Luminex Corporation

National Instruments Corporation

Mckenzie, Cynthia

Matthew S Fisher

Dinesh R Nair

Satish V Kumar

Lothar Wenzel

Ram Rajagopal

Darren R Schmidt

Kevin M Crotty

Nicolas Arab

Adam Richard Schilffarth

Wayne Dennis Roth

Subramanian Ramamoorthy

Bruce Smyth

David R Torgerson

Cynthia Mckenzie

Adam Schilffarth

An apparatus and method for image normalization using a Gaussian residual of fit selection criteria. The method may include acquiring a two-dimensional image of a plurality of particles, where the plurality of particles comprises a plurality of calibration particles, and identifying a calibration particle by correlating a portion of the image corresponding to the calibration particle to a mathematical model (e.g. Gaussian fit). The measured intensity of the calibration particle may then be used to normalize the intensity of the image.

Apparatus, system, and method for image normalization using a Gaussian residual of fit selection criteria

Methods and apparatuses for tracking and correlating particles include an optical detector that captures a first and a second image of the particles. A video detector is used to capture a plurality of video frames of the particles. The video detector captures the video frames of the particles at a rate faster than the rate at which images are captured by the optical detector to track the movement of particles. A first image position of a particle in the first image of the particles is identified, and then the first image position of the particle is correlated to a second image position of the particle in the second image using the plurality of video frames.

Real-time tracking and correlation of microspheres

Techniques are disclosed relating to assay configuration. Assay devices are often used to determine characteristics of test samples, e.g., using polymerase chain reaction (PCR) or Deoxyribonucleic Acid (DNA) melt techniques. Various disclosed techniques allow detailed specification of assay parameters. This may allow user modification of assays and/or assay development by third parties. In embodiments in which assay parameters are specified using a separate device, these techniques may reduce validation requirements resulting from modified assays. In some embodiments, assay configuration information that may be added/removed/modified may include: a sequence of operations, parameters for the sequence of operations, data processing parameters, call logic rules/dependencies, and/or reporting rules.

Detailed assay protocol specification

Apparatus, system, and method for image normalization using a gaussian residual of fit selection criteria

Embodiments of the computer-implemented methods, storage mediums, and systems may be configured to determine locations of particles within a first image of the particles. The particles may have fluorescence-material associated therewith. The embodiments may include calculating a transform parameter, and the transform parameter may define an estimated movement in the locations of the particles between the first image of the particles and a second image of the particles. The embodiments may further including applying the transform parameter to the locations of the particles within the first image to determine movement locations of the particles within the second image.

Methods and systems for image data processing

An apparatus, system, and method for increasing measurement accuracy in imaging cytometry. The system may include a light detector configured to measure light emitted by a particle in response to a first light source, and processor coupled to the light detector. The processor may be configured create a first image by taking a first measurement of light and create a second image by interpolating the first image, where the second image has higher resolution than the first image. The processor may be configured to determine a difference between pixels of the second image and an expected distribution and discard the first measurement of light if the difference is above a predetermined threshold.

Apparatus, system, and method for increasing measurement accuracy in a particle imaging device using light distribution

An apparatus, system, and method for increasing measurement accuracy in imaging cytometry. The system may include a light detector configured to measure light emitted by a first particle and light emitted by a second particle, where the measured light from the second particle at least partially overlaps the measured light from the first particle in an overlap region. Additionally, the system may include a processor coupled to the light detector, where the processor is configured to determine a contribution of light from the first particle in the overlap region and determine a contribution of light from the second particle in the overlap region. The processor may also be configured to subtract the contribution of light from the second particle from the contribution of light from the first particle and determine the intensity of light emitted by the first particle.

Apparatus, system, and method for increasing measurement accuracy in a particle imaging device

A geometric pattern matching method to locate instances of a template image in a target image using a plurality of models with different feature combinations. A learning phase involves learning geometric information about the template image and creating a model for each of a plurality of different respective parent features. Each model comprises a relationship tree from the respective parent feature to one or more other child features, and hence each model may have different feature combinations. In a matching phase, the method may examine a plurality of different models to determine matches in the target image being analyzed. The matching phase may select different models dynamically based on prior matching results.

Geometric pattern matching using dynamic feature combinations

System and method for determining the presence of an object of interest in a target data set. Portions of a target data set may be located that match an object of interest, e.g., in a template data set, with respect to various information, e.g., edge or boundary information. The invention includes improved methods for mapping point sets or curves to new point sets or curves for curve matching. The method determines the presence of an object of interest in a target data set despite of or using various types of topological transformations of the object of interest in the target data set. One or more mapping operators are determined based on template curves and/or example target curves. Pattern matching is performed on one or more target data sets using the mapping operator(s) to generate pattern matching results, and the pattern matching results output.

Pattern matching system utilizing discrete curve matching with a mapping operator

System and method for determining the presence of an object of interest in a target image. Regions of a target image may be located that match an object of interest, e.g., in a template image, with respect to various information, e.g., luminance, color and/or other types of boundary information. The invention includes improved methods for mapping point sequences (e.g., pixel sequences) or curves to new point sets or curves for curve matching. The method determines the presence of an object of interest in a target image despite of or using various types of topological transformations of the object of interest in the target image. One or more mapping operators are determined based on template curves and/or example target curves. Pattern matching is performed on one or more target images using the mapping operator(s) to generate pattern matching results, and the pattern matching results output.

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Austin, TX, United States of America

Matthew S Fisher