AIMC Topic:
Magnetic Resonance Imaging
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Distortion-corrected image reconstruction with deep learning on an MRI-Linac.
Magnetic resonance in medicine
May 1, 2023
PURPOSE: MRI is increasingly utilized for image-guided radiotherapy due to its outstanding soft-tissue contrast and lack of ionizing radiation. However, geometric distortions caused by gradient nonlinearities (GNLs) limit anatomical accuracy, potenti...
Rapid 3D T mapping using deep learning-assisted Look-Locker inversion recovery MRI.
Magnetic resonance in medicine
May 1, 2023
PURPOSE: Conventional 3D Look-Locker inversion recovery (LLIR) T mapping requires multi-repetition data acquisition to reconstruct images at different inversion times for T fitting. To ensure B robustness, sufficient time of delay (TD) is needed betw...
Wide and deep learning based approaches for classification of Alzheimer's disease using genome-wide association studies.
PloS one
May 1, 2023
The increasing incidence of Alzheimer's disease (AD) has been leading towards a significant growth in socioeconomic challenges. A reliable prediction of AD might be useful to mitigate or at-least slow down its progression for which, identification of...
Deep learning techniques in liver tumour diagnosis using CT and MR imaging - A systematic review.
Artificial intelligence in medicine
Apr 29, 2023
Deep learning has become a thriving force in the computer aided diagnosis of liver cancer, as it solves extremely complicated challenges with high accuracy over time and facilitates medical experts in their diagnostic and treatment procedures. This p...
Prediction of total knee replacement using deep learning analysis of knee MRI.
Scientific reports
Apr 28, 2023
Current methods for assessing knee osteoarthritis (OA) do not provide comprehensive information to make robust and accurate outcome predictions. Deep learning (DL) risk assessment models were developed to predict the progression of knee OA to total k...
A least square generative network based on invariant contrastive feature pair learning for multimodal MR image synthesis.
International journal of computer assisted radiology and surgery
Apr 27, 2023
PURPOSE: During MR-guided neurosurgical procedures, several factors may limit the acquisition of additional MR sequences, which are needed by neurosurgeons to adjust surgical plans or ensure complete tumor resection. Automatically synthesized MR cont...
Deep Learning of Time-Signal Intensity Curves from Dynamic Susceptibility Contrast Imaging Enables Tissue Labeling and Prediction of Survival in Glioblastoma.
AJNR. American journal of neuroradiology
Apr 27, 2023
BACKGROUND AND PURPOSE: An autoencoder can learn representative time-signal intensity patterns to provide tissue heterogeneity measures using dynamic susceptibility contrast MR imaging. The aim of this study was to investigate whether such an autoenc...
Artificial intelligence assisted whole organ pancreatic fat estimation on magnetic resonance imaging and correlation with pancreas attenuation on computed tomography.
Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.]
Apr 26, 2023
BACKGROUND: Fatty pancreas is associated with inflammatory and neoplastic pancreatic diseases. Magnetic resonance imaging (MRI) is the diagnostic modality of choice for measuring pancreatic fat. Measurements typically use regions of interest limited ...
[Feasibility Study of the Prediction of Radiologist's Instructions with the Bi-LSTM Model Trained with Descriptions of MR Imaging Order-statement].
Nihon Hoshasen Gijutsu Gakkai zasshi
Apr 26, 2023
PURPOSE: Magnetic resonance (MR) images provide essential diagnostic information; however, it is also a very burdensome examination for patients. At our hospital, radiologists make imaging instructions for all MR examination orders, but this is a tim...
Construction and evaluation of a gated high-resolution neural network for automatic brain metastasis detection and segmentation.
European radiology
Apr 25, 2023
OBJECTIVES: To construct and evaluate a gated high-resolution convolutional neural network for detecting and segmenting brain metastasis (BM).
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