公开(公告)号：US12254694B2

公开(公告)日：2025-03-18

申请号：US16630286

申请日：2018-06-25

Applicant: Siemens Healthcare Diagnostics Inc.

Inventor： Yao-Jen Chang ,  Stefan Kluckner ,  Benjamin S. Pollack ,  Terrence Chen

IPC: G01N21/25 ,  G01N35/00 ,  G01N35/04 ,  G06V20/52

Abstract: Embodiments provide a method of using image-based tube top circle detection based on multiple candidate selection to localize the tube top circle region in input images. According to embodiments provided herein, the multi-candidate selection enhances the robustness of tube circle detection by making use of multiple views of the same tube to improve the robustness of tube top circle detection. With multiple candidates extracted from images under different viewpoints of the same tube, the multi-candidate selection algorithm selects an optimal combination among the candidates and provides more precise measurement of tube characteristics. This information is invaluable in an IVD environment in which a sample handler is processing the tubes and moving the tubes to analyzers for testing and analysis.

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

IPC: G01N35/00 ,  G01N35/04

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.

公开(公告)号：US11927736B2

公开(公告)日：2024-03-12

申请号：US17251744

申请日：2019-06-10

Applicant: Siemens Healthcare Diagnostics Inc.

Inventor： Kai Ma ,  Yao-Jen Chang ,  Terrence Chen ,  Benjamin S. Pollack

IPC: G02B21/34 ,  G01N35/00 ,  G06F18/214 ,  G06F18/241 ,  G06F18/2431 ,  G06T7/00 ,  G06V10/10 ,  G06V10/25 ,  G06V10/764 ,  G06V10/82

CPC classification number: G02B21/34 ,  G01N35/00732 ,  G06F18/241 ,  G06F18/2431 ,  G06T7/0012 ,  G06V10/25 ,  G06V10/764 ,  G06V10/82 ,  G01N2035/00752 ,  G06F18/214 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30024 ,  G06V10/16

Abstract: A method of characterizing a serum or plasma portion of a specimen in a specimen container provides a fine-grained HILN index (hemolysis, icterus, lipemia, normal) of the serum or plasma portion of the specimen, wherein the H, I, and L classes may each have five to seven sub-classes. The HILN index may also have one un-centrifuged class. Pixel data of an input image of the specimen container may be processed by a deep semantic segmentation network having, in some embodiments, more than 100 layers. A small front-end container segmentation network may be used to determine a container type and boundary, which may additionally be input to the deep semantic segmentation network. A discriminative network may be used to train the deep semantic segmentation network to generate a homogeneously structured output. Quality check modules and testing apparatus configured to carry out the method are also described, as are other aspects.

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

IPC: G06T7/00 ,  H04N17/00 ,  H04N5/265

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.

公开(公告)号：US11650197B2

公开(公告)日：2023-05-16

申请号：US16072394

申请日：2017-01-24

Applicant: Siemens Healthcare Diagnostics Inc.

Inventor： Stefan Kluckner ,  Yao-Jen Chang ,  Terrence Chen ,  Benjamin S. Pollack

IPC: G01N21/31 ,  G06T7/00 ,  G06T7/62 ,  G01F23/00 ,  G01N33/49 ,  G01N21/90 ,  G01N35/00 ,  G01N35/04 ,  G06K9/62 ,  G06N7/08 ,  G01N35/02 ,  G01N21/17

CPC classification number: G01N21/31 ,  G01F23/00 ,  G01N21/90 ,  G01N33/49 ,  G01N33/491 ,  G01N35/00732 ,  G01N35/04 ,  G06K9/628 ,  G06K9/6269 ,  G06N7/08 ,  G06T7/0012 ,  G06T7/62 ,  G01N35/0099 ,  G01N35/02 ,  G01N2021/1772 ,  G01N2021/1776 ,  G01N2035/00495 ,  G01N2035/00752 ,  G01N2035/0406 ,  G01N2035/0439 ,  G06T2207/10016 ,  G06T2207/10024 ,  G06T2207/10144 ,  G06T2207/10152 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30024

Abstract: A model-based method for quantifying a specimen. The method includes providing a specimen, capturing images of the specimen while illuminated by multiple spectra at different nominal wavelengths, and exposures, and classifying the specimen into various class types comprising one or more of serum or plasma portion, settled blood portion, gel separator (if used), air, tube, label, or cap; and quantifying of the specimen. Quantifying includes determining one or more of: a location of a liquid-air interface, a location of a serum-blood interface, a location of a serum-gel interface, a location of a blood-gel interface, a volume and/or a depth of the serum or plasma portion, or a volume and/or a depth of the settled blood portion. Quality check modules and specimen testing apparatus adapted to carry out the method are described, as are other aspects.

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.

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.

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

IPC: G06T7/00 ,  G06K9/62

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.

公开(公告)号：US11035870B2

公开(公告)日：2021-06-15

申请号：US16320198

申请日：2017-07-07

Applicant: Siemens Healthcare Diagnostics Inc.

Inventor： Stefan Kluckner ,  Yao-Jen Chang ,  Terrence Chen ,  Benjamin S. Pollack

IPC: G06K9/00 ,  G01N35/02 ,  G01N21/25 ,  G01N21/55 ,  G01N21/63 ,  G06K9/62 ,  G06K9/20 ,  G06T7/586 ,  G01N35/00 ,  G01N35/04 ,  B01L3/00

Abstract: A model-based method of determining characteristics of a specimen container cap to identify the container cap. The method includes providing a specimen container including a container cap; capturing backlit images of the container cap taken at different exposures lengths and using a plurality of different nominal wavelengths; selecting optimally-exposed pixels from the images at different exposure lengths at each nominal wavelength to generate optimally-exposed image data for each nominal wavelength; classifying the optimally-exposed pixels as at least being one of a tube, a label or a cap; and identifying a shape of the container cap based upon the optimally-exposed pixels classified as being the cap and the image data for each nominal wavelength. Quality check modules and specimen testing apparatus adapted to carry out the method are described, as are numerous other aspects.

公开(公告)号：US11009467B2

公开(公告)日：2021-05-18

申请号：US15551562

申请日：2016-02-16

Applicant: Siemens Healthcare Diagnostics Inc.

Inventor： JinHyeong Park ,  Yao-Jen Chang ,  Wen Wu ,  Terrence Chen ,  Benjamin Pollack

IPC: G01N21/94 ,  G06T7/00 ,  G01J3/46 ,  G01J3/50 ,  G01N21/25 ,  G01N21/03 ,  G01N21/27 ,  G01N35/00 ,  G06K9/00 ,  G06K9/62 ,  G01N21/59

Abstract: A model-based method of inspecting a specimen for presence of one or more interferent, such as Hemolysis, Icterus, and/or Lipemia (HI L) is provided. The method includes generating a pixelated image of the specimen in a first color space, determining color components (e.g., an a-value and a b-value) for pixels in the pixelated image, classifying of the pixels as being either liquid or non-liquid, defining one or more liquid regions based upon the pixels classified as liquid, and determining a presence of one or more interferent within the one or more liquid regions. The liquid classification is based upon a liquid classification model. Pixel classification may be based on a trained multiclass classifier. Interference level for the one or more interferent may be provided. Testing apparatus adapted to carry out the method are described, as are other aspects.