公开(公告)号：US20170372475A1

公开(公告)日：2017-12-28

申请号：US15680584

申请日：2017-08-18

Applicant: Siemens Healthcare GmbH

Inventor： Mehmet A. Gulsun ,  Yefeng Zheng ,  Puneet Sharma ,  Bogdan Georgescu ,  Dorin Comaniciu

IPC: G06T7/00 ,  G06T7/60 ,  G06K9/46 ,  G06N3/02

CPC classification number: G06T7/0012 ,  G06K9/00147 ,  G06K9/4628 ,  G06K9/6271 ,  G06K9/6857 ,  G06N3/02 ,  G06T7/60 ,  G06T2200/04 ,  G06T2207/10081 ,  G06T2207/20084 ,  G06T2207/30101 ,  G06T2207/30172

Abstract: A method and apparatus for vascular disease detection and characterization using a recurrent neural network (RNN) is disclosed. A plurality of 2D cross-section image patches are extracted from a 3D computed tomography angiography (CTA) image, each extracted at a respective sampling point along a vessel centerline of a vessel of interest in the 3D CTA image. Vascular abnormalities in the vessel of interest are detected and characterized by classifying each of the sampling points along the vessel centerline based on the plurality of 2D cross-section image patches using a trained RNN.

公开(公告)号：US09881372B2

公开(公告)日：2018-01-30

申请号：US15680584

申请日：2017-08-18

Applicant: Siemens Healthcare GmbH

Inventor： Mehmet A. Gulsun ,  Yefeng Zheng ,  Puneet Sharma ,  Bogdan Georgescu ,  Dorin Comaniciu

IPC: G06K9/00 ,  G06T7/00 ,  G06N3/02 ,  G06T7/60 ,  G06K9/46

CPC classification number: G06T7/0012 ,  G06K9/00147 ,  G06K9/4628 ,  G06K9/6271 ,  G06K9/6857 ,  G06N3/02 ,  G06T7/60 ,  G06T2200/04 ,  G06T2207/10081 ,  G06T2207/20084 ,  G06T2207/30101 ,  G06T2207/30172

Abstract: A method and apparatus for vascular disease detection and characterization using a recurrent neural network (RNN) is disclosed. A plurality of 2D cross-section image patches are extracted from a 3D computed tomography angiography (CTA) image, each extracted at a respective sampling point along a vessel centerline of a vessel of interest in the 3D CTA image. Vascular abnormalities in the vessel of interest are detected and characterized by classifying each of the sampling points along the vessel centerline based on the plurality of 2D cross-section image patches using a trained RNN.

公开(公告)号：US09767557B1

公开(公告)日：2017-09-19

申请号：US15429806

申请日：2017-02-10

Applicant: Siemens Healthcare GmbH

Inventor： Mehmet A. Gulsun ,  Yefeng Zheng ,  Puneet Sharma ,  Bogdan Georgescu ,  Dorin Comaniciu

IPC: G06K9/00 ,  G06T7/00 ,  G06K9/46 ,  G06T7/60 ,  G06N3/02

CPC classification number: G06T7/0012 ,  G06K9/00147 ,  G06K9/4628 ,  G06K9/6271 ,  G06K9/6857 ,  G06N3/02 ,  G06T7/60 ,  G06T2200/04 ,  G06T2207/10081 ,  G06T2207/20084 ,  G06T2207/30101 ,  G06T2207/30172

Abstract: A method and apparatus for vascular disease detection and characterization using a recurrent neural network (RNN) is disclosed. A plurality of 2D cross-section image patches are extracted from a 3D computed tomography angiography (CTA) image, each extracted at a respective sampling point along a vessel centerline of a vessel of interest in the 3D CTA image. Vascular abnormalities in the vessel of interest are detected and characterized by classifying each of the sampling points along the vessel centerline based on the plurality of 2D cross-section image patches using a trained RNN.