signal quantification systems and methods

Systems and methods for detecting, decoupling and quantifying unresolved signals in trace signal data in the presence of noise with no prior knowledge of the signal characteristics (e.g., signal peak location, intensity and width) of the unresolved signals. The systems and methods are useful for analyzing any trace data signals having one or multiple constituent signals, including overlapping constituent signals, and particularly useful for analyzing data signals which often contain an unknown number of constituent signals with varying signal characteristics, such as peak location, peak intensity and peak width, and varying resolutions. A general signal model function is assumed for each unknown, constituent signal in the trace signal data.

Spectral response synthesis on trace data

Systems and methods for detecting, decoupling and quantifying unresolved signals in trace signal data in the presence of noise with no prior knowledge of the signal characteristics (e.g., signal peak location, intensity and width) of the unresolved signals. The systems and methods are useful for analyzing any trace data signals having one or multiple overlapping constituent signals and particularly useful for analyzing data signals which often contain an unknown number of constituent signals with varying signal characteristics, such as peak location, peak intensity and peak width, and varying resolutions. A general signal model function is assumed for each unknown, constituent signal in the trace signal data. In a first phase, the number of constituent signals and signal characteristics are determined automatically in a parallel fashion by executing multiple simultaneous evaluations iteratively starting with an initial set of trial signals. Making simultaneous evaluations and systematically reducing the number of trial signals allows for convergence to an optimal, final set of signals in a very fast and efficient manner.

Adaptive signal detection and synthesis on trace data

A method for applying a filter to data to improve data quality and/or reduce file size. In one example, a region of interest of an image is identified. A histogram is generated of pixel intensity values in the region of interest. The histogram is iteratively updated to focus (zoom) in on the highest peak in the histogram. A Gaussian curve is fitted to the updated histogram. A bilateral filter is applied to the images, where parameters of the bilateral filter are based on the parameters of the Gaussian curve.

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Lincoln, NE, United States of America

Patrick G Humphrey