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公开(公告)号:US20250017825A1
公开(公告)日:2025-01-16
申请号:US18577029
申请日:2022-06-23
Applicant: AMGEN INC.
Inventor: Todd Neslund , Stephen Karl Shutt , Eunah Choi , Alberto David Herrera , Jordan Ray Fine , Thomas Clark Pearson
Abstract: A system for dispensing, inspecting, and/or processing drug includes a tray adapted to be operably coupled with a workstation, a handle member operably coupled with the tray, and a funnel region operably coupled with the tray. The tray has a body defining a recessed region and a sidewall positioned adjacent to the recessed region. The handle member is positioned at or near a first corner of the tray. The funnel region is positioned at or near a second corner of the tray. The first corner is opposite the second corner.
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公开(公告)号:US20250139756A1
公开(公告)日:2025-05-01
申请号:US18692360
申请日:2022-09-28
Applicant: AMGEN INC.
Inventor: Jordan Ray Fine , Thomas Clark Pearson , Graham F. Milne
Abstract: Automatic prefilled syringe inspection systems, apparatus and methods are provided. The automatic syringe inspection systems, apparatus and methods may determine a plunger depth within a syringe that has been pre-filled with a medication. The plunger depth may be based on digital image data that is representative of a silhouette of at least a portion of a tubular vessel and at least a portion of a plunger within the tubular vessel.
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公开(公告)号:US20240095983A1
公开(公告)日:2024-03-21
申请号:US18039898
申请日:2021-12-01
Applicant: AMGEN INC.
Inventor: Al Patrick Goodwin , Joseph Peter Bernacki , Graham F. Milne , Thomas Clark Pearson , Aman Mahendra Jain , Jordan Ray Fine , Kenneth E. Hampshire , Aik Jun Tan , Osvaldo Perez Varela , Nishant Mukesh Gadhvi
Abstract: Various techniques facilitate the development of an image library that can be used to train and/or validate an automated visual inspection (AVI) model, such an AVI neural network for image classification. In one aspect, an arithmetic transposition algorithm is used to generate synthetic images from original images by transposing features (e.g., defects) onto the original images, with pixel-level realism. In other aspects, digital inpainting techniques are used to generate realistic synthetic images from original images. Deep learning-based inpainting techniques may be used to add, remove, and/or modify defects or other depicted features. In still other aspects, quality control techniques are used to assess the suitability of image libraries for training and/or validation of AVI models, and/or to assess whether individual images are suitable for inclusion in such libraries.
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公开(公告)号:US20230196096A1
公开(公告)日:2023-06-22
申请号:US17923347
申请日:2021-04-30
Applicant: AMGEN INC.
Inventor: Graham F. Milne , Thomas C. Pearson , Kenneth E. Hampshire , Joseph Peter Bernacki , Mark Quinlan , Jordan Ray Fine
CPC classification number: G06N3/08 , G06F9/5027
Abstract: Techniques that facilitate the development and/or modification of an automated visual inspection (AVI) system that implements deep learning are described herein. Some aspects facilitate the generation of a large and diverse training image library, such as by digitally modifying images of real-world containers, and/or generating synthetic container images using a deep generative model. Other aspects decrease the use of processing resources for training, and/or making inferences with, neural networks in an AVI system, such as by automatically reducing the pixel sizes of training images (e.g., by down-sampling and/or selectively cropping container images). Still other aspects facilitate the testing or qualification of an AVI neural network by automatically analyzing a heatmap or bounding box generated by the neural network. Various other techniques are also described herein.
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公开(公告)号:US20220261977A1
公开(公告)日:2022-08-18
申请号:US17670745
申请日:2022-02-14
Applicant: AMGEN INC.
Inventor: Al Patrick Goodwin , Graham F. Milne , Thomas C. Pearson , Jordan Ray Fine
Abstract: An automated inspection system includes a sensor system that includes a sensor and is configured to generate a plurality of syringe scans by scanning each of a plurality of syringes. Each of the plurality of syringe scans is indicative of distance relative to the sensor. The automated inspection system also includes one or more processors configured to, for each of the plurality of syringes, analyze the respective syringe scan to determine (i) a first distance to a first portion (e.g., flange) of the syringe and (ii) a second distance to a second portion (e.g., plunger) of the syringe, and calculate a distance between the first and second portions based on the first distance and the second distance.
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