AIMC Topic:
Magnetic Resonance Imaging
Clear Filters Showing 1161 to 1170 of 5972 articles
[Accelerated musculoskeletal magnetic resonance imaging with deep learning-based image reconstruction at 0.55 T-3 T].
Radiologie (Heidelberg, Germany)
Jun 12, 2024
CLINICAL/METHODICAL ISSUE: Magnetic resonance imaging (MRI) is a central component of musculoskeletal imaging. However, long image acquisition times can pose practical barriers in clinical practice.
A Predictive Model for Intraoperative Cerebrospinal Fluid Leak During Endonasal Pituitary Adenoma Resection Using a Convolutional Neural Network.
World neurosurgery
Jun 12, 2024
BACKGROUND: Cerebrospinal fluid (CSF) leak during endoscopic endonasal transsphenoidal surgery can lead to postoperative complications. The clinical and anatomic risk factors of intraoperative CSF leak are not well defined. We applied a two-dimension...
Discovering the gene-brain-behavior link in autism via generative machine learning.
Science advances
Jun 12, 2024
Autism is traditionally diagnosed behaviorally but has a strong genetic basis. A genetics-first approach could transform understanding and treatment of autism. However, isolating the gene-brain-behavior relationship from confounding sources of variab...
Deep Learning Reconstructed New-Generation 0.55 T MRI of the Knee-A Prospective Comparison With Conventional 3 T MRI.
Investigative radiology
Jun 11, 2024
OBJECTIVES: The aim of this study was to compare deep learning reconstructed (DLR) 0.55 T magnetic resonance imaging (MRI) quality, identification, and grading of structural anomalies and reader confidence levels with conventional 3 T knee MRI in pat...
URCA: Uncertainty-based region clipping algorithm for semi-supervised medical image segmentation.
Computer methods and programs in biomedicine
Jun 11, 2024
BACKGROUND AND OBJECTIVE: Training convolutional neural networks based on large amount of labeled data has made great progress in the field of image segmentation. However, in medical image segmentation tasks, annotating the data is expensive and time...
Artificial intelligence and radiologists in prostate cancer detection on MRI (PI-CAI): an international, paired, non-inferiority, confirmatory study.
The Lancet. Oncology
Jun 11, 2024
BACKGROUND: Artificial intelligence (AI) systems can potentially aid the diagnostic pathway of prostate cancer by alleviating the increasing workload, preventing overdiagnosis, and reducing the dependence on experienced radiologists. We aimed to inve...
Artificial intelligence for scoring prostate MRI: ready for prospective evaluation.
The Lancet. Oncology
Jun 11, 2024
Artificial Intelligence Improves the Ability of Physicians to Identify Prostate Cancer Extent.
The Journal of urology
Jun 11, 2024
PURPOSE: Defining prostate cancer contours is a complex task, undermining the efficacy of interventions such as focal therapy. A multireader multicase study compared physicians' performance using artificial intelligence (AI) vs standard-of-care metho...
Artificial intelligence solution to accelerate the acquisition of MRI images: Impact on the therapeutic care in oncology in radiology and radiotherapy departments.
Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique
Jun 11, 2024
PURPOSE: MRI is essential in the management of brain tumours. However, long waiting times reduce patient accessibility. Reducing acquisition time could improve access but at the cost of spatial resolution and diagnostic quality. A commercially availa...
Parallel CNN-Deep Learning Clinical-Imaging Signature for Assessing Pathologic Grade and Prognosis of Soft Tissue Sarcoma Patients.
Journal of magnetic resonance imaging : JMRI
Jun 10, 2024
BACKGROUND: Traditional biopsies pose risks and may not accurately reflect soft tissue sarcoma (STS) heterogeneity. MRI provides a noninvasive, comprehensive alternative.
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