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公开(公告)号：US20240320962A1
公开(公告)日：2024-09-26
申请号：US18576256
申请日：2022-07-06
Applicant: Siemens Healthcare Diagnostics Inc.
Inventor： Venkatesh NarasimhaMurthy , Vivek Singh , Yao-Jen Chang , Benjamin S. Pollack , Ankur Kapoor , Rayal Raj Prasad Nalam Venkat
IPC: G06V10/776 , G06V10/778 , G06V10/94 , G06V20/69 , G16H50/20
CPC classification number: G06V10/776 , G06V10/778 , G06V10/945 , G06V20/698 , G16H50/20
Abstract: Methods of characterizing a sample container or a biological sample in an automated diagnostic analysis system using an artificial intelligence (AI) algorithm include retraining of the AI algorithm in response to characterization confidence levels determined to be unsatisfactory. The AI algorithm is retrained with data (including image data and/or non-image data) having features prevalent at the site where the automated diagnostic analysis system is operated, which were not sufficiently or at all included in training data used to initially train the AI algorithm. Systems for characterizing a sample container or a biological sample using an AI algorithm are also provided, as are other aspects.
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2.发明公开公开(公告)号：US20240133908A1
公开(公告)日：2024-04-25
申请号：US18546160
申请日：2022-02-10
Applicant: Siemens Healthcare Diagnostics Inc.
Inventor： Rayal Raj Prasad Nalam Venkat , Yao-Jen Chang , Benjamin S. Pollack , Ankur Kapoor
CPC classification number: G01N35/00732 , G01N35/04 , G06T7/0012 , G06T7/60 , G06T7/97 , G01N2035/0406
Abstract: A method of determining a 3D center location of a specimen container on a track. The method includes providing a calibration object on the track; providing an initially calibrated image capture device adjacent to the track; moving the calibration object to at least two different longitudinal positions along the track; capturing a first image with the calibration object located at the first longitudinal position; capturing a second image with the calibration object located at the second longitudinal position; and determining a three-dimensional path trajectory of a center location along the track based at least upon the first image and the second image. The method can be used to determine a 3D center location of a specimen container imaged anywhere within a viewing area. Characterization apparatus and specimen testing apparatus adapted to carry out the methods are described, as are other aspects.
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公开(公告)号：US20230091197A1
公开(公告)日：2023-03-23
申请号：US17905101
申请日：2021-02-25
Applicant: Siemens Healthcare Diagnostics Inc.
Inventor： Mark Edwards , Vivek Singh , Bogdan Georgescu , Ankur Kapoor
IPC: G06F11/07 , G06N3/08 , G06N3/0455
Abstract: The disclosure provides a computer-implemented method for detecting a failure of a device, wherein the device is connected to a sensor, the method comprising: receiving, by a machine learning model, a trace signal from the sensor indicating a status of the device; encoding, by the machine learning model, the trace signal into a plurality of vector representations; and determining, by the machine learning model, whether the trace signal is valid or invalid based on the plurality of vector representations.
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公开(公告)号：US20220390478A1
公开(公告)日：2022-12-08
申请号：US17755469
申请日：2020-10-22
Applicant: Siemens Healthcare Diagnostics Inc.
Inventor： Yao-Jen Chang , Patrick Wissmann , Ludwig Listl , Benjamin S. Pollack , Ramkrishna Jangale , Rayal Raj Prasad Nalam Venkat , Venkatesh NarasimhaMurthy , Ankur Kapoor
IPC: G01N35/00
Abstract: A method of calibrating an imaging device adapted to characterize a feature of a sample container, such as a cap color or cap type. The method includes providing a calibration tube including an imaging surface at an imaging location of a first imaging apparatus; illuminating the imaging surface with light emitted from multiple front light sources; adjusting a drive current to each of the multiple front light sources to establish a substantially uniform intensity of the imaging surface; recording drive current values for the multiple front light sources; replacing the calibration tube with a calibration tool having a calibration surface of a known reflectance; and measuring target intensity values of the calibration tool at the respective drive current values. Calibration tools, imaging apparatus, quality check modules, and health check methods are provided, as are other aspects.
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5.发明公开公开(公告)号：US20240159786A1
公开(公告)日：2024-05-16
申请号：US17755461
申请日：2020-10-22
Applicant: Siemens Healthcare Diagnostics Inc.
Inventor： Yao-Jen Chang , Patrick Wissmann , Ludwig Listl , Benjamin S. Pollack , Ramkrishna Jangale , Rayal Raj Prasad Nalam Venkat , Venkatesh NarasimhaMurthy , Ankur Kapoor
CPC classification number: G01N35/00693 , G01N35/00663 , G01N2035/0406
Abstract: A calibration method is provided including identifying the imaging area on each light panel with respect to each imaging device. A center position of the imaging area of each light panel for each imaging device is determined. An optimal optical center of the imaging apparatus using the center position of the imaging area of each imaging device is determined. A tube calibration tool is installed in a carrier on a track, and the carrier is moved on the track so that a center of the tube calibration tool is located at a closest location to the optimal optical center of the imaging apparatus. The center of the tube calibration tool is used to determine a center of a region of interest (ROI) for backlight calibration. Methods for heath checking the calibration and apparatus used to carry out the calibration are provided as well as other aspects.
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Patent Agency Ranking
公开(公告)号：US20240037723A1
公开(公告)日：2024-02-01
申请号：US18264237
申请日：2022-02-02
Applicant: Siemens Healthcare Diagnostics Inc.
Inventor： Rayal Raj Prasad Nalam Venkat , Yao-Jen Chang , Benjamin S. Pollack , Ankur Kapoor
CPC classification number: G06T7/0002 , H04N17/002 , H04N5/265 , G06T2207/20212 , H04N23/90
Abstract: Methods of identifying a defect in a machine vision system. Embodiments of the method include providing a first imaging device having a first field of view; moving a reflective tool through the first field of view; capturing a plurality of images of the reflective tool at different locations in the first field of view using the first imaging device; and analyzing at least one of the plurality of images to identify one or more defects in the machine vision system. Systems and apparatus configured to carry out the methods are provided, as are other aspects.
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公开(公告)号：US20220398846A1
公开(公告)日：2022-12-15
申请号：US17755473
申请日：2020-10-22
Applicant: Siemens Healthcare Diagnostics Inc.
Inventor： Rayal Raj Prasad Nalam Venkat , Benjamin S. Pollack , Yao-Jen Chang , Venkatesh NarasimhaMurthy , Vivek Singh , Ankur Kapoor
IPC: G06V20/50 , G01N35/00 , G06V10/14 , G06T7/90 , G06V10/764
Abstract: A method of identifying a tube type. The method includes capturing one or more pixelated images of a cap affixed to a tube; identifying a color of one or more pixels of the pixilated image of the cap; identifying one or more gradients of a dimension of the cap; and identifying the tube type based at least on: the color of the one or more pixels, and the one or more gradients of a dimension of the cap. Apparatus adapted to carry out the method are disclosed as are other aspects.
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公开(公告)号：US20220383618A1
公开(公告)日：2022-12-01
申请号：US17755477
申请日：2020-10-22
Applicant: Siemens Healthcare Diagnostics Inc.
Inventor： Rayal Raj Prasad Nalam Venkat , Benjamin S. Pollack , Yao-Jen Chang , Venkatesh NarasimhaMurthy , Vivek Singh , Ankur Kapoor
IPC: G06V10/764 , G06V10/774 , G06V10/82 , G06V20/60 , G06V10/56
Abstract: A method of training a model of a diagnostic apparatus includes providing one or more first tube assemblies of a first type and one or more second tube assemblies of a second type in a diagnostic apparatus; capturing one or more first images of at least a portion of each of the one or more first tube assemblies and the second tube assemblies using the imaging device. Training the model includes identifying tube assemblies of the first type and tube assemblies of the second type based on the one or more first images and the one or more second images. Tubes assemblies of the first type are grouped into a first group and tube assemblies of the second type are grouped into a second group. Other methods and apparatus are disclosed.
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公开(公告)号：US20210334972A1
公开(公告)日：2021-10-28
申请号：US17278285
申请日：2019-09-19
Applicant: Siemens Healthcare Diagnostics Inc.
Inventor： Venkatesh NarasimhaMurthy , Vivek Singh , Yao-Jen Chang , Benjamin S. Pollack , Ankur Kapoor
Abstract: A method of characterizing a serum or plasma portion of a specimen in a specimen container provides an HILN (hemolysis, icterus, lipemia, normal) determination. Pixel data of an input image of the specimen container is processed by a classification network to identify whether the specimen contains plasma or serum. Specimen Pixel data representing a plasma sample are forwarded to a segmentation/classification/regression network trained with plasma samples for HILN determination. Pixel data representing a serum sample are forwarded to a transformation network, wherein the serum sample pixel data is transformed into pixel data that matches pixel data of a corresponding previously-collected plasma sample by changing sample color, contrast, intensity, and/or brightness. The transformed serum sample pixel data are forwarded to the segmentation/classification/regression network for HILN determination. Quality check modules and testing apparatus configured to carry out the method are also described, as are other aspects.
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公开(公告)号：US20240310395A1
公开(公告)日：2024-09-19
申请号：US18546959
申请日：2022-02-17
Applicant: SIEMENS HEALTHCARE DIAGNOSTICS INC.
Inventor： Yao-Jen Chang , Rayal Raj Prasad Nalam Venkat , Benjamin S. Pollack , Vivek Singh , Venkatesh NarasimhaMurthy , Ankur Kapoor
CPC classification number: G01N35/00712 , G01N35/1016 , G01N2035/1025
Abstract: Methods of operating a diagnostic laboratory system include providing a module configured to perform a function on an item in the diagnostic laboratory system; providing a plurality of sensors, each of the plurality of sensors configured to monitor the function or the item and generate sensor data in response to the monitoring; checking an operational status of a first sensor of the plurality of sensors; receiving sensor data from at least one of the plurality of sensors; and scaling sensor data from the first sensor in response to the operational status and the sensor data to generate revised sensor data. Systems including a middleware server configured to carry out the methods are provided as are other aspects.
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