Journal of magnetic resonance imaging : JMRI
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J Magn Reson Imaging · May 2020
ReviewArtificial intelligence in the interpretation of breast cancer on MRI.
Advances in both imaging and computers have led to the rise in the potential use of artificial intelligence (AI) in various tasks in breast imaging, going beyond the current use in computer-aided detection to include diagnosis, prognosis, response to therapy, and risk assessment. The automated capabilities of AI offer the potential to enhance the diagnostic expertise of clinicians, including accurate demarcation of tumor volume, extraction of characteristic cancer phenotypes, translation of tumoral phenotype features to clinical genotype implications, and risk prediction. The combination of image-specific findings with the underlying genomic, pathologic, and clinical features is becoming of increasing value in breast cancer. ⋯ Magn. Reson. Imaging 2020;51:1310-1324.
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J Magn Reson Imaging · Jun 2019
Meta Analysis Comparative StudyCervical spine findings on MRI in people with neck pain compared with pain-free controls: A systematic review and meta-analysis.
There is uncertainty regarding the clinical significance of findings on MRI in patients with whiplash associated disorder (WAD) or nonspecific neck pain (NSNP). ⋯ 3 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018.
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J Magn Reson Imaging · Apr 2019
ReviewDeep learning in radiology: An overview of the concepts and a survey of the state of the art with focus on MRI.
Deep learning is a branch of artificial intelligence where networks of simple interconnected units are used to extract patterns from data in order to solve complex problems. Deep-learning algorithms have shown groundbreaking performance in a variety of sophisticated tasks, especially those related to images. They have often matched or exceeded human performance. ⋯ Magn. Reson. Imaging 2019;49:939-954.
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J Magn Reson Imaging · Jan 2019
Systematic review on the characterization of chronic traumatic encephalopathy by MRI and MRS.
Chronic traumatic encephalopathy (CTE) is a neurodegenerative disease that is found in people who have suffered from chronic traumatic brain injury (TBI). Up to now, diagnosis of CTE could only be made based on postmortem histopathological examinations. The application of MR techniques might offer a promising possibility for in vivo diagnoses. ⋯ 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:212-228.
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Renal function varies according to the nature and stage of diseases. Renal functional magnetic resonance imaging (fMRI), a technique considered superior to the most common method used to estimate the glomerular filtration rate, allows for noninvasive, accurate measurements of renal structures and functions in both animals and humans. ⋯ Function-related imaging markers can be acquired via renal fMRI, encompassing water molecular diffusion, perfusion, and oxygenation. This review focuses on the progression and challenges of the main renal fMRI methods, including dynamic contrast-enhanced MRI, blood oxygen level-dependent MRI, diffusion-weighted imaging, diffusion tensor imaging, arterial spin labeling, fat fraction imaging, and their recent clinical applications.