Deep learning enables reduced gadolinium dose for contrast-enhanced brain MRI

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Items 201–300 of 350

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8. Machine Learning in Medical Imaging – Clinical Applications and Challenges in Computer Vision
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17. Applications of Artificial Intelligence in MR Image Acquisition and Reconstruction
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18. T1‐contrast enhanced MRI generation from multi‐parametric MRI for glioma patients with latent tumor conditioning
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21. Multi-phase synthetic contrast enhancement in interventional computed tomography for guiding renal cryotherapy
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22. Alzheimer’s Detection and Prediction on MRI Scans: A Comparative Study
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23. Generalizing deep whole-brain segmentation for post-contrast MRI with transfer learning
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24. The Quest to Reduce the Use of Gadolinium-based Contrast Agents: AI May Provide a Solution
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26. Low-dose GBCA administration for brain tumour dynamic contrast enhanced MRI: a feasibility study
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27. Evaluating Virtual Contrast-Enhanced Magnetic Resonance Imaging in Nasopharyngeal Carcinoma Radiation Therapy: A Retrospective Analysis for Primary Gross Tumor Delineation
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28. Generative deep-learning-model based contrast enhancement for digital subtraction angiography using a text-conditioned image-to-image model
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32. Simulation of Arbitrary Level Contrast Dose in MRI Using an Iterative Global Transformer Model
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35. Interpretation of 3D CNNs for Brain MRI Data Classification
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36. Time conditioning for arbitrary contrast phase generation in interventional computed tomography
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37. Deep Learning Enables Reduced Gadolinium Dose for Contrast-Enhanced Blood-Brain Barrier Opening Quantitative Measurement
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38. Artificial Intelligence in Pediatrics
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39. Spinal Stenosis Detection in MRI using Modular Coordinate Convolutional Attention Networks
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40. MRI Pulse Sequence Integration for Deep-Learning Based Brain Metastasis Segmentation
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41. Deep Learning Substitutes Gadolinium in Detecting Functional and Structural Brain Lesions with MRI
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42. Pix2pix GAN for Image‐to‐Image Translation
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43. Exploring the Limitations of Virtual Contrast Prediction in Brain Tumor Imaging: A Study of Generalization Across Tumor Types and Patient Populations
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44. An Automated Deep Learning Based Muscular Dystrophy Detection and Classification Model
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45. AI in Acute Cerebrovascular Disorders: What can the Radiologist Contribute?
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46. Prediction of Glioma enhancement pattern using a MRI radiomics-based model
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47. AAD-DCE: An Aggregated Multimodal Attention Mechanism for Early and Late Dynamic Contrast Enhanced Prostate MRI Synthesis
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48. Application of artificial intelligence in magnetic resonance imaging to reduce gadolinium accumulation in patients with multiple sclerosis: A review
    Vijay Anant Athavale · 2022 · Science Progress and Research
49. KI-unterstützte Anwendungen und Potenziale in der Medizin- und Gesundheitstechnologie
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50. Substituting Gadolinium in Brain MRI Using DeepContrast
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51. CycleQSM: Unsupervised QSM Deep Learning using Physics-Informed CycleGAN
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52. A pilot study assessing the clinical utility of deep learning-reconstructed 3D-echo-planar-imaging-based quantitative susceptibility mapping in multiple sclerosis
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53. Gadolinium Pollution—A Future Forward Perspective on Human and Environmental Impact
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57. Artificial Intelligence in Infection Biology
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58. Virtual Contrast-Enhanced MRI Synthesis with High Model Generalizability Using Trusted Federated Learning (FL-TrustVCE): A Multi-institutional Study
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59. Gadolinium-free Magnetic Resonance Imaging of the Liver using an Oatp1-targeted Manganese(III) Porphyrin
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60. Deep Learning Enables Reduced Gadolinium Dose for Contrast-Enhanced Blood-Brain Barrier Opening
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62. Deep Learning Models for Low Dose CT Simulation
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63. Potential Role of Generative Adversarial Networks in Enhancing Brain Tumors
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64. DCE-former: A Transformer-Based Model with Mutual Information and Frequency-Based Loss Functions for Early and Late Response Prediction in Prostate DCE-MRI
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65. Exogenous Agent-Free Synthetic Post-contrast Imaging with a Cascade of Deep Networks for Enhancement Prediction After Tumor Resection. A Parametric-Map Oriented Approach
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67. Validation of deep-learning accelerated quantitative susceptibility mapping for deep brain nuclei
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68. Denoising Diffusion Probabilistic Model to Simulate Contrast-enhanced spinal MRI of Spinal Tumors: A Multi-Center Study.
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71. A deep learning model to reduce agent dose for contrast-enhanced MRI of the cerebellopontine angle cistern
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83. [Predicting cerebral glioma enhancement pattern using a machine learning-based magnetic resonance imaging radiomics model].
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