NSTL国家科技图书文献中心

1. Dynamic MRI reconstruction via multi-directional low-rank tensor regularization NSTL国家科技图书文献中心

Liu S. | Lei M.... - 《Biomedical signal processing and control》 - 2025,99(Jan.) - 1.1～1.16 - 共16页

摘要： dynamic MRI makes it have a multi-directional low-rank | -dimensional low-rank regularization for dynamic MRI | multi-directional slices. We take dynamic* MRI tensor* | significantly accelerates dynamic* magnetic resonance imaging* | (MRI) by allowing the exact reconstruction of images

关键词： Compressed sensing | Dynamic MRI | Multi-directional low-rank | Schatten capped p-norm

2. DYNAMIC MRI RECONSTRUCTION VIA WEIGHTED NUCLEAR NORM AND TOTAL VARIATION REGULARIZATION NSTL国家科技图书文献中心

Shi, Bao-li | Fu, Li-wen ... - 《Inverse problems and imaging》 - 2025,19(3) - 539～559 - 共21页

摘要：Dynamic Magnetic Resonance Imaging (dMRI) is a | valuable tool in the diagnosis, management and monitoring | of numerous diseases. The dimensions of the image | determine the number of radio frequency pulses that must | be applied, which makes the dMRI scan a time

关键词： Dynamic MRI | Low-rank | sparsity | total variation | weighted nuclear norm | primal-dual method

3. Dynamic glucose-enhanced MRI of gliomas: A preliminary clinical application NSTL国家科技图书文献中心

Mo, Jianhua | Xu, Xiang ... - 《NMR in biomedicine》 - 2025,38(1) - e5265～e5265 - 共12页

摘要： of dynamic* glucose-enhanced (DGE) MRI technology in* | -MRI* protocol before clinical intervention. A brief* | areas. These results show that DGE MRI* is a feasible* | clinical exam. Importantly, DGE MRI* showed enhancement in* | Gd T1w MRI* did not show any enhancement in this*

关键词： dynamic enhanced | glioma | glucose | glucoseCEST | MRI

4. Smooth robust principal component analysis based on multidimensional transform tensor for dynamic MRI NSTL国家科技图书文献中心

Liu, Xiaotong | He, Jingfei ... - 《Signal Processing》 - 2025,227 - 共14页

摘要：Dynamic magnetic resonance imaging (DMRI | ) stands as a sophisticated medical imaging technique | pivotal to clinical practice, but the protracted | duration of its imaging poses a substantial constraint on | its practical application. This paper introduces a

关键词： Dynamic magnetic resonance imaging | Low-rank | Tensor robust principal component analysis | model | Transform tensor | Weighted tensor total variation regularization

5. Artificial Intelligence Quantification of Enhanced Synovium Throughout the Entire Hand in Rheumatoid Arthritis on Dynamic Contrast-Enhanced MRI NSTL国家科技图书文献中心

Mao, Yijun | Imahori, Kiko ... - 《Journal of magnetic resonance imaging》 - 2025,61(2) - 771～783 - 共13页

摘要： dynamic contrast-enhanced (DCE) MRI in rheumatoid | optimized dynamic* MRI protocol for quantifying disease* | patients underwent DCE-MRI* with 27 phases for creating* | various DCE-MRI* time-intensity number of phases* | Background: Challenges persist in achieving

关键词： rheumatoid arthritis | dynamic contrast-enhanced MRI | artificial intelligence | one-dimensional time-intensity data | dynamic contrast‐enhanced MRI | one‐dimensional time‐intensity data

6. Computer-aided diagnosis of pituitary microadenoma on dynamic contrast-enhanced MRI based on spatio-temporal features NSTL国家科技图书文献中心

Te Guo | Jixin Luan ... - 《Expert Systems with Application》 - 2025,260(Jan.) - 125414.1～125414.11 - 共11页

摘要： Magnetic Resonance Imaging (MRI) images. To address these | , achieving classification from dynamic* contrast-enhanced* | MRI(DCE-MRI) to identify positive PM samples. For | Computer-aided diagnosis (CAD) of pituitary | microadenoma (PM) can assist doctors in decision-making

关键词： Computer-aided diagnosis | Dynamic contrast enhanced MRI | Pituitary microadenoma lesions | Spatio-temporal information | Small objects

7. A signal model for fat-suppressed T 1 -mapping and dynamic contrast-enhanced MRI with interrupted spoiled gradient-echo readout NSTL国家科技图书文献中心

Wennen, Myrte | Stehling, Wilhelm ... - 《NMR in biomedicine》 - 2025,38(1) - e5289～e5289 - 共15页

摘要： variable flip angle (VFA) MRI* and dynamic contrast* | -echo (SPGR) based quantitative MRI* models, including* | -enhanced MRI* (DCE). However, including preparation pulses* | The conventional gradient-echo steady-state | signal model is the basis of various spoiled gradient

关键词： dynamic contrast-enhanced MRI | fat suppression | spoiled gradient echo | T-1-mapping | variable flip angle | dynamic contrast‐enhanced MRI | T1‐mapping

8. Radiomics Model of Dynamic Contrast-Enhanced MRI for Evaluating Vessels Encapsulating Tumor Clusters and Microvascular Invasion in Hepatocellular Carcinoma NSTL国家科技图书文献中心

Yang, Jiawen | Dong, Xue ... - 《Academic radiology》 - 2025,32(1) - 146～156 - 共11页

摘要： validate a clinical-radiomics model of dynamic* contrast* | -enhanced MRI* (DCE-MRI) for the preoperative* | ) of DCE-MRI. Six radiomics models (intratumor and | peritumor in AP, PP, and DP of DCE-MRI) and one clinical | Rationale and Objectives: To develop and

关键词： Hepatocellular Carcinoma | Vessels Encapsulating Tumor Clusters | Microvascular Invasion | Radiomics | Dynamic Contrast- Enhanced MRI | Prognosis

9. Advanced Framework for Fetal Diffusion MRI: Dynamic Distortion and Motion Correction NSTL国家科技图书文献中心

Haykel Snoussi | Davood Karimi ... - 《Perinatal, Preterm and Paediatric Image Analysis》 - International Workshop on Preterm, Perinatal and Paediatric Image Analysis | International Conference on Medical Image Computing and Computer Assisted Intervention - 2025, - 35～45 - 共11页

摘要：-reversed dual-echo multi-shell acquisition for dynamic | Diffusion magnetic resonance imaging (dMRI) is | essential for studying the microstructure of the | developing fetal brain. However, fetal motion during scans | and its interaction with magnetic field inhomo

关键词： Fetal imaging | Diffusion MRI | Motion correction | Dynamic distortion correction

10. Development and Validation of a Deep Learning System to Differentiate HER2-Zero, HER2-Low, and HER2-Positive Breast Cancer Based on Dynamic Contrast-Enhanced MRI NSTL国家科技图书文献中心

Dai, Yi | Lian, Chun ... - 《Journal of magnetic resonance imaging》 - 2025,61(5) - 2212～2220 - 共9页

摘要： using dynamic* contrast-enhanced MRI (DCE-MRI) for* | Background: Previous studies explored MRI | centers who underwent DCE-MRI* before surgery were* | segmented tumors utilizing DCE-MRI* data, followed by a* | Conclusion: The proposed DCE-MRI-based deep learning system

摘要： dynamic MRI makes it have a multi-directional low-rank | -dimensional low-rank regularization for dynamic MRI | multi-directional slices. We take dynamic* MRI tensor* | significantly accelerates dynamic* magnetic resonance imaging* | (MRI) by allowing the exact reconstruction of images

关键词： Compressed sensing | Dynamic MRI | Multi-directional low-rank | Schatten capped p-norm

摘要：Dynamic Magnetic Resonance Imaging (dMRI) is a | valuable tool in the diagnosis, management and monitoring | of numerous diseases. The dimensions of the image | determine the number of radio frequency pulses that must | be applied, which makes the dMRI scan a time

关键词： Dynamic MRI | Low-rank | sparsity | total variation | weighted nuclear norm | primal-dual method

摘要： of dynamic* glucose-enhanced (DGE) MRI technology in* | -MRI* protocol before clinical intervention. A brief* | areas. These results show that DGE MRI* is a feasible* | clinical exam. Importantly, DGE MRI* showed enhancement in* | Gd T1w MRI* did not show any enhancement in this*

关键词： dynamic enhanced | glioma | glucose | glucoseCEST | MRI

摘要：Dynamic magnetic resonance imaging (DMRI | ) stands as a sophisticated medical imaging technique | pivotal to clinical practice, but the protracted | duration of its imaging poses a substantial constraint on | its practical application. This paper introduces a

关键词： Dynamic magnetic resonance imaging | Low-rank | Tensor robust principal component analysis | model | Transform tensor | Weighted tensor total variation regularization

摘要： dynamic contrast-enhanced (DCE) MRI in rheumatoid | optimized dynamic* MRI protocol for quantifying disease* | patients underwent DCE-MRI* with 27 phases for creating* | various DCE-MRI* time-intensity number of phases* | Background: Challenges persist in achieving

关键词： rheumatoid arthritis | dynamic contrast-enhanced MRI | artificial intelligence | one-dimensional time-intensity data | dynamic contrast‐enhanced MRI | one‐dimensional time‐intensity data

摘要： Magnetic Resonance Imaging (MRI) images. To address these | , achieving classification from dynamic* contrast-enhanced* | MRI(DCE-MRI) to identify positive PM samples. For | Computer-aided diagnosis (CAD) of pituitary | microadenoma (PM) can assist doctors in decision-making

关键词： Computer-aided diagnosis | Dynamic contrast enhanced MRI | Pituitary microadenoma lesions | Spatio-temporal information | Small objects

摘要： variable flip angle (VFA) MRI* and dynamic contrast* | -echo (SPGR) based quantitative MRI* models, including* | -enhanced MRI* (DCE). However, including preparation pulses* | The conventional gradient-echo steady-state | signal model is the basis of various spoiled gradient

关键词： dynamic contrast-enhanced MRI | fat suppression | spoiled gradient echo | T-1-mapping | variable flip angle | dynamic contrast‐enhanced MRI | T1‐mapping

摘要： validate a clinical-radiomics model of dynamic* contrast* | -enhanced MRI* (DCE-MRI) for the preoperative* | ) of DCE-MRI. Six radiomics models (intratumor and | peritumor in AP, PP, and DP of DCE-MRI) and one clinical | Rationale and Objectives: To develop and

关键词： Hepatocellular Carcinoma | Vessels Encapsulating Tumor Clusters | Microvascular Invasion | Radiomics | Dynamic Contrast- Enhanced MRI | Prognosis

摘要：-reversed dual-echo multi-shell acquisition for dynamic | Diffusion magnetic resonance imaging (dMRI) is | essential for studying the microstructure of the | developing fetal brain. However, fetal motion during scans | and its interaction with magnetic field inhomo

关键词： Fetal imaging | Diffusion MRI | Motion correction | Dynamic distortion correction

摘要： using dynamic* contrast-enhanced MRI (DCE-MRI) for* | Background: Previous studies explored MRI | centers who underwent DCE-MRI* before surgery were* | segmented tumors utilizing DCE-MRI* data, followed by a* | Conclusion: The proposed DCE-MRI-based deep learning system

关键词： dynamic contrast-enhanced MRI | deep learning | breast cancer | human epidermal growth factor receptor 2 | dynamic contrast‐enhanced MRI

4008-161-200 800-990-8900

国家科技图书文献中心

摘要： dynamic MRI makes it have a multi-directional low-rank | -dimensional low-rank regularization for dynamic MRI | multi-directional slices. We take dynamic MRI tensor | significantly accelerates dynamic magnetic resonance imaging | (MRI) by allowing the exact reconstruction of images

关键词： Compressed sensing | Dynamic MRI | Multi-directional low-rank | Schatten capped p-norm

摘要：Dynamic Magnetic Resonance Imaging (dMRI) is a | valuable tool in the diagnosis, management and monitoring | of numerous diseases. The dimensions of the image | determine the number of radio frequency pulses that must | be applied, which makes the dMRI scan a time

关键词： Dynamic MRI | Low-rank | sparsity | total variation | weighted nuclear norm | primal-dual method

摘要： of dynamic glucose-enhanced (DGE) MRI technology in | -MRI protocol before clinical intervention. A brief | areas. These results show that DGE MRI is a feasible | clinical exam. Importantly, DGE MRI showed enhancement in | Gd T1w MRI did not show any enhancement in this

关键词： dynamic enhanced | glioma | glucose | glucoseCEST | MRI

摘要：Dynamic magnetic resonance imaging (DMRI | ) stands as a sophisticated medical imaging technique | pivotal to clinical practice, but the protracted | duration of its imaging poses a substantial constraint on | its practical application. This paper introduces a

关键词： Dynamic magnetic resonance imaging | Low-rank | Tensor robust principal component analysis | model | Transform tensor | Weighted tensor total variation regularization

摘要： dynamic contrast-enhanced (DCE) MRI in rheumatoid | optimized dynamic MRI protocol for quantifying disease | patients underwent DCE-MRI with 27 phases for creating | various DCE-MRI time-intensity number of phases | Background: Challenges persist in achieving

关键词： rheumatoid arthritis | dynamic contrast-enhanced MRI | artificial intelligence | one-dimensional time-intensity data | dynamic contrast‐enhanced MRI | one‐dimensional time‐intensity data

摘要： Magnetic Resonance Imaging (MRI) images. To address these | , achieving classification from dynamic contrast-enhanced | MRI(DCE-MRI) to identify positive PM samples. For | Computer-aided diagnosis (CAD) of pituitary | microadenoma (PM) can assist doctors in decision-making

关键词： Computer-aided diagnosis | Dynamic contrast enhanced MRI | Pituitary microadenoma lesions | Spatio-temporal information | Small objects

摘要： variable flip angle (VFA) MRI and dynamic contrast | -echo (SPGR) based quantitative MRI models, including | -enhanced MRI (DCE). However, including preparation pulses | The conventional gradient-echo steady-state | signal model is the basis of various spoiled gradient

关键词： dynamic contrast-enhanced MRI | fat suppression | spoiled gradient echo | T-1-mapping | variable flip angle | dynamic contrast‐enhanced MRI | T1‐mapping

摘要： validate a clinical-radiomics model of dynamic contrast | -enhanced MRI (DCE-MRI) for the preoperative | ) of DCE-MRI. Six radiomics models (intratumor and | peritumor in AP, PP, and DP of DCE-MRI) and one clinical | Rationale and Objectives: To develop and

关键词： Hepatocellular Carcinoma | Vessels Encapsulating Tumor Clusters | Microvascular Invasion | Radiomics | Dynamic Contrast- Enhanced MRI | Prognosis

摘要：-reversed dual-echo multi-shell acquisition for dynamic | Diffusion magnetic resonance imaging (dMRI) is | essential for studying the microstructure of the | developing fetal brain. However, fetal motion during scans | and its interaction with magnetic field inhomo

关键词： Fetal imaging | Diffusion MRI | Motion correction | Dynamic distortion correction

摘要： using dynamic contrast-enhanced MRI (DCE-MRI) for | Background: Previous studies explored MRI | centers who underwent DCE-MRI before surgery were | segmented tumors utilizing DCE-MRI data, followed by a | Conclusion: The proposed DCE-MRI-based deep learning system

关键词： dynamic contrast-enhanced MRI | deep learning | breast cancer | human epidermal growth factor receptor 2 | dynamic contrast‐enhanced MRI

4008-161-200 800-990-8900

国家科技图书文献中心

摘要： dynamic MRI makes it have a multi-directional low-rank | -dimensional low-rank regularization for dynamic MRI | multi-directional slices. We take dynamic* MRI tensor* | significantly accelerates dynamic* magnetic resonance imaging* | (MRI) by allowing the exact reconstruction of images

摘要： of dynamic* glucose-enhanced (DGE) MRI technology in* | -MRI* protocol before clinical intervention. A brief* | areas. These results show that DGE MRI* is a feasible* | clinical exam. Importantly, DGE MRI* showed enhancement in* | Gd T1w MRI* did not show any enhancement in this*

摘要： dynamic contrast-enhanced (DCE) MRI in rheumatoid | optimized dynamic* MRI protocol for quantifying disease* | patients underwent DCE-MRI* with 27 phases for creating* | various DCE-MRI* time-intensity number of phases* | Background: Challenges persist in achieving

摘要： Magnetic Resonance Imaging (MRI) images. To address these | , achieving classification from dynamic* contrast-enhanced* | MRI(DCE-MRI) to identify positive PM samples. For | Computer-aided diagnosis (CAD) of pituitary | microadenoma (PM) can assist doctors in decision-making

摘要： variable flip angle (VFA) MRI* and dynamic contrast* | -echo (SPGR) based quantitative MRI* models, including* | -enhanced MRI* (DCE). However, including preparation pulses* | The conventional gradient-echo steady-state | signal model is the basis of various spoiled gradient

摘要： validate a clinical-radiomics model of dynamic* contrast* | -enhanced MRI* (DCE-MRI) for the preoperative* | ) of DCE-MRI. Six radiomics models (intratumor and | peritumor in AP, PP, and DP of DCE-MRI) and one clinical | Rationale and Objectives: To develop and

摘要： using dynamic* contrast-enhanced MRI (DCE-MRI) for* | Background: Previous studies explored MRI | centers who underwent DCE-MRI* before surgery were* | segmented tumors utilizing DCE-MRI* data, followed by a* | Conclusion: The proposed DCE-MRI-based deep learning system