公开(公告)号：US20200245960A1

公开(公告)日：2020-08-06

申请号：US16734599

申请日：2020-01-06

Applicant: EXINI Diagnostics AB

Inventor： Jens Filip Andreas Richter ,  Kerstin Elsa Maria Johnsson ,  Erik Konrad Gjertsson ,  Aseem Undvall Anand

IPC: A61B6/00 ,  A61B6/03 ,  A61K51/04 ,  G06K9/00 ,  G06K9/68 ,  G06K9/62 ,  G16H30/20 ,  G16H30/40 ,  G16H50/20 ,  G16H50/50 ,  G16H50/30

Abstract: Presented herein are systems and methods that provide for automated analysis of three-dimensional (3D) medical images of a subject in order to automatically identify specific 3D volumes within the 3D images that correspond to specific anatomical regions (e.g., organs and/or tissue). Notably, the image analysis approaches described herein are not limited to a single particular organ or portion of the body. Instead, they are robust and widely applicable, providing for consistent, efficient, and accurate detection of anatomical regions, including soft tissue organs, in the entire body. In certain embodiments, the accurate identification of one or more such volumes is used to automatically determine quantitative metrics that represent uptake of radiopharmaceuticals in particular organs and/or tissue regions. These uptake metrics can be used to assess disease state in a subject, determine a prognosis for a subject, and/or determine efficacy of a treatment modality.

公开(公告)号：US20250061580A1

公开(公告)日：2025-02-20

申请号：US18934154

申请日：2024-10-31

Applicant: EXINI Diagnostics AB

Inventor： Jens Filip Andreas Richter ,  Kerstin Elsa Maria Johnsson ,  Erik Konrad Gjertsson ,  Aseem Undvall Anand

IPC: G06T7/11 ,  A61B6/00 ,  A61B6/03 ,  A61B6/46 ,  A61B6/50 ,  A61K51/04 ,  G06F18/214 ,  G06V20/64 ,  G06V20/69 ,  G06V30/24 ,  G16H30/20 ,  G16H30/40 ,  G16H50/20 ,  G16H50/30 ,  G16H50/50

Abstract: Presented herein are systems and methods that provide for automated analysis of three-dimensional (3D) medical images of a subject in order to automatically identify specific 3D volumes within the 3D images that correspond to specific anatomical regions (e.g., organs and/or tissue). Notably, the image analysis approaches described herein are not limited to a single particular organ or portion of the body. Instead, they are robust and widely applicable, providing for consistent, efficient, and accurate detection of anatomical regions, including soft tissue organs, in the entire body. In certain embodiments, the accurate identification of one or more such volumes is used to automatically determine quantitative metrics that represent uptake of radiopharmaceuticals in particular organs and/or tissue regions. These uptake metrics can be used to assess disease state in a subject, determine a prognosis for a subject, and/or determine efficacy of a treatment modality.

公开(公告)号：US20240354940A1

公开(公告)日：2024-10-24

申请号：US18627691

申请日：2024-04-05

Applicant: Progenics Pharmaceuticals, Inc. ,  EXINI Diagnostics AB

Inventor： Karl Vilhelm Sjöstrand ,  Jens Filip Andreas Richter ,  Johan Martin Brynolfsson ,  Hannicka Maria Eleonora Sahlstedt

IPC: G06T7/00 ,  G06F3/04842 ,  G06V10/25 ,  G06V10/40 ,  G06V10/70

CPC classification number: G06T7/0012 ,  G06F3/04842 ,  G06V10/25 ,  G06V10/40 ,  G06V10/70 ,  G06T2207/30096

Abstract: Presented herein are systems, methods, and architectures related to the identification and presentation of hotspots (e.g., cancerous regions (e.g., metastatic) and/or regions suspected of being cancerous, e.g., 3D regions) in medical images. In certain embodiments, a slider and/or other graphical user interface widget is provided to allow intuitive, interactive adjustment by a user for inclusion and/or exclusion of hotspots (e.g., thresholds or other criteria for selection of a hotspot or other ROI are adjusted by the user by manipulation of the slider or other GUI widget).

公开(公告)号：US20240285246A1

公开(公告)日：2024-08-29

申请号：US18435386

申请日：2024-02-07

Applicant: Progenics Pharmaceuticals, Inc. ,  EXINI Diagnostics AB

Inventor： Karl Vilhelm Sjöstrand ,  Jens Filip Andreas Richter ,  Lars Edenbrandt

IPC: A61B6/46 ,  A61B6/00 ,  A61B6/03 ,  A61B6/50 ,  A61K51/04 ,  G06T7/00 ,  G06T7/11 ,  G06T7/73 ,  G16H15/00 ,  G16H30/20 ,  G16H30/40 ,  G16H50/20 ,  G16H50/30 ,  G16H50/70 ,  G16H70/60

CPC classification number: A61B6/469 ,  A61B6/037 ,  A61B6/465 ,  A61B6/505 ,  A61B6/5217 ,  A61B6/5258 ,  A61B6/563 ,  A61K51/0489 ,  G06T7/0012 ,  G06T7/11 ,  G06T7/73 ,  G16H15/00 ,  G16H30/20 ,  G16H30/40 ,  G16H50/20 ,  G16H50/30 ,  G16H50/70 ,  G16H70/60 ,  G06T2200/24 ,  G06T2207/30008 ,  G06T2207/30096

Abstract: Presented herein are systems and methods that provide for improved computer aided display and analysis of nuclear medicine images. In particular, in certain embodiments, the systems and methods described herein provide improvements to several image processing steps used for automated analysis of bone scan images for assessing cancer status of a patient. For example, improved approaches for image segmentation, hotspot detection, automated classification of hotspots as representing metastases, and computation of risk indices such as bone scan index (BSI) values are provided.

公开(公告)号：US20230148980A1

公开(公告)日：2023-05-18

申请号：US17989863

申请日：2022-11-18

Applicant: Progenics Pharmaceuticals, Inc. ,  EXINI Diagnostics AB

Inventor： Karl Vilhelm Sjöstrand ,  Jens Filip Andreas Richter ,  Lars Edenbrandt

IPC: A61B6/00 ,  G06T7/11 ,  G06T7/73 ,  G16H70/60 ,  G16H15/00 ,  G16H30/20 ,  G16H50/30 ,  G16H50/70 ,  G16H50/20 ,  G16H30/40 ,  A61B6/03 ,  A61K51/04 ,  G06T7/00

CPC classification number: A61B6/469 ,  G06T7/11 ,  G06T7/73 ,  G16H70/60 ,  G16H15/00 ,  G16H30/20 ,  G16H50/30 ,  G16H50/70 ,  G16H50/20 ,  G16H30/40 ,  A61B6/037 ,  A61B6/465 ,  A61B6/505 ,  A61B6/5217 ,  A61B6/5258 ,  A61B6/563 ,  A61K51/0489 ,  G06T7/0012 ,  G06T2200/24 ,  G06T2207/30008 ,  G06T2207/30096

Abstract: Presented herein are systems and methods that provide for improved computer aided display and analysis of nuclear medicine images. In particular, in certain embodiments, the systems and methods described herein provide improvements to several image processing steps used for automated analysis of bone scan images for assessing cancer status of a patient. For example, improved approaches for image segmentation, hotspot detection, automated classification of hotspots as representing metastases, and computation of risk indices such as bone scan index (BSI) values are provided.

公开(公告)号：US20230115732A1

公开(公告)日：2023-04-13

申请号：US17959357

申请日：2022-10-04

Applicant: EXINI Diagnostics AB

Inventor： Johan Martin Brynolfsson ,  Hannicka Maria Eleonora Sahlstedt ,  Jens Filip Andreas Richter

IPC: G06T7/00 ,  A61B6/03

Abstract: Presented herein are systems and methods that provide automated analysis of 3D images to classify representations of lesions identified therein. In particular, in certain embodiments, approaches described herein allow hotspots representing lesions to be classified based on their spatial relationship with (e.g., whether they are in proximity to, overlap with, or are located within) one or more pelvic lymph node regions in detailed fashion.

公开(公告)号：US20220398724A1

公开(公告)日：2022-12-15

申请号：US17762796

申请日：2020-08-21

Applicant: Progenics Pharmaceuticals, Inc. ,  EXINI Diagnostics AB

Inventor： Aseem Undvall Anand ,  Karl Vilhelm Sjöstrand ,  Jens Filip Andreas Richter

IPC: G06T7/00 ,  G06V10/25 ,  G16H50/20 ,  G16H30/40

Abstract: Presented herein are systems and methods that provide for automated analysis of medical images to determine a predicted disease status (e.g., prostate cancer status) and/or a value corresponding to predicted risk of the disease status for a subject. The approaches described herein leverage artificial intelligence (AI) to analyze intensities of voxels in a functional image, such as a PET image, and determine a risk and/or likelihood that a subject's disease, e.g., cancer, is aggressive. The approaches described herein can provide predictions of whether a subject that presents a localized disease has and/or will develop aggressive disease, such as metastatic cancer. These predictions are generated in a fully automated fashion and can be used alone, or in combination with other cancer diagnostic metrics (e.g., to corroborate predictions and assessments or highlight potential errors). As such, they represent a valuable tool in support of improved cancer diagnosis and treatment.

公开(公告)号：US20210093249A1

公开(公告)日：2021-04-01

申请号：US16734609

申请日：2020-01-06

Applicant: Progenics Pharmaceuticals, Inc. ,  EXINI Diagnostics AB

Inventor： Aseem Undvall Anand ,  Karl Vilhelm Sjöstrand ,  Jens Filip Andreas Richter

IPC: A61B5/00 ,  G16H50/30 ,  G06T7/00 ,  G06N3/08 ,  G06N20/00

Abstract: Presented herein are systems and methods that provide for automated analysis of medical images to determine a predicted disease status (e.g., prostate cancer status) and/or a value corresponding to predicted risk of the disease status for a subject. The approaches described herein leverage artificial intelligence (AI) to analyze intensities of voxels in a functional image, such as a PET image, and determine a risk and/or likelihood that a subject's disease, e.g., cancer, is aggressive. The approaches described herein can provide predictions of whether a subject that presents a localized disease has and/or will develop aggressive disease, such as metastatic cancer. These predictions are generated in a fully automated fashion and can be used alone, or in combination with other cancer diagnostic metrics (e.g., to corroborate predictions and assessments or highlight potential errors). As such, they represent a valuable tool in support of improved cancer diagnosis and treatment.

公开(公告)号：US11941817B2

公开(公告)日：2024-03-26

申请号：US18127991

申请日：2023-03-29

Applicant: EXINI Diagnostics AB

Inventor： Jens Filip Andreas Richter ,  Kerstin Elsa Maria Johnsson ,  Erik Konrad Gjertsson ,  Aseem Undvall Anand

IPC: G06T7/00 ,  A61B6/00 ,  A61B6/03 ,  A61K51/04 ,  G06F18/214 ,  G06T7/11 ,  G06V20/64 ,  G06V20/69 ,  G06V30/24 ,  G16H30/20 ,  G16H30/40 ,  G16H50/20 ,  G16H50/30 ,  G16H50/50

CPC classification number: G06T7/11 ,  A61B6/032 ,  A61B6/037 ,  A61B6/463 ,  A61B6/466 ,  A61B6/481 ,  A61B6/505 ,  A61B6/507 ,  A61B6/5205 ,  A61B6/5241 ,  A61B6/5247 ,  A61K51/0455 ,  G06F18/214 ,  G06V20/64 ,  G06V20/695 ,  G06V20/698 ,  G06V30/2504 ,  G16H30/20 ,  G16H30/40 ,  G16H50/20 ,  G16H50/30 ,  G16H50/50 ,  G06V2201/031 ,  G06V2201/033

Abstract: Presented herein are systems and methods that provide for automated analysis of three-dimensional (3D) medical images of a subject in order to automatically identify specific 3D volumes within the 3D images that correspond to specific anatomical regions (e.g., organs and/or tissue). Notably, the image analysis approaches described herein are not limited to a single particular organ or portion of the body. Instead, they are robust and widely applicable, providing for consistent, efficient, and accurate detection of anatomical regions, including soft tissue organs, in the entire body. In certain embodiments, the accurate identification of one or more such volumes is used to automatically determine quantitative metrics that represent uptake of radiopharmaceuticals in particular organs and/or tissue regions. These uptake metrics can be used to assess disease state in a subject, determine a prognosis for a subject, and/or determine efficacy of a treatment modality.

公开(公告)号：US11900597B2

公开(公告)日：2024-02-13

申请号：US17762796

申请日：2020-08-21

Applicant: Progenics Pharmaceuticals, Inc. ,  EXINI Diagnostics AB

Inventor： Aseem Undvall Anand ,  Karl Vilhelm Sjöstrand ,  Jens Filip Andreas Richter

IPC: G06V10/25 ,  G06T7/00 ,  G16H30/40 ,  G16H50/20

CPC classification number: G06T7/0012 ,  G06V10/25 ,  G16H30/40 ,  G16H50/20 ,  G06T2207/10081

Abstract: Presented herein are systems and methods that provide for automated analysis of medical images to determine a predicted disease status (e.g., prostate cancer status) and/or a value corresponding to predicted risk of the disease status for a subject. The approaches described herein leverage artificial intelligence (AI) to analyze intensities of voxels in a functional image, such as a PET image, and determine a risk and/or likelihood that a subject's disease, e.g., cancer, is aggressive. The approaches described herein can provide predictions of whether a subject that presents a localized disease has and/or will develop aggressive disease, such as metastatic cancer. These predictions are generated in a fully automated fashion and can be used alone, or in combination with other cancer diagnostic metrics (e.g., to corroborate predictions and assessments or highlight potential errors). As such, they represent a valuable tool in support of improved cancer diagnosis and treatment.