Background: For both hospitals and patients it would be beneficial if the scan time of MR images could be reduced. At the moment, Compressed Sensing (CS) is introduced to reduce the scan time, however, new methods are developed such as a deep learning method, called the Recurrent Inference Machine (RIM). In this study the effect of reconstructing undersampled MRI images with lesions, using the RIM and CS, was evaluated. In data of a healthy control, lesions were simulated. Evaluation is done by checking if the lesion has the correct intensity and shape after reconstruction of undersampled data. Methods: In raw data of a healthy control lesions were simulated. To test the RIM and CS, the images with lesions where first undersampled 4x, 6x, 8...
Abstract Magnetic Resonance Imaging (MRI) plays a vital role in diagnosis, management and monitorin...
Compressed sensing (CS) is a new signal acquisition paradigm that enables the reconstruction of sign...
In recent years, there is a growing focus on the application of fast magnetic resonance imaging (MRI...
Deep learning allows for accelerated magnetic resonance image (MRI) reconstruction, thereby shorteni...
The Recurrent Inference Machine (RIM) has been developed as an alternative to the clinically used Co...
Compressed sensing accelerates magnetic resonance imaging (MRI) acquisition by undersampling of the ...
Recently, many advancements have been made in accelerated MRI reconstruction with the use of neural ...
OBJECTIVES: The aim of this study was to investigate the influence of variable density and data-driv...
Magnetic Resonance (MR) imaging is a multiparametric imaging technique allowing the diagnosis of a w...
The high fidelity reconstruction of compressed and low-resolution magnetic resonance (MR) data is es...
Classic signal processing theory dictates that, in order to faithfully reconstruct a band-limited si...
The combination of compressed sensing (CS) and parallel magnetic resonance (MR) imaging enables furt...
Objective. Machine Learning methods can learn how to reconstruct magnetic resonance images (MRI) and...
Magnetic Resonance Imaging (MRI) reconstruction algorithm using semi-PROPELLER compressed sensing is...
Abstract(#br)Compressive sensing enables fast magnetic resonance imaging (MRI) reconstruction with u...
Abstract Magnetic Resonance Imaging (MRI) plays a vital role in diagnosis, management and monitorin...
Compressed sensing (CS) is a new signal acquisition paradigm that enables the reconstruction of sign...
In recent years, there is a growing focus on the application of fast magnetic resonance imaging (MRI...
Deep learning allows for accelerated magnetic resonance image (MRI) reconstruction, thereby shorteni...
The Recurrent Inference Machine (RIM) has been developed as an alternative to the clinically used Co...
Compressed sensing accelerates magnetic resonance imaging (MRI) acquisition by undersampling of the ...
Recently, many advancements have been made in accelerated MRI reconstruction with the use of neural ...
OBJECTIVES: The aim of this study was to investigate the influence of variable density and data-driv...
Magnetic Resonance (MR) imaging is a multiparametric imaging technique allowing the diagnosis of a w...
The high fidelity reconstruction of compressed and low-resolution magnetic resonance (MR) data is es...
Classic signal processing theory dictates that, in order to faithfully reconstruct a band-limited si...
The combination of compressed sensing (CS) and parallel magnetic resonance (MR) imaging enables furt...
Objective. Machine Learning methods can learn how to reconstruct magnetic resonance images (MRI) and...
Magnetic Resonance Imaging (MRI) reconstruction algorithm using semi-PROPELLER compressed sensing is...
Abstract(#br)Compressive sensing enables fast magnetic resonance imaging (MRI) reconstruction with u...
Abstract Magnetic Resonance Imaging (MRI) plays a vital role in diagnosis, management and monitorin...
Compressed sensing (CS) is a new signal acquisition paradigm that enables the reconstruction of sign...
In recent years, there is a growing focus on the application of fast magnetic resonance imaging (MRI...