AIMC Topic: Magnetic Resonance Imaging
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Neural Network Detection of Pacemakers for MRI Safety.
Journal of digital imaging
Jun 29, 2022
Flagging the presence of cardiac devices such as pacemakers before an MRI scan is essential to allow appropriate safety checks. We assess the accuracy with which a machine learning model can classify the presence or absence of a pacemaker on pre-exis...
A Deep Learning Approach for Automated Segmentation of Kidneys and Exophytic Cysts in Individuals with Autosomal Dominant Polycystic Kidney Disease.
Journal of the American Society of Nephrology : JASN
Jun 29, 2022
BACKGROUND: Total kidney volume (TKV) is an important imaging biomarker in autosomal dominant polycystic kidney disease (ADPKD). Manual computation of TKV, particularly with the exclusion of exophytic cysts, is laborious and time consuming.
Logistic Regression-Based Model Is More Efficient Than U-Net Model for Reliable Whole Brain Magnetic Resonance Imaging Segmentation.
Topics in magnetic resonance imaging : TMRI
Jun 28, 2022
OBJECTIVES: Automated whole brain segmentation from magnetic resonance images is of great interest for the development of clinically relevant volumetric markers for various neurological diseases. Although deep learning methods have demonstrated remar...
Feasibility of accelerated whole-body diffusion-weighted imaging using a deep learning-based noise-reduction technique in patients with prostate cancer.
Magnetic resonance imaging
Jun 27, 2022
PURPOSE: To assess the possibility of reducing the image acquisition time for diffusion-weighted whole-body imaging with background body signal suppression (DWIBS) by denoising with deep learning-based reconstruction (dDLR).
Deep learning-based acceleration of Compressed Sense MR imaging of the ankle.
European radiology
Jun 25, 2022
OBJECTIVES: To evaluate a compressed sensing artificial intelligence framework (CSAI) to accelerate MRI acquisition of the ankle.
DeepStroke: An efficient stroke screening framework for emergency rooms with multimodal adversarial deep learning.
Medical image analysis
Jun 25, 2022
In an emergency room (ER) setting, stroke triage or screening is a common challenge. A quick CT is usually done instead of MRI due to MRI's slow throughput and high cost. Clinical tests are commonly referred to during the process, but the misdiagnosi...
A state-of-the-art technique to perform cloud-based semantic segmentation using deep learning 3D U-Net architecture.
BMC bioinformatics
Jun 24, 2022
Glioma is the most aggressive and dangerous primary brain tumor with a survival time of less than 14 months. Segmentation of tumors is a necessary task in the image processing of the gliomas and is important for its timely diagnosis and starting a tr...
Optimal Superpixel Kernel-Based Kernel Low-Rank and Sparsity Representation for Brain Tumour Segmentation.
Computational intelligence and neuroscience
Jun 24, 2022
Given the need for quantitative measurement and 3D visualisation of brain tumours, more and more attention has been paid to the automatic segmentation of tumour regions from brain tumour magnetic resonance (MR) images. In view of the uneven grey dist...
Eliminating CT radiation for clinical PET examination using deep learning.
European journal of radiology
Jun 23, 2022
Clinical PET/CT examinations rely on CT modality for anatomical localization and attenuation correction of the PET data. However, the use of CT significantly increases the risk of ionizing radiation exposure for patients. We propose a deep learning f...
Multimodal Magnetic Resonance Imaging to Diagnose Knee Osteoarthritis under Artificial Intelligence.
Computational intelligence and neuroscience
Jun 23, 2022
This work aimed to investigate the application value of the multimodal magnetic resonance imaging (MRI) algorithm based on the low-rank decomposition denoising (LRDD) in the diagnosis of knee osteoarthritis (KOA), so as to offer a better examination ...
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