CN-115667967-B - Method for magnetic resonance scanner simulation

Abstract

A method for performing Magnetic Resonance (MR) scanner simulation in a Magnetic Resonance Imaging (MRI) simulator is described, the method comprising inputting data parameters into a network interface of the MRI simulator, wherein the input data parameters are at least a pulse sequence and an anatomical model, connecting the network interface and a cloud-based simulator engine of the MRI simulator to communicate the data parameters to the cloud-based simulator engine, the method comprising importing a pulse sequence calculation model, setting the input data, and slicing the acquired image in the network interface, the method further comprising recalculating the data parameters to provide one or more simulated MR signals, the recalculating performed in the cloud, and wherein the method further comprises reconstructing an MR image based on the one or more simulated MR signals, the reconstruction of the MR image performed in the cloud, and transmitting the MR image to the network interface.

Inventors

• Christos Santis
• Anthony Aletras

Assignees

• 科斯迈德有限公司

Dates

Publication Date

20260508

Application Date

20210609

Priority Date

20200610

Claims (8)

1. 1. A method for performing magnetic resonance MR scanner simulation in a magnetic resonance imaging MRI simulator, the method comprising: -inputting data parameters into a network interface of the MRI simulator, wherein the input data parameters are at least a pulse sequence and an anatomical model; -a cloud-based simulator engine connecting the network interface and the MRI simulator to communicate the data parameters to the cloud-based simulator engine, the method comprising: -importing a pulse sequence calculation model, thereby constructing a pulse sequence in the simulation; -setting the input data, and -Slice selection of the acquired image in the network interface; The method further comprises the steps of: Recalculating the data parameters to provide one or more simulated MR signals, the recalculating taking place in the cloud, And wherein the method further comprises: Reconstructing an MR image based on the one or more simulated MR signals, the reconstruction of the MR image taking place in the cloud, and Transmitting the MR image to the network interface, Wherein the phase encoding direction and the frequency encoding direction respectively represent an axis orthogonal to the slice selection direction, and Wherein the slice selection is a single slice selection in 2D acquisition or a slice selection in 3D acquisition.
2. 2. The method of claim 1, wherein the cloud-based simulator engine performs the recalculation and sends the recalculated data to one or more graphics processing units, GPUs, of the MRI simulator, the GPUs returning the one or more simulated MR signals.
3. 3. The method according to any one of claims 1 to 2, wherein the MR image reconstruction step is performed by one or more central processing units, CPUs, and/or the one or more graphics processing units, GPUs, of the MRI simulators in the cloud.
4. 4. The method of any one of claims 1-2, wherein at least a portion of the recalculation is performed using MATLAB.
5. 5. A method according to any one of claims 1 to 2, wherein the pulse sequence is a sequence of events that alters the way each point in space should behave to produce a signal.
6. 6. The method according to any of claims 1 to 2, wherein each new slice selection consists in providing a reference for the next slice selection.
7. 7. The method according to any one of claims 1 to 2, wherein the following process is carried out: -slice selection of the acquired image in the network interface; -obtaining a new image; -making a new slice selection in a different direction; -obtaining a new image, and, finally: -performing another slice selection.
8. 8. The method of claim 7, wherein each image obtained is a cross-section of the image for which the slice selection is made.

Description

Method for magnetic resonance scanner simulation Technical Field The invention relates to a method for magnetic resonance scanner simulation. Disclosure of Invention The present invention relates to a method for performing Magnetic Resonance (MR) scanner simulation in a Magnetic Resonance Imaging (MRI) simulator, the method comprising: -inputting data parameters into a network interface of the MRI simulator, wherein the input data parameters are at least a pulse sequence and an anatomical model; -a cloud-based simulator engine connecting the network interface and the MRI simulator to communicate data parameters to the cloud-based simulator engine, the method comprising: -importing a pulse sequence calculation model; -setting the input data, and -Slice selection of the acquired image in the network interface; The method further comprises the steps of: recalculating the data parameters to provide one or more simulated MR signals, the recalculating being performed in the cloud, And wherein the method further comprises: reconstructing an MR image based on the one or more simulated MR signals, the reconstruction of the MR image taking place in the cloud, and -Transmitting the MR image to a network interface. Christos G Xanthis and Anthony H Aletras, "CoreMRI:A high-performance, publicly available MR simulation platform on the cloud," published on PLOSONE disclose a cloud-oriented engine for advanced MRI simulation (coreMRI). The aim of this study is to develop the first advanced MR simulation platform provided as a web service by on-demand, scalable and cloud-based and GPU-based infrastructure. As described above, the online MR simulation platform can be used as a virtual MRI scanner, but can also be used as a cloud-based high performance engine for advanced MR simulation in a simulation-based quantitative MR (qMR) method. In the method used, a slice is also taken to achieve the MRI simulation process. It should be noted that the methods presented in this invention are not disclosed or implied herein. The present invention provides an improved method for implementing cloud-based MR simulation, for example, for implementing the processes provided herein above. The improvements provided by the present invention relate to the slicing process and also, for example, to the system level of how the different units interact (CPU, GPU, user interface, etc.). Detailed Description Some specific embodiments of the invention are provided and further described below. According to the invention the above method further comprises reconstructing an MR image based on the one or more simulated MR signals, the reconstruction of the MR image taking place in the cloud, and transmitting the MR image to the network interface. It will be appreciated from the foregoing that this reconstruction is a step based on actual simulation according to the present invention. The reconstruction may be part of the method according to the invention, but it is also considered that the method according to the invention also embodies the case where the raw data is a controlled expected output or the case of a quantitative MR based on simulation. According to a further embodiment of the invention, the input data parameters are at least a pulse sequence and an anatomical model. Furthermore, in the method according to the invention, other parameters may also be entered. For example, a general configuration may be specified as such an input. Further, and as will be appreciated from the foregoing, the method according to the invention is also obviously directed to the interaction of the different interfaces and units involved in the platform system according to the invention. In this context, it may be noted that the present invention is obviously directed to providing an analysis or numerical MRI simulation platform for teaching purposes, wherein the platform is Graphics Processing Unit (GPU) based, cloud based, and network based. There are other interesting applications according to the invention, for example for research and AI purposes. Further in this regard, it can also be said that according to a particular embodiment, the cloud-based simulator engine performs the recalculation and sends the recalculated data into one or more Graphics Processing Units (GPUs) of the MRI simulator, which GPU returns the one or more simulated MR signals. Furthermore, according to a further specific embodiment of the invention, the reconstruction step of the MR image is performed by one or more Central Processing Units (CPUs) and/or the one or more Graphics Processing Units (GPUs) of the MRI simulator in the cloud. In this context, it may also be noted that the characteristics/specifications of the GPU card determine how the experiment is split into smaller parts. In addition, there may be GPU resource limits (e.g., maximum threads, shared memory capacity, maximum registers per thread, register file capacity, etc.) that may limit GPU utilization. The optimal GPU card will