Automatic substance preparation and evaluation systems and methods are provided for preparing and evaluating a fluidic substance, such as e.g. a sample with bodily fluid, in a container and/or in a dispense tip. The systems and methods can detect volumes, evaluate integrities, and check particle concentrations in the container and/or the dispense tip.

The present invention generally relates to a wearable electronic device that collects information about test sample using an optical sensor. The wearable device photographs and analyzes one or more organic samples placed on one or more immunoassay regions of a test strip in order to reveal information about the sample. The wearable electronic device may also sequentially photograph a plurality of individual organic samples applied to different immunoassay regions of a test strip.

The subject disclosure provides systems and methods for determination of Area of Interest (AOI) for different types of input slides. Slide thumbnails may be assigned into one of five different types, and separate algorithms for AOI detection executed depending on the slide type. Slide types include ThinPrep (RTM) slides, tissue micro-array (TMA) slides, control HER2 slides with 4 cores, smear slides, and a generic slide. The slide type may be assigned based on a user input. Customized AOI detection operations are provided for each slide type. If the user enters an incorrect slide type, operations include detecting the incorrect input and executing the appropriate method. The result of each AOI detection operations provides as its output a soft-weighted image having zero intensity values at pixels that are detected as not belonging to tissue, and higher intensity values assigned to pixels detected as likely belonging to tissue regions.

Systems and methods are provided for automatically imaging and analyzing cell samples in an incubator. An actuated microscope operates to generate images of samples within wells of a sample container across days, weeks, or months. A plurality of images is generated for each scan of a particular well, and the images within such a scan are used to image and analysis metabolically active cells in the well. Tins analysis includes generating a “range image” by subtracting the minimum intensity value, across the scan, for each pixel from the maximum intensity value. This range image thus emphasizes cells or portions of cells that exhibit changes in activity over a scan period (e.g., neurons, myocytes, cardiomyocytes) while de-emphasizing regions that exhibit consistently high intensities when images (e.g., regions exhibiting a great deal of autofluorescence unrelated to cell activity).

Techniques are described for dynamically correcting image distortion during imaging of a patterned sample having repeating spots. Different sets of image distortion correction coefficients may be calculated for different regions of a sample during a first imaging cycle of a multicycle imaging run and subsequently applied in real time to image data generated during subsequent cycles. In one implementation, image distortion correction coefficients may be calculated for an image of a patterned sample having repeated spots by: estimating an affine transform of the image; sharpening the image; and iteratively searching for an optimal set of distortion correction coefficients for the sharpened image, where iteratively searching for the optimal set of distortion correction coefficients for the sharpened image includes calculating a mean chastity for spot locations in the image, and where the estimated affine transform is applied during each iteration of the search.

A method for collection and dissemination of biologic data, comprising collecting at least one biologic sample by a testing device including thereon an alignment target and including a plurality of immunoassay test strips, wherein the at least one biologic sample contacts a sample pad on at least one of the plurality of immunoassay test strips, assigning correlative values as test results, wherein each test performed on the biologic sample is assigned a different correlative value, receiving the test results at a server disposed on a network, wherein the server has configured thereon a database, assigning a unique identification to the biologic sample, storing the unique identification in the database, storing the test results in the database in association with the unique identification of the biologic sample, and providing access to the database to healthcare organizations for analysis of the test results.

The technology disclosed relates to classification of process cycle images to predict success or failure of process cycles. The technology disclosed includes capturing and processing images of sections arranged on an image generating chip in genotyping process. Image description features of production cycle images are created and given as input to classifiers. A trained classifier separates successful production images from unsuccessful or failed production images. The failed production images are further classified by a trained root cause classifier into various categories of failure.

A contractile tissue-based analysis device is provided, in which a strip of contractile tissue is supported by support structure. The support structure comprises a substantially planar base element, and first and second support pillars extending from said base element. An optical detection device is arranged on the side of the base element opposite to said support pillars, and is arranged to capture image data from at least one of the head portions of the support pillars. The motion of the support pillars induced by the strip of contractile tissue can thus be captured from below, i.e. through the planar base element.

Biosensor including an array of reaction sites and corresponding light sensors may experience crosstalk in which photons from one reaction site are detected by neighbors of its corresponding light sensor, and such crosstalk may be corrected using sharpening kernels corresponding to the sensors in the array. Such sharpening kernels may be derived from point spread functions, which may be determined in real time analysis based on images captured during sequencing.

Disclosed herein are platforms, systems, and methods including a cell culture system that includes a cell culture container comprising a cell culture, the cell culture receiving input cells, a cell imaging subsystem configured to acquire images of the cell culture, a computing subsystem configured to perform a cell culture process on the cell culture according to the images acquired by the cell imaging subsystem, and a cell editing subsystem configured to edit the cell culture to produce output cell products according to the cell culture process.