AIMC Topic: Magnetic Resonance Imaging

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Prediction of pathologic complete response to neoadjuvant systemic therapy in triple negative breast cancer using deep learning on multiparametric MRI.

Scientific reports Jan 20, 2023
Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer. Neoadjuvant systemic therapy (NAST) followed by surgery are currently standard of care for TNBC with 50-60% of patients achieving pathologic complete response (pCR). We i...
Retrospective Studies Female Deep Learning Triple Negative Breast Neoplasms Breast Neoplasms Humans Prospective Studies Neoadjuvant Therapy Magnetic Resonance Imaging Multiparametric Magnetic Resonance Imaging
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Rapid high-fidelity mapping using single-shot overlapping-echo acquisition and deep learning reconstruction.

Magnetic resonance in medicine Jan 19, 2023
PURPOSE: To develop and evaluate a single-shot quantitative MRI technique called GRE-MOLED (gradient-echo multiple overlapping-echo detachment) for rapid mapping.
Echo-Planar Imaging Neural Networks, Computer Humans Deep Learning Brain Magnetic Resonance Imaging Phantoms, Imaging
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Diffusion MRI data analysis assisted by deep learning synthesized anatomical images (DeepAnat).

Medical image analysis Jan 19, 2023
Diffusion MRI is a useful neuroimaging tool for non-invasive mapping of human brain microstructure and structural connections. The analysis of diffusion MRI data often requires brain segmentation, including volumetric segmentation and cerebral cortic...
Image Processing, Computer-Assisted Aged Magnetic Resonance Imaging Deep Learning Humans Diffusion Magnetic Resonance Imaging Data Analysis
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MEDL-Net: A model-based neural network for MRI reconstruction with enhanced deep learned regularizers.

Magnetic resonance in medicine Jan 19, 2023
PURPOSE: To improve the MRI reconstruction performance of model-based networks and to alleviate their large demand for GPU memory.
Magnetic Resonance Imaging Acceleration Algorithms Image Processing, Computer-Assisted Neural Networks, Computer
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Comparison of a Deep Learning-Accelerated vs. Conventional T2-Weighted Sequence in Biparametric MRI of the Prostate.

Journal of magnetic resonance imaging : JMRI Jan 18, 2023
BACKGROUND: Demand for prostate MRI is increasing, but scan times remain long even in abbreviated biparametric MRIs (bpMRI). Deep learning can be leveraged to accelerate T2-weighted imaging (T2WI).
Deep Learning Magnetic Resonance Imaging Male Middle Aged Prostatic Neoplasms Prostate Retrospective Studies Aged Humans
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Editorial for "Comparison of a Deep Learning-Accelerated vs. Conventional T2-Weighted Sequence in Biparametric MRI of the Prostate".

Journal of magnetic resonance imaging : JMRI Jan 18, 2023
Humans Retrospective Studies Male Prostatic Neoplasms Prostate Deep Learning Magnetic Resonance Imaging
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Deep Learning Diagnosis and Classification of Rotator Cuff Tears on Shoulder MRI.

Investigative radiology Jan 18, 2023
BACKGROUND: Detection of rotator cuff tears, a common cause of shoulder disability, can be time-consuming and subject to reader variability. Deep learning (DL) has the potential to increase radiologist accuracy and consistency.
Rotator Cuff Injuries Humans Shoulder Deep Learning Rotator Cuff Magnetic Resonance Imaging
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Deep learning for improving ZTE MRI images in free breathing.

Magnetic resonance imaging Jan 18, 2023
INTRODUCTION: Despite a growing interest in lung MRI, its broader use in a clinical setting remains challenging. Several factors limit the image quality of lung MRI, such as the extremely short T2 and T2* relaxation times of the lung parenchyma and c...
Image Interpretation, Computer-Assisted Retrospective Studies Respiration Deep Learning Magnetic Resonance Imaging Humans
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Deep Learning Reconstruction Enables Prospectively Accelerated Clinical Knee MRI.

Radiology Jan 17, 2023
Background MRI is a powerful diagnostic tool with a long acquisition time. Recently, deep learning (DL) methods have provided accelerated high-quality image reconstructions from undersampled data, but it is unclear if DL image reconstruction can be r...
Humans Signal-To-Noise Ratio Male Knee Magnetic Resonance Imaging Knee Joint Deep Learning
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High-throughput precision MRI assessment with integrated stack-ensemble deep learning can enhance the preoperative prediction of prostate cancer Gleason grade.

British journal of cancer Jan 17, 2023
BACKGROUND: To develop and test a Prostate Imaging Stratification Risk (PRISK) tool for precisely assessing the International Society of Urological Pathology Gleason grade (ISUP-GG) of prostate cancer (PCa).
Prostatic Neoplasms Humans Deep Learning Male Magnetic Resonance Imaging Neoplasm Grading Prostate
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