Orientation recognition and correction of Cardiac MRI with deep neural network

11/21/2022
by   Jiyao Liu, et al.
0

In this paper, the problem of orientation correction in cardiac MRI images is investigated and a framework for orientation recognition via deep neural networks is proposed. For multi-modality MRI, we introduce a transfer learning strategy to transfer our proposed model from single modality to multi-modality. We embed the proposed network into the orientation correction command-line tool, which can implement orientation correction on 2D DICOM and 3D NIFTI images. Our source code, network models and tools are available at https://github.com/Jy-stdio/MSCMR_orient/

READ FULL TEXT
research
11/17/2020

Recognition and standardization of cardiac MRI orientation via multi-tasking learning and deep neural networks

In this paper, we study the problem of imaging orientation in cardiac MR...
research
07/31/2023

Cardiac MRI Orientation Recognition and Standardization using Deep Neural Networks

Orientation recognition and standardization play a crucial role in the e...
research
05/15/2019

Simultaneous Inference Under the Vacuous Orientation Assumption

I propose a novel approach to simultaneous inference that alleviates the...
research
11/14/2022

Recognition of Cardiac MRI Orientation via Deep Neural Networks and a Method to Improve Prediction Accuracy

In most medical image processing tasks, the orientation of an image woul...
research
01/05/2021

Density Compensated Unrolled Networks for Non-Cartesian MRI Reconstruction

Deep neural networks have recently been thoroughly investigated as a pow...
research
02/13/2021

Rotation-Equivariant Deep Learning for Diffusion MRI

Convolutional networks are successful, but they have recently been outpe...
research
10/19/2019

Attention Guided Metal Artifact Correction in MRI using Deep Neural Networks

An attention guided scheme for metal artifact correction in MRI using de...

Please sign up or login with your details

Forgot password? Click here to reset