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.

公开(公告)号：US20230316530A1

公开(公告)日：2023-10-05

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

CPC classification number: G06T7/11 ,  G16H50/50 ,  G16H30/20 ,  G16H50/30 ,  G16H50/20 ,  G16H30/40 ,  A61B6/032 ,  A61B6/037 ,  A61B6/463 ,  A61B6/466 ,  A61B6/481 ,  A61B6/505 ,  A61B6/507 ,  A61B6/5205 ,  A61B6/5241 ,  A61B6/5247 ,  A61K51/0455 ,  G06V20/64 ,  G06V20/695 ,  G06V20/698 ,  G06V30/2504 ,  G06F18/214 ,  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：US11657508B2

公开(公告)日：2023-05-23

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

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：US11564621B2

公开(公告)日：2023-01-31

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: G06T7/00 ,  A61B5/00 ,  G16H50/30 ,  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.