Abstract: Disclosed herein are methods, systems, and computer-readable media for generating and using unbinned image data, characterized by (a) receiving image data corresponding to an image; (b) generating the unbinned image data by performing an unbinning operation on the received image data, wherein the unbinning operation is characterized by conditions of invertibility and smoothness; and (c) using the unbinned image data for either: (i) displaying a version of the image based on the unbinned image data; and/or (ii) performing image processing.

Abstract: Aspects relate to reconstructing phase images from brightfield images at multiple focal planes using machine learning techniques. A machine learning model may be trained using a training data set comprised of matched sets of images, each matched set of images comprising a plurality of brightfield images at different focal planes and, optionally, a corresponding ground truth phase image. An initial training data set may include images selected based on image views of a specimen that are substantially free of undesired visual artifacts such as dust. The brightfield images of the training data set can then be modified based on simulating at least one visual artifact, generating an enhanced training data set for use in training the model. Output of the machine learning model may be compared to the ground truth phase images to train the model. The trained model may be used to generate phase images from input data sets.

Abstract: Certain configurations are described of methods and systems that can be used to image three-dimensional objects such as biological cells, biological tissues or biological organisms. The methods and systems can image the three-dimensional objects at reduced imaging times and with reduced data volumes.

Abstract: Described herein are computationally efficient systems and methods for processing and analyzing two-dimensional (2D) and three-dimensional (3D) images using texture filters that are based on the Hessian eigenvalues (e.g., eigenvalues of a square matrix of second-order partial derivatives) of each pixel or voxel. The original image may be a single image or a set of multiple images. In certain embodiments, the filtered images are used to calculate texture feature values for objects such as cells identified in the image. Once objects are identified, the filtered images can be used to classify the objects, for image segmentation, and/or to quantify the objects (e.g., via regression).

Abstract: Aspects relate to reconstructing phase images from brightfield images at multiple focal planes using machine learning techniques. A machine learning model may be trained using a training data set comprised of matched sets of images, each matched set of images comprising a plurality of brightfield images at different focal planes and, optionally, a corresponding ground truth phase image. An initial training data set may include images selected based on image views of a specimen that are substantially free of undesired visual artifacts such as dust. The brightfield images of the training data set can then be modified based on simulating at least one visual artifact, generating an enhanced training data set for use in training the model. Output of the machine learning model may be compared to the ground truth phase images to train the model. The trained model may be used to generate phase images from input data sets.

Abstract: Certain configurations are described of methods and systems that can be used to image three-dimensional objects such as biological cells, biological tissues or biological organisms. The methods and systems can image the three-dimensional objects at reduced imaging times and with reduced data volumes.

Abstract: Certain configurations are described of methods and systems that can be used to image three-dimensional objects such as biological cells, biological tissues or biological organisms. The methods and systems can image the three-dimensional objects at reduced imaging times and with reduced data volumes.

Abstract: Certain configurations are described of methods and systems that can be used to image three-dimensional objects such as biological cells, biological tissues or biological organisms. The methods and systems can image the three-dimensional objects at reduced imaging times and with reduced data volumes.

Abstract: Described herein are computationally efficient systems and methods for processing and analyzing two-dimensional (2D) and three-dimensional (3D) images using texture filters that are based on the Hessian eigenvalues (e.g., eigenvalues of a square matrix of second-order partial derivatives) of each pixel or voxel. The original image may be a single image or a set of multiple images. In certain embodiments, the filtered images are used to calculate texture feature values for objects such as cells identified in the image. Once objects are identified, the filtered images can be used to classify the objects, for image segmentation, and/or to quantify the objects (e.g., via regression).

Abstract: Described herein is a method for adjusting one or more images of a sample to correct geometric distortions and/or to properly align the one or more images using a pattern of dots, e.g., a quasiperiodic grid.

Abstract: A method for identifying the impact on data, such as experimental data, of interfering effects, such as unwanted auto-fluorescence, fluorescence quenching, and fluorescent-sample deterioration, whether or not the data fulfill certain criteria with respect to a threshold indicative of the interfering effects.

Abstract: Described herein is a method for adjusting one or more images of a sample to correct geometric distortions and/or to properly align the one or more images using a pattern of dots, e.g., a quasiperiodic grid.

Abstract: An apparatus for confocal observation of a specimen includes an illumination device. The illumination device generates illumination radiations of at least two different wavelengths. With the aid of a mask device illuminated by the illumination radiations, one mask image is generated per wavelength. An objective serves for imaging said mask images in the specimen. With the aid of a beam splitter device, the emission radiations emitted by the specimen are divided based on the wavelengths, and are detected based on the wavelengths by a detection device.

Abstract: Described herein is a method for adjusting one or more images of a sample to correct geometric distortions and/or to properly align the one or more images using a pattern of dots, e.g., a quasiperiodic grid.

Abstract: An apparatus for confocal observation of a specimen includes an illumination device. The illumination device generates illumination radiations of at least two different wavelengths. With the aid of a mask device illuminated by the illumination radiations, one mask image is generated per wavelength. An objective serves for imaging said mask images in the specimen. With the aid of a beam splitter device, the emission radiations emitted by the specimen are divided based on the wavelengths, and are detected based on the wavelengths by a detection device.

Abstract: Described herein is a method for adjusting one or more images of a sample to correct geometric distortions and/or to properly align the one or more images using a pattern of dots, e.g., a quasiperiodic grid.

Abstract: Methods and apparatus are provided for image analysis and modification using a fast sliding parabola erosion. The methods include selecting a scan line in an image and performing a unidirectional left-hand pass followed by a unidirectional right-hand pass. The unidirectional passes are performed as loops with increasing distance. By utilizing simple unidirectional left-hand and right-hand passes along a scan line in an image, the erosion procedure is greatly simplified and computation times are significantly reduced.

Abstract: The invention provides a method for identifying the impacts of interfering effects on experimental data. In particular, a method is described for identifying the impacts of unwanted auto-fluorescence, fluorescence quenching, and deterioration of a fluorescent sample under study on the collected experimental data. The data are analyzed whether or not said data fulfill certain criteria with respect to a threshold which is indicative for said interfering effect.

Abstract: The invention provides a method for identifying the impacts of interfering effects on experimental data. In particular, a method is described for identifying the impacts of unwanted auto-fluorescence, fluorescence quenching, and deterioration of a fluorescent sample under study on the collected experimental data. The data are analyzed whether or not said data fulfill certain criteria with respect to a threshold which is indicative for said interfering effect.

Abstract: A method for detecting a biochemical interaction between at least two interaction partners, comprising the steps of bringing into contact the at least two interaction partners, taking a temporal sequence of measurements, each of them producing a measurement value describing the state of the interaction at a given point in time, adapting a mathematical model to the temporal sequence of measurements, whereby the model contains at least one first parameter characterising a temporal phase of increasing measurement values and at least one second parameter characterising a temporal phase of decreasing measurement values, and detecting the biochemical interaction by evaluating the first and second parameter.