公开(公告)号：US20230366801A1

公开(公告)日：2023-11-16

申请号：US18030034

申请日：2021-10-05

Applicant: Stichting VU ,  LUMICKS CA HOLDING B.V.

Inventor： Andreas Sebastian Biebricher ,  Vadim Bogatyr ,  Gijs Jan Lodewijk Wuite ,  Erwin Johannes Gerard Peterman ,  Iddo Heller ,  Rogier Martijn Reijmers

IPC: G01N15/14 ,  G06T7/60 ,  G06T7/20 ,  G06T7/70 ,  G06V20/69

CPC classification number: G01N15/1404 ,  G01N15/1434 ,  G06T7/60 ,  G06T7/20 ,  G06T7/70 ,  G06V20/698 ,  G01N2015/149 ,  G01N2015/1493 ,  G01N2015/1075

Abstract: A method comprises receiving images representing manipulating cellular bodies that includes exerting force pulses to the bodies on a wall surface; analyzing the images to determine the size of the bodies and tracking locations during and after each of force pulses, the tracking locations defining first trajectories of the bodies moving away from the wall surface and trajectories of the bodies moving towards the wall surface; determining densities of the bodies using the second trajectories and a sedimentation model of the bodies moving towards the wall surface and determining body velocities based on the first trajectories and a velocity model of the bodies moving away from the wall surface; and, determining a contrast factor for each body based on the sizes and the densities, the force applied to the bodies and the body velocities and determining a compressibility for each of the bodies based on the determined contrast factors.

公开(公告)号：US11817217B2

公开(公告)日：2023-11-14

申请号：US17117375

申请日：2020-12-10

Applicant: Tata Consultancy Services Limited

Inventor： Varsha Sharma ,  Chirayata Bhattacharyya ,  Tanuka Bhattacharjee ,  Murali Poduval ,  Sundeep Khandelwal ,  Anirban Dutta Choudhury

IPC: G16H50/30 ,  G16H50/70 ,  G16H40/67 ,  G06N20/00 ,  A61B5/00 ,  G06V20/69 ,  G06F18/2113 ,  G06F18/2132 ,  G06F18/214 ,  G06F18/21

CPC classification number: G16H50/30 ,  A61B5/412 ,  A61B5/7267 ,  G06F18/2113 ,  G06F18/2132 ,  G06F18/2148 ,  G06F18/2193 ,  G06N20/00 ,  G06V20/698 ,  G16H40/67 ,  G16H50/70

Abstract: Sepsis is one of the most prevalent causes of mortality in Intensive Care Units (ICUs) and delayed treatment is associated with increase in death and financial burden. There is no single laboratory test or clinical sign that by itself can be considered diagnostic of sepsis. The present disclosure provides discriminating domain specific continuous and categorical features that can reliably classify a subject being monitored into a sepsis class or a normal class. A combination of physiological parameters, laboratory parameters and demographic details are used to extract the discriminating features. Even though the parameters may be sporadic in nature, the systems and methods of the present disclosure make use of a sliding time window to generate continuous features that capture the trend in the sporadic data; and a binning approach to generate categorical features to discriminate deviation from the normal class and facilitate timely treatment.

公开(公告)号：US11815519B2

公开(公告)日：2023-11-14

申请号：US16632321

申请日：2018-07-16

Applicant: Siemens Healthcare Diagnostics Inc.

Inventor： Patrick Wissmann ,  Benjamin S. Pollack

IPC: G06T7/12 ,  G01N35/00 ,  G01J1/02 ,  G06T7/00 ,  G06T7/80 ,  G06V10/143 ,  G06V20/69 ,  G06V10/60

CPC classification number: G01N35/00732 ,  G01J1/0295 ,  G01N35/00623 ,  G01N35/00693 ,  G06T7/0012 ,  G06T7/80 ,  G06V10/143 ,  G06V20/698 ,  G06V10/60

Abstract: A quality check module for characterizing a specimen and/or a specimen container including stray light compensation. The quality check module includes an imaging location within the quality check module configured to receive a specimen container containing a specimen, one or more image capture devices configured to capture images of the imaging location from one or more viewpoints, and one or more light sources configured to provide back lighting for the one or more image capture devices, and one or more stray light patches located in an area receiving stray light from the one or more light sources enabling stray light affecting the images to be compensated for and to provide a stray light compensated image. Calibration methods, methods of characterizing a specimen, specimen testing apparatus including a quality check module, and specimen container carriers including one or more stray light patches are provided, as are other aspects.

公开(公告)号：US11808701B2

公开(公告)日：2023-11-07

申请号：US16769883

申请日：2018-12-04

Applicant: Wisconsin Alumni Research Foundation

Inventor： David Charles Schwartz ,  Subhrangshu Nandi ,  Michael Abbott Newton

IPC: G06K9/00 ,  G01N21/64 ,  G16B30/00 ,  C12Q1/6818 ,  G02B21/16 ,  G02B21/36 ,  G06V20/69

CPC classification number: G01N21/6428 ,  C12Q1/6818 ,  G01N21/6458 ,  G02B21/16 ,  G02B21/365 ,  G06V20/693 ,  G06V20/695 ,  G06V20/698 ,  G16B30/00 ,  G01N2021/6439 ,  G06V2201/03

Abstract: Systems and methods for identifying sequence information from measurements made on single nucleic acid molecules are disclosed. The systems and methods can include binding portions of nucleic acid molecules with marker molecules, such as fluorescent molecules and/or intercalating molecules. The marker molecules provide a detectable signal that includes information about the underlying genomic information of the location on the nucleic acid molecule where a given marker molecule is bound. A profile of the detectable signal along a position of the nucleic acid is acquired for multiple different nucleic acid molecules. The PRIMR algorithm processes the data to provide a consensus profile from which a consensus underlying genomic information can be determined.

公开(公告)号：US11804030B2

公开(公告)日：2023-10-31

申请号：US17697977

申请日：2022-03-18

Applicant: SYSMEX CORPORATION

Inventor： Hajimu Kawakami ,  Hirokazu Kurata

IPC: G06V20/69 ,  G06V10/764 ,  G06V10/94

CPC classification number: G06V10/764 ,  G06V10/945 ,  G06V20/69 ,  G06V20/693 ,  G06V20/695 ,  G06V20/698

Abstract: A cell image analysis method may include: obtaining, for each of cell images, a value of a feature parameter to be used in determination of a type of a cell, by analyzing the cell images; and displaying the value of the feature parameter in association with the each of the cell images.

公开(公告)号：US11798163B2

公开(公告)日：2023-10-24

申请号：US17870332

申请日：2022-07-21

Applicant: PharmaNest LLC

Inventor： Mathieu Maurice Petitjean

IPC: G06V10/80 ,  G06T7/00 ,  G06V20/69

CPC classification number: G06T7/0012 ,  G06V10/806 ,  G06V10/809 ,  G06V20/695 ,  G06V20/698 ,  G06T2207/10056 ,  G06T2207/30024

Abstract: Systems and methods are provided for computer aided phenotyping of fibrosis-related conditions. A digital image indicates presence of collagens in a biological tissue sample. The image is processed to quantify parameters, each parameter describing a feature of the collagens that is expected to be different for different phenotypes of fibrosis. At least some features are tissue level features that describe macroscopic characteristics of the collagens, morphometric level features that describe morphometric characteristics of the collagens, and texture level features that describe an organization of the collagens. At least some of the plurality of parameters are statistics associated with histograms corresponding to distributions of the associated parameters across at least some of the digital image. At least some of the plurality of parameters are combined to obtain one or more composite scores that quantify a phenotype of fibrosis for the biological tissue sample.

公开(公告)号：US20230296595A1

公开(公告)日：2023-09-21

申请号：US18089556

申请日：2022-12-27

Applicant: Essenlix Corporation

Inventor： Stephen Y. CHOU ,  Wei DING ,  Ji LI ,  Yufan ZHANG

IPC: G01N33/543 ,  C12Q1/6804 ,  C12Q1/6869 ,  G06V20/69

CPC classification number: G01N33/54313 ,  C12Q1/6804 ,  C12Q1/6869 ,  G01N33/54386 ,  G06V20/693 ,  G06V20/698

Abstract: Among other things, the present disclosure is related to devices and methods of performing biological and chemical assays, such as but not limited to immunoassays and nucleic assay acid, particularly a homogeneous assay that does not use a wash step and that is fast (e.g., 60 seconds from dropping a sample to displaying results). The present disclosure is related to both competitive and non-competitive homogeneous assays.

公开(公告)号：US20230281825A1

公开(公告)日：2023-09-07

申请号：US18170076

申请日：2023-02-16

Applicant: ALLEN INSTITUTE

Inventor： Gregory JOHNSON ,  Chawin OUNKOMOL ,  Forrest COLLMAN ,  Sharmishtaa SESHAMANI

IPC: G06T7/11 ,  G06T7/187 ,  G06T7/174 ,  G06N20/20 ,  G02B21/00 ,  G06N3/08 ,  G06N3/045 ,  G06V10/25 ,  G06V10/764 ,  G06V10/50 ,  G06V20/69

CPC classification number: G06T7/11 ,  G06T7/187 ,  G06T7/174 ,  G06N20/20 ,  G02B21/008 ,  G06N3/08 ,  G06N3/045 ,  G06V10/25 ,  G06V10/764 ,  G06V10/50 ,  G06V20/695 ,  G06V20/698 ,  G06T2207/10061 ,  G06T2207/10064 ,  G06T2207/30024

Abstract: A computing device, method, system, and instructions in a non-transitory computer-readable medium for performing image analysis on 3D microscopy images to predict localization and/or labeling of various structures or objects of interest, by predicting the location in such images at which a dye or other marker associated with such structures would appear. The computing device, method, and system receives sets of 3D images that include unlabeled images, such as transmitted light images or electron microscope images, and labeled images, such as images captured with fluorescence tagging. The computing device trains a statistical model to associate structures in the labeled images with the same structures in the unlabeled light images. The processor further applies the statistical model to a new unlabeled image to generate a predictive labeled image that predicts the location of a structure of interest in the new image.

公开(公告)号：US11748881B2

公开(公告)日：2023-09-05

申请号：US17847326

申请日：2022-06-23

Applicant: Agilent Technologies, Inc.

Inventor： Elad Arbel ,  Itay Remer ,  Amir Ben-Dor

IPC: G06T7/00 ,  G06T7/10 ,  G06T7/187 ,  G06T7/11 ,  G06T7/174 ,  G06N20/00 ,  G06F3/0482 ,  G06F3/0486 ,  G06N3/08 ,  G06F18/2431 ,  G06V10/764 ,  G06V10/774 ,  G06V10/80 ,  G06V10/82 ,  G06V10/26 ,  G06V10/28 ,  G06V20/69 ,  G06V10/94 ,  G06V10/24

CPC classification number: G06T7/0012 ,  G06F3/0482 ,  G06F3/0486 ,  G06F18/2431 ,  G06N3/08 ,  G06N20/00 ,  G06T7/0014 ,  G06T7/10 ,  G06T7/11 ,  G06T7/174 ,  G06T7/187 ,  G06V10/267 ,  G06V10/28 ,  G06V10/764 ,  G06V10/7753 ,  G06V10/809 ,  G06V10/82 ,  G06V10/945 ,  G06V20/695 ,  G06V20/698 ,  G06T2207/10056 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/20104 ,  G06T2207/30024 ,  G06T2207/30096 ,  G06V10/247

Abstract: Novel tools and techniques are provided for implementing digital microscopy imaging using deep learning-based segmentation and/or implementing instance segmentation based on partial annotations. In various embodiments, a computing system might receive first and second images, the first image comprising a field of view of a biological sample, while the second image comprises labeling of objects of interest in the biological sample. The computing system might encode, using an encoder, the second image to generate third and fourth encoded images (different from each other) that comprise proximity scores or maps. The computing system might train an AI system to predict objects of interest based at least in part on the third and fourth encoded images. The computing system might generate (using regression) and decode (using a decoder) two or more images based on a new image of a biological sample to predict labeling of objects in the new image.

公开(公告)号：US20230273122A1

公开(公告)日：2023-08-31

申请号：US18312241

申请日：2023-05-04

Applicant: VIAVI Solutions Inc.

Inventor： ChangMeng HSIUNG ,  Christopher G. PEDERSON ,  Marc K. VON GUNTEN ,  Lan SUN

IPC: G06V20/69 ,  G01J3/10 ,  G01N21/25 ,  G01N21/35 ,  G01N21/359 ,  G06F18/2433 ,  G06N20/00 ,  G16C20/20 ,  G16C20/70 ,  G06F18/2411

CPC classification number: G06V20/698 ,  G01J3/108 ,  G01N21/253 ,  G01N21/35 ,  G01N21/359 ,  G06F18/2433 ,  G06N20/00 ,  G16C20/20 ,  G16C20/70 ,  G06F18/2411 ,  G01N2201/129

Abstract: A device may receive information identifying results of a set of spectroscopic measurements of a training set of known samples and a validation set of known samples. The device may generate a classification model based on the information identifying the results of the set of spectroscopic measurements, wherein the classification model includes at least one class relating to a material of interest for a spectroscopic determination, and wherein the classification model includes a no-match class relating to at least one of at least one material that is not of interest or a baseline spectroscopic measurement. The device may receive information identifying a particular result of a particular spectroscopic measurement of an unknown sample. The device may determine whether the unknown sample is included in the no-match class using the classification model. The device may provide output indicating whether the unknown sample is included in the no-match class.