Index by author
Wang, D.
- SpineOpen AccessDeep Learning–Based Automatic Segmentation of Lumbosacral Nerves on CT for Spinal Intervention: A Translational StudyG. Fan, H. Liu, Z. Wu, Y. Li, C. Feng, D. Wang, J. Luo, W.M. Wells and S. HeAmerican Journal of Neuroradiology June 2019, 40 (6) 1074-1081; DOI: https://doi.org/10.3174/ajnr.A6070
Wang, X.
- FELLOWS' JOURNAL CLUBAdult BrainOpen AccessSurveillance of Unruptured Intracranial Saccular Aneurysms Using Noncontrast 3D-Black-Blood MRI: Comparison of 3D-TOF and Contrast-Enhanced MRA with 3D-DSAC. Zhu, X. Wang, L. Eisenmenger, B. Tian, Q. Liu, A.J. Degnan, C. Hess, D. Saloner and J. LuAmerican Journal of Neuroradiology June 2019, 40 (6) 960-966; DOI: https://doi.org/10.3174/ajnr.A6080
Sixty-four patients with 68 saccular unruptured intracranial aneurysms were recruited. Patients underwent 3T MR imaging with 3D-TOF-MRA, 3D black-blood MR imaging, and contrast-enhanced MRA, and they underwent 3D rotational angiography within 2 weeks. The neck, width, and height of the unruptured intracranial aneurysms were measured by 2 radiologists independently on 3D rotational angiography and 3 MR imaging sequences. 3D black-blood MR imaging demonstrates the best agreement with DSA, with the smallest limits of agreement and measurement error. 3D-TOF-MRA had the largest limits of agreement and measurement error. The authors conclude that 3D black-blood MR imaging achieves better accuracy for aneurysm size measurements compared with 3D-TOF, using 3D rotational angiography as a criterion standard.
Wang, Y.
- Adult BrainOpen AccessQuantitative Susceptibility Mapping of Time-Dependent Susceptibility Changes in Multiple Sclerosis LesionsS. Zhang, T.D. Nguyen, S.M. Hurtado Rúa, U.W. Kaunzner, S. Pandya, I. Kovanlikaya, P. Spincemaille, Y. Wang and S.A. GauthierAmerican Journal of Neuroradiology June 2019, 40 (6) 987-993; DOI: https://doi.org/10.3174/ajnr.A6071
Wang, Y.-L.
- Adult BrainOpen AccessAssociation between Tumor Acidity and Hypervascularity in Human Gliomas Using pH-Weighted Amine Chemical Exchange Saturation Transfer Echo-Planar Imaging and Dynamic Susceptibility Contrast Perfusion MRI at 3TY.-L. Wang, J. Yao, A. Chakhoyan, C. Raymond, N. Salamon, L.M. Liau, P.L. Nghiemphu, A. Lai, W.B. Pope, N. Nguyen, M. Ji, T.F. Cloughesy and B.M. EllingsonAmerican Journal of Neuroradiology June 2019, 40 (6) 979-986; DOI: https://doi.org/10.3174/ajnr.A6063
Wells, W.M.
- SpineOpen AccessDeep Learning–Based Automatic Segmentation of Lumbosacral Nerves on CT for Spinal Intervention: A Translational StudyG. Fan, H. Liu, Z. Wu, Y. Li, C. Feng, D. Wang, J. Luo, W.M. Wells and S. HeAmerican Journal of Neuroradiology June 2019, 40 (6) 1074-1081; DOI: https://doi.org/10.3174/ajnr.A6070
Wimmer, K.
- LetterYou have accessPatients with High-Grade Gliomas and Café-au-Lait Macules: Is Neurofibromatosis Type 1 the Only Diagnosis?L. Guerrini-Rousseau, M. Suerink, J. Grill, E. Legius, K. Wimmer and L. BrugièresAmerican Journal of Neuroradiology June 2019, 40 (6) E30-E31; DOI: https://doi.org/10.3174/ajnr.A6058
Winzeck, S.
- EDITOR'S CHOICEAdult BrainOpen AccessEnsemble of Convolutional Neural Networks Improves Automated Segmentation of Acute Ischemic Lesions Using Multiparametric Diffusion-Weighted MRIS. Winzeck, S.J.T. Mocking, R. Bezerra, M.J.R.J. Bouts, E.C. McIntosh, I. Diwan, P. Garg, A. Chutinet, W.T. Kimberly, W.A. Copen, P.W. Schaefer, H. Ay, A.B. Singhal, K. Kamnitsas, B. Glocker, A.G. Sorensen and O. WuAmerican Journal of Neuroradiology June 2019, 40 (6) 938-945; DOI: https://doi.org/10.3174/ajnr.A6077
Convolutional neural networks were trained on combinations of DWI, ADC, and low b-value-weighted images from 116 subjects. The performances of the networks (measured by the Dice score, sensitivity, and precision) were compared with one another and with ensembles of 5 networks. An ensemble of convolutional neural networks trained on DWI, ADC, and low b-value-weighted images produced the most accurate acute infarct segmentation over individual networks. Automated volumes correlated with manually measured volumes for the independent cohort.
Wolf, D.S.
- LetterYou have accessReply:N. Kadom, R.C. Castellino and D.S. WolfAmerican Journal of Neuroradiology June 2019, 40 (6) E32; DOI: https://doi.org/10.3174/ajnr.A6062
Wu, O.
- EDITOR'S CHOICEAdult BrainOpen AccessEnsemble of Convolutional Neural Networks Improves Automated Segmentation of Acute Ischemic Lesions Using Multiparametric Diffusion-Weighted MRIS. Winzeck, S.J.T. Mocking, R. Bezerra, M.J.R.J. Bouts, E.C. McIntosh, I. Diwan, P. Garg, A. Chutinet, W.T. Kimberly, W.A. Copen, P.W. Schaefer, H. Ay, A.B. Singhal, K. Kamnitsas, B. Glocker, A.G. Sorensen and O. WuAmerican Journal of Neuroradiology June 2019, 40 (6) 938-945; DOI: https://doi.org/10.3174/ajnr.A6077
Convolutional neural networks were trained on combinations of DWI, ADC, and low b-value-weighted images from 116 subjects. The performances of the networks (measured by the Dice score, sensitivity, and precision) were compared with one another and with ensembles of 5 networks. An ensemble of convolutional neural networks trained on DWI, ADC, and low b-value-weighted images produced the most accurate acute infarct segmentation over individual networks. Automated volumes correlated with manually measured volumes for the independent cohort.
Wu, Z.
- SpineOpen AccessDeep Learning–Based Automatic Segmentation of Lumbosacral Nerves on CT for Spinal Intervention: A Translational StudyG. Fan, H. Liu, Z. Wu, Y. Li, C. Feng, D. Wang, J. Luo, W.M. Wells and S. HeAmerican Journal of Neuroradiology June 2019, 40 (6) 1074-1081; DOI: https://doi.org/10.3174/ajnr.A6070
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