Essenlix Corporation (Monmouth Junction, NJ)
This invention relates to correction of errors within equipment, operations and operation. through smart monitors, machine learning and various.
Accuracy is crucial when it comes to chemical and biological tests such as a complete blood cell count. However, the errors are unavoidable in instrumentation and operation, particularly, when using low-cost instruments and under resource-limitedconditions. This invention offers instruments and methods that improve the accuracy of image-based biological/chemical analysis of samples.
The following brief summary is not intended to include all the features and characteristics of the invention.
One of the features of the invention a method to enhance imaging-based tests by using a sample hold device equipped with special monitoring mechanisms to assay accuracy and efficiency, error detection, monitoring or any combination thereof.
Another aspect of the present invention is a method of micro-selective-image-assaying (MSIA) that can perform multiple assaying applications on a single image of the sample taken by the imager.
Another feature of the present invention is the ability of detecting monitoring structures and determine their locations from the images of the specimen for assaying and combining machine learning with correction of errors using predetermined characteristics of the structure that are associated with the plurality of the monitored structures.
Another aspect of the present invention is a method to estimate the true-lateral-dimension (TLD) in the image-based assaying, from which the actual dimension or morphological features of the analytes in the image of the sample can be determined.
A method for determining the volume and size of the area-of interest in the image of a sample is a different feature of the invention. This allows for imaging-based assaying to be carried out on any sub-area that is flexible and granular.
Another feature of the invention concerns the evaluation of the performance of the sample-holding device and sample preparation using an image-based test based on images of monitoring structures within the device holding the sample.
Another feature of the present invention is a method for using the monitoring structures that are predesigned in the sample holding device to adjust the imager’s operation in the process of image-based assaying.
A further aspect of the invention is a method for eliminating foreign objects or imperfections from the image-based test using the image of the sample that was taken by the imager.
Another aspect of the invention is a method of developing machine learning models to be used in image-based assay that utilize intelligent monitoring structures in which two strategies that are based on the original image of the sample as well as on the sample images that have been transformed are described.
Another feature of the present invention is the actual application instance of imaging-based assaying for red blood cells in a complete blood count (CBC) by using the methods and algorithms described in the present invention.
A method of using an apparatus to improve imaging-based assays, comprising: (a) having a sample holder, comprising the first plate and second plates that face each other and a plurality of monitoring structures on a sample contact surface of oneor both plates, wherein the monitoring structures have at least one predesigned and predetermined parameter of geometry and/or an optical property, wherein the sample contact surface contacts a sample; (b) sandwiching a sample that contains or issuspected of containing an analyte between the respective sample contact surfaces of the two plates to form a thin layer of 200 .mu.m thick or less, wherein the sample on the sample contact surface is mixed and reacts with a reagent), and wherein thesandwiching, mixing, or reacting is susceptible an error; (c) imaging, using an imager, the sample and the monitoring structures on the sample contact area together, wherein the imager is susceptible to a defect in imaging, and wherein the imagingoperation is susceptible an error; and (d) analyzing the images taken in step (c), using an algorithm, to detect a parameter related to the analyte, wherein the analysis comprises comparing the images with the at least one predesigned and predeterminedparameter and detecting and/or correcting the defect and errors using the at least one predesigned and predetermined parameter.
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