An identification device for identifying identifiers on and/or features of laboratory objects and/or of samples located therein in conjunction with automated laboratory systems or facilities, for example, medical, chemical, or pharmaceutical analysis devices. Barcodes on sample containers, for example, sample tubes, reagent tubs, or microplates are used, for example, as identifiers. An optical recording unit and a mirror are used, the spacing is variable for the detection of laboratory objects, each at different distances, from a recording distance by the optical recording unit is within a depth of field of the optical recording unit. The mirror is used for imaging the laboratory object to be detected on the optical axis. The identification device is substantially simplified, more reliable, and more cost-effective in comparison to known devices that use a zoom lens together with an autofocus unit.

The invention relates to a biopsy container (10) with an identification mark (13), which comprises one or more curves that surround the biopsy container. Identification information of the biopsy container may be encoded in a plurality of widths of the curves surrounding the biopsy container as well as in distances between these curves. Additionally, the biopsy container may comprise an alignment mark (11), which is configured to facilitate the registration of images of the biopsy container. The invention also relates to systems configured to determine identification information of a biopsy container and an image processing method.

Disclosed is a biological analyte monitoring device including a strip inserter in which a test strip is to be inserted, and a processor configured to read a code sequence based on an element detected from an index region, a first code region, and a second code region of the test strip in response to the test strip being inserted in the strip inserter, wherein the processor is further configured to determine a target interval in which an index element formed in the index region is detected while the test strip is being inserted in the strip inserter, detect a first code element formed in the first code region in the target interval and detect a second code element formed in the second code region in the target interval, and identify the code sequence based on a result of detecting the first code element and the second code element.

Tissue sample management systems include a central network, a medical professional system, and a pathology lab system for processing a tissue sample in a matrix having a sectionable code. At least the pathology lab system includes at least one imaging device, and the central network is configured to process images from the at least one imaging device to identify and record at least the sectionable code of the matrix. Methods for tissue sample processing include providing a matrix having a sectionable code and measurement marks, the matrix for receiving a tissue sample, and identifying the sectionable code from an image taken of the tissue sample in the matrix. Tissue sample-receiving matrices include a sectionable alphanumeric code or bar code, a tissue sample receptacle, and measurement marks formed along a sidewall thereof. The matrices include one or more proteins and one or more lipids.

A method of tube slot localization is provided using a tray coordinate system and a camera coordinate system. The method includes receiving, a series of images from at least one camera of a tray comprising tube slots arranged in a matrix of rows and columns. Each tube slot is configured to receive a sample tube. The method also includes automatically detecting fiducial markers disposed on cross sectional areas between the tube slots on the tray and receiving an encoder value indicating when each row of the tray is substantially at the center of the camera's field of view. The method further includes determining calibration information to provide mapping of locations from the tray coordinate system to locations from the camera coordinate system and automatically aligning the tray based on the encoder value and calibration information.

A method for optically reading information encoded in a microfluidic device, the microfluidic device including an input microchannel, microfluidic modules, and sets of nodes. Nodes of a first set connect the input microchannel to one of the microfluidic modules, and nodes of a second set connect the one of the microfluidic modules to another to form an ordered pair of the microfluidic modules, where the nodes of the first and second sets have different liquid pinning strengths. A liquid loaded into the input microchannel causes an ordered passage of the liquid through each of the microfluidic modules in an order determined by the liquid pinning strengths of the nodes. The passage of the liquid produces an optically readable dynamic pattern which evolves in accordance with the ordered passage of the liquid through the device.

A kit comprises one or more sample containers adapted to receive a sample and an embedding substance solidifiable to embed items in the sample container. A liquid embedding substance is adapted to be received in an inner cavity of the sample container. An identification label adapted to be received in an inner cavity of the sample container and configured to have data identifying the sample in the sample container, the label being resistant to chemicals of the embedding substance. The kit may be assembled into the sample container, solidified embedding substance in an inner cavity of the sample container, a sample embedded in the solidified embedding substance, and an identification label embedded in the solidified embedding substance, the identification label having data identifying the sample.

A method of characterizing a serum and plasma portion of a specimen in regions occluded by one or more labels. The characterization may be used for Hemolysis, Icterus, and/or Lipemia, or Normal detection. The method captures one or more images of a labeled specimen container including a serum or plasma portion, processes the one or more images to provide segmentation data and identification of a label-containing region, and classifying the label-containing region with a convolutional neural network (CNN) to provide a pixel-by-pixel (or patch-by-patch) characterization of the label thickness count, which may be used to adjust intensities of regions of a serum or plasma portion having label occlusion. Optionally, the CNN can characterize the label-containing region as one of multiple pre-defined label configurations. Quality check modules and specimen testing apparatus adapted to carry out the method are described, as are other aspects.

A sample-containing device configured to be placed into a sample processing instrument for performing a process on a sample contained in the device includes redundant identification features, such as machine-readable tags. A first machine-readable information tag is read before the device is placed in the instrument, and a second machine-readable information tag is read after the device is in the instrument. Information read from the two tags is compared to determine if there is proper correspondence between the information read from the tags to ensure that the correct sample processing device was placed in the instrument.

An identification device for identifying identifiers on and/or features of laboratory objects and/or of samples located therein in conjunction with automated laboratory systems or facilities, for example, medical, chemical, or pharmaceutical analysis devices. Barcodes on sample containers, for example, sample tubes, reagent tubs, or microplates are used, for example, as identifiers. An optical recording unit and a mirror are used, the spacing is variable for the detection of laboratory objects, each at different distances, from a recording distance by the optical recording unit is within a depth of field of the optical recording unit. The mirror is used for imaging the laboratory object to be detected on the optical axis. The identification device is substantially simplified, more reliable, and more cost-effective in comparison to known devices that use a zoom lens together with an autofocus unit.