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公开(公告)号：US20250127479A1
公开(公告)日：2025-04-24
申请号：US18572466
申请日：2022-06-22
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： Soumabha Bhowmick , Karthik Krishnan , Karthik Raj Katipally , Giridhar Narasapura Rajagopalaiah , Celine Firtion , Subhendu Seth , Pallavi Vajinepalli , David Nigel Roundhill , Matthew Rielly
Abstract: A mechanism for automatically generating and ranking M-mode lines for generating or defining M-mode data usable to assess fetal heart activity, e.g. determine a fetal heart rate. A region of interest, containing a fetal heart, in a sequence of ultrasound images is identified. The region of interest is used to define the position of each of a plurality of M-mode lines, e.g. anatomical M-mode lines. A quality measure of each M-mode line is determined based on M-mode data generated for each M-mode line, and the quality measures are then used to rank the M-mode lines.
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公开(公告)号：US20230419602A1
公开(公告)日：2023-12-28
申请号：US18034901
申请日：2021-11-01
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： Karthik Krishnan , Celine Firtion , Pallavi Vajinepalli , Saunak Chatterjee , Giridhar Narasapura Rajagopalaiah , Matthew Rielly
CPC classification number: G06T17/00 , G06T7/0012 , G06T7/20 , G06T7/30 , G06V10/25 , G06V2201/07 , G06V2201/03 , G06T2207/30048
Abstract: There is proposed a mechanism for generating and displaying a 3D representation of an anatomical structure of an individual. Image data of the anatomical structure is obtained and processed to obtain 2D images or image sequences corresponding to predetermined views of the anatomical structure. Anatomical landmarks are identified in the 2D images or image sequences and used to determine a 3D landmark model of the anatomical 5structure. The 3D landmark model is used to render and display a 3D representation of the anatomical structure.
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公开(公告)号：US12277718B2
公开(公告)日：2025-04-15
申请号：US17915183
申请日：2021-03-24
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： Karthik Krishnan , Celine Firtion , Subhendu Seth , Pallavi Vajinepalli , David Nigel Roundhill
Abstract: A computer-implemented method for visualization of an elongated anatomical structure (20), for example of a fetal spine using ultrasound is provided. The method comprising the steps of: receiving a plurality of 3D ultrasound image volumes, each image volume depicting at least a portion of an elongated anatomical structure (20); on each 3D ultrasound image volume, automatically or semi-automatically fitting a parametric curve (30) to the depicted portion of the elongated anatomical structure, the parametric curve being defined by curve parameters; reformatting each 3D ultrasound image volume by applying a transformation which straightens the parametric curve along at least one axis, so as to generate a plurality of reformatted image volumes and reformatted parametric curves (32, 34); registering the reformatted image volumes with one another by determining the joining point of their respective parametric curves; and fusing the reformatted image volumes with one another to yield a fused image depicting the whole elongated anatomical structure or a larger portion thereof than the 3D ultrasound image volumes.
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公开(公告)号：US20240099692A1
公开(公告)日：2024-03-28
申请号：US18038498
申请日：2021-11-17
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： Karthik Krishnan , Celine Firtion , Pallavi Vajinepalli , Giridhar Narasapura Rajagopalaiah , Saunak Chatterjee , Robert Gustav Trahms , Earl M. Canfield, II , Matthew Rielly , David Nigel Roundhill
CPC classification number: A61B8/4245 , A61B8/0883 , A61B8/483 , G06T7/75 , G06T17/00 , G06T2207/10132 , G06T2207/20081 , G06T2207/30048
Abstract: There is proposed a mechanism for determining whether or not an imaging probe, such as an ultrasound imaging probe, is at a desired orientation and/or position with respect to an anatomical structure. Image data of the imaging probe is processed to generate a 3D landmark model that contains anatomical landmarks of the anatomical structure. The 3D landmark model is then processed to determine whether or not the imaging probe is at the desired orientation and/or position.
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Patent Agency Ranking
公开(公告)号：US20230064623A1
公开(公告)日：2023-03-02
申请号：US17799958
申请日：2021-02-03
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： Karthik Krishnan , Karan Kumar , Celine Firtion , Saunak Chatterjee , Pallavi Vajinepalli , Robert Gustav Trahms , Earl M. Canfield , Matthew Rielly
IPC: A61B8/08
Abstract: The invention provides a method for deriving a biometric parameter of a fetal heart. The method includes acquiring a plurality of ultrasound images of a region of interest, wherein the region of interest comprises a fetal heart and comparing the plurality of ultrasound images to a predefined clinical view. A group of ultrasound images related to the predefined clinical view are selected based on the comparison, wherein the group of ultrasound images represents at least one cardiac cycle. An anatomical landmark of the fetal heart is detected within an ultrasound image of the group of ultrasound images and the anatomical landmark of the fetal heart is detected or tracked across the group of ultrasound images. A biometric parameter of the fetal heart is then determined based on the detected or tracked anatomical landmark from one or more ultrasound images of the group of ultrasound images.
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公开(公告)号：US12283052B2
公开(公告)日：2025-04-22
申请号：US17792013
申请日：2021-01-12
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： Soumabha Bhowmick , Subhendu Seth , Karthik Krishnan , Celine Firtion , Pallavi Vajinepalli
IPC: G06T7/10 , G06T7/00 , G06T7/11 , G06T7/70 , G06V10/25 , G06V10/26 , G06V10/764 , G06V10/774 , G06V10/82
Abstract: The invention relates to a computer-implemented method for automatically detecting anatomical structures (3) in a medical image (1) of a subject, the method comprising applying an object detector function (4) to the medical image, wherein the object detector function performs the steps of: (A) applying a first neural network (40) to the medical image, wherein the first neural network is trained to detect a first plurality of classes of larger-sized anatomical structures (3a), thereby generating as output the coordinates of at least one first bounding box (51) and the confidence score of it containing a larger-sized anatomical structure; (B) cropping (42) the medical image to the first bounding box, thereby generating a cropped image (11) containing the image content within the first bounding box (51); and (C) applying a second neural network (44) to the cropped medical image, wherein the second neural network is trained to detect at least one second class of smaller-sized anatomical structures (3b), thereby generating as output the coordinates of at least one second bounding box (54) and the confidence score of it containing a smaller-sized anatomical structure.
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公开(公告)号：US20240366187A1
公开(公告)日：2024-11-07
申请号：US18689171
申请日：2022-09-06
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： Nitesh Kaushal , Karthick Raja , Kothawala Aliarshad Aameer , Karthik Krishnan , Subhendu Seth , Pallavi Vajinepalli , Earl M. Canfield
Abstract: A mechanism for defining a set of preset parameter values for an ultrasound imaging system. Information about local machine-learning models, generated by a plurality of ultrasound imaging systems and updated responsive to operator feedback, is provided to an external server. The external server generates a global machine-learning model based on this information, which is then used to update the local machine-learning model on target ultrasound imaging systems.
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公开(公告)号：US20230124879A1
公开(公告)日：2023-04-20
申请号：US17915183
申请日：2021-03-24
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： Karthik Krishnan , Celine Firtion , Subhendu Seth , Pallavi Vajinepalli , David Nigel Roundhill
Abstract: A computer-implemented method for visualization of an elongated anatomical structure (20), for example of a fetal spine using ultrasound is provided. The method comprising the steps of: receiving a plurality of 3D ultrasound image volumes, each image volume depicting at least a portion of an elongated anatomical structure (20); on each 3D ultrasound image volume, automatically or semi-automatically fitting a parametric curve (30) to the depicted portion of the elongated anatomical structure, the parametric curve being defined by curve parameters; reformatting each 3D ultrasound image volume by applying a transformation which straightens the parametric curve along at least one axis, so as to generate a plurality of reformatted image volumes and reformatted parametric curves (32, 34); registering the reformatted image volumes with one another by determining the joining point of their respective parametric curves; and fusing the reformatted image volumes with one another to yield a fused image depicting the whole elongated anatomical structure or a larger portion thereof than the 3D ultrasound image volumes.
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公开(公告)号：US20230038364A1
公开(公告)日：2023-02-09
申请号：US17792013
申请日：2021-01-12
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： Soumabha Bhowmick , Subhendu Seth , Karthik Krishnan , Celine Firtion , Pallavi Vajinepalli
IPC: A61B8/00 , G06V10/22 , G06V10/764 , G06T7/00 , G06T7/11 , G06V10/82 , G06T7/70 , G06V10/774 , A61B8/08
Abstract: The invention relates to a computer-implemented method for automatically detecting anatomical structures (3) in a medical image (1) of a subject, the method comprising applying an object detector function (4) to the medical image, wherein the object detector function performs the steps of: (A) applying a first neural network (40) to the medical image, wherein the first neural network is trained to detect a first plurality of classes of larger-sized anatomical structures (3a), thereby generating as output the coordinates of at least one first bounding box (51) and the confidence score of it containing a larger-sized anatomical structure; (B) cropping (42) the medical image to the first bounding box, thereby generating a cropped image (11) containing the image content within the first bounding box (51); and (C) applying a second neural network (44) to the cropped medical image, wherein the second neural network is trained to detect at least one second class of smaller-sized anatomical structures (3b), thereby generating as output the coordinates of at least one second bounding box (54) and the confidence score of it containing a smaller-sized anatomical structure.
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