AIMC Topic: Magnetic Resonance Imaging
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Hybrid Optimization Algorithm Enabled Deep Learning Approach Brain Tumor Segmentation and Classification Using MRI.
Journal of digital imaging
Jan 9, 2023
The unnatural and uncontrolled increase of brain cells is called brain tumors, leading to human health danger. Magnetic resonance imaging (MRI) is widely applied for classifying and detecting brain tumors, due to its better resolution. In general, me...
Acceleration of knee magnetic resonance imaging using a combination of compressed sensing and commercially available deep learning reconstruction: a preliminary study.
BMC medical imaging
Jan 9, 2023
PURPOSE: To evaluate whether deep learning reconstruction (DLR) accelerates the acquisition of 1.5-T magnetic resonance imaging (MRI) knee data without image deterioration.
Democratization of deep learning for segmenting cartilage from MRIs of human knees: Application to data from the osteoarthritis initiative.
Journal of orthopaedic research : official publication of the Orthopaedic Research Society
Jan 7, 2023
In this study, we aimed to democratize access to convolutional neural networks (CNN) for segmenting cartilage volumes, generating state-of-the-art results for specialized, real-world applications in hospitals and research. Segmentation of cross-secti...
Application of deep learning-based super-resolution to T1-weighted postcontrast gradient echo imaging of the chest.
La Radiologia medica
Jan 7, 2023
OBJECTIVES: A deep learning-based super-resolution for postcontrast volume-interpolated breath-hold examination (VIBE) of the chest was investigated in this study. Aim was to improve image quality, noise, artifacts and diagnostic confidence without c...
Lesion-preserving unpaired image-to-image translation between MRI and CT from ischemic stroke patients.
International journal of computer assisted radiology and surgery
Jan 6, 2023
PURPOSE: Multiple medical imaging modalities are used for clinical follow-up ischemic stroke analysis. Mixed-modality datasets are challenging, both for clinical rating purposes and for training machine learning models. While image-to-image translati...
Deep Learning-Based Multiclass Brain Tissue Segmentation in Fetal MRIs.
Sensors (Basel, Switzerland)
Jan 6, 2023
Fetal brain tissue segmentation is essential for quantifying the presence of congenital disorders in the developing fetus. Manual segmentation of fetal brain tissue is cumbersome and time-consuming, so using an automatic segmentation method can great...
Prostatic urinary tract visualization with super-resolution deep learning models.
PloS one
Jan 6, 2023
In urethra-sparing radiation therapy, prostatic urinary tract visualization is important in decreasing the urinary side effect. A methodology has been developed to visualize the prostatic urinary tract using post-urination magnetic resonance imaging ...
Deep learning prediction of pathological complete response, residual cancer burden, and progression-free survival in breast cancer patients.
PloS one
Jan 6, 2023
The goal of this study was to employ novel deep-learning convolutional-neural-network (CNN) to predict pathological complete response (PCR), residual cancer burden (RCB), and progression-free survival (PFS) in breast cancer patients treated with neoa...
Rapid lumbar MRI protocol using 3D imaging and deep learning reconstruction.
Skeletal radiology
Jan 5, 2023
BACKGROUND AND PURPOSE: Three-dimensional (3D) imaging of the spine, augmented with AI-enabled image enhancement and denoising, has the potential to reduce imaging times without compromising image quality or diagnostic performance. This work evaluate...
4D segmentation of the thoracic aorta from 4D flow MRI using deep learning.
Magnetic resonance imaging
Jan 5, 2023
BACKGROUND: 4D flow MRI allows the analysis of hemodynamic changes in the aorta caused by pathologies such as thoracic aortic aneurysms (TAA). For personalized management of TAA, new biomarkers are required to analyze the effect of fluid structure it...
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