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Index by author

October 01, 2024; Volume 45,Issue 10

  1. Chen, Li

    1. Neurovascular/Stroke Imaging
      Estimating Flow Direction of Circle of Willis Using Dynamic Arterial Spin-Labeling MR Angiography
      Kaiyu Zhang, Halit Akcicek, Gen Shi, Gador Canton, Josh Liu, Yin Guo, Xin Wang, Li Chen, Kristi D. Pimentel, Ebru Yaman Akcicek, Xihe Tang, Yongjian Jin, Xuesong Li, Niranjan Balu, Thomas S. Hatsukami, Mahmud Mossa-Basha, Zhensen Chen and Chun Yuan
      American Journal of Neuroradiology October 2024, 45 (10) 1419-1426; DOI: https://doi.org/10.3174/ajnr.A8355

  2. Chen, Zhensen

    1. Neurovascular/Stroke Imaging
      Estimating Flow Direction of Circle of Willis Using Dynamic Arterial Spin-Labeling MR Angiography
      Kaiyu Zhang, Halit Akcicek, Gen Shi, Gador Canton, Josh Liu, Yin Guo, Xin Wang, Li Chen, Kristi D. Pimentel, Ebru Yaman Akcicek, Xihe Tang, Yongjian Jin, Xuesong Li, Niranjan Balu, Thomas S. Hatsukami, Mahmud Mossa-Basha, Zhensen Chen and Chun Yuan
      American Journal of Neuroradiology October 2024, 45 (10) 1419-1426; DOI: https://doi.org/10.3174/ajnr.A8355

  3. Chetta, Justin A.

    1. Neurovascular/Stroke Imaging
      Neurovascular Imaging with Ultra-High-Resolution Photon-Counting CT: Preliminary Findings on Image-Quality Evaluation
      Adrienn Tóth, Justin A. Chetta, Milad Yazdani, M. Gisele Matheus, Jim O‘Doherty, Sameer V. Tipnis and M. Vittoria Spampinato
      American Journal of Neuroradiology October 2024, 45 (10) 1450-1457; DOI: https://doi.org/10.3174/ajnr.A8350

  4. Chin, John K.

    1. EDITOR'S CHOICEEmergency Neuroradiology
      Evaluation of an Artificial Intelligence Model for Identification of Mass Effect and Vasogenic Edema on CT of the Head
      Isabella Newbury-Chaet, Sarah F. Mercaldo, John K. Chin, Ankita Ghatak, Madeleine A. Halle, Ashley L. MacDonald, Karen Buch, John Conklin, William A. Mehan, Stuart Pomerantz, Sandra Rincon, Keith J. Dreyer, Bernardo C. Bizzo and James M. Hillis
      American Journal of Neuroradiology October 2024, 45 (10) 1528-1535; DOI: https://doi.org/10.3174/ajnr.A8358

      This study compared the accuracy of a stand-alone AI model with consensus neuroradiologists’ interpretations in detecting mass effect and vasogenic edema on CT of the head. The ability to identify these findings could assist the clinical workflow through prioritizing the interpretation of abnormal cases.

  5. Cho, Nicholas S.

    1. Brain Tumor
      Pseudo-Resting-State Functional MRI Derived from Dynamic Susceptibility Contrast Perfusion MRI Can Predict Cognitive Impairment in Glioma
      Nicholas S. Cho, Chencai Wang, Kathleen Van Dyk, Francesco Sanvito, Sonoko Oshima, Jingwen Yao, Albert Lai, Noriko Salamon, Timothy F. Cloughesy, Phioanh L. Nghiemphu and Benjamin M. Ellingson
      American Journal of Neuroradiology October 2024, 45 (10) 1552-1561; DOI: https://doi.org/10.3174/ajnr.A8327

  6. Choi, Kyu Sung

    1. Neurovascular/Stroke Imaging
      Quantification of Infarct Core Volume in Patients with Acute Ischemic Stroke Using Cerebral Metabolic Rate of Oxygen in CT Perfusion
      Chuluunbaatar Otgonbaatar, Huijin Song, Keun-Hwa Jung, Inpyeong Hwang, Young Hun Jeon, Kyu Sung Choi, Dong Hyun Yoo and Chul-Ho Sohn
      American Journal of Neuroradiology October 2024, 45 (10) 1432-1440; DOI: https://doi.org/10.3174/ajnr.A8360

  7. Cloughesy, Timothy F.

    1. Brain Tumor
      Pseudo-Resting-State Functional MRI Derived from Dynamic Susceptibility Contrast Perfusion MRI Can Predict Cognitive Impairment in Glioma
      Nicholas S. Cho, Chencai Wang, Kathleen Van Dyk, Francesco Sanvito, Sonoko Oshima, Jingwen Yao, Albert Lai, Noriko Salamon, Timothy F. Cloughesy, Phioanh L. Nghiemphu and Benjamin M. Ellingson
      American Journal of Neuroradiology October 2024, 45 (10) 1552-1561; DOI: https://doi.org/10.3174/ajnr.A8327

  8. Collins, Scott

    1. Neurodegenerative Disorder Imaging
      MRI-Based Prediction of Clinical Improvement after Ventricular Shunt Placement for Normal Pressure Hydrocephalus: Development and Evaluation of an Integrated Multisequence Machine Learning Algorithm
      Owen P. Leary, Zhusi Zhong, Lulu Bi, Zhicheng Jiao, Yu-Wei Dai, Kevin Ma, Shanzeh Sayied, Daniel Kargilis, Maliha Imami, Lin-Mei Zhao, Xue Feng, Gerald Riccardello, Scott Collins, Konstantina Svokos, Abhay Moghekar, Li Yang, Harrison Bai, Petra M. Klinge and Jerrold L. Boxerman
      American Journal of Neuroradiology October 2024, 45 (10) 1536-1544; DOI: https://doi.org/10.3174/ajnr.A8372

  9. Conklin, John

    1. EDITOR'S CHOICEEmergency Neuroradiology
      Evaluation of an Artificial Intelligence Model for Identification of Mass Effect and Vasogenic Edema on CT of the Head
      Isabella Newbury-Chaet, Sarah F. Mercaldo, John K. Chin, Ankita Ghatak, Madeleine A. Halle, Ashley L. MacDonald, Karen Buch, John Conklin, William A. Mehan, Stuart Pomerantz, Sandra Rincon, Keith J. Dreyer, Bernardo C. Bizzo and James M. Hillis
      American Journal of Neuroradiology October 2024, 45 (10) 1528-1535; DOI: https://doi.org/10.3174/ajnr.A8358

      This study compared the accuracy of a stand-alone AI model with consensus neuroradiologists’ interpretations in detecting mass effect and vasogenic edema on CT of the head. The ability to identify these findings could assist the clinical workflow through prioritizing the interpretation of abnormal cases.

  10. Cross, Nathan M.

    1. Artificial Intelligence
      Using an Ensemble of Segmentation Methods to Detect Vertebral Bodies on Radiographs
      Brian C. Chang, Jonathan Renslo, Qifei Dong, Sandra K. Johnston, Jessica Perry, David R. Haynor, Gang Luo, Nancy E. Lane, Jeffrey G. Jarvik and Nathan M. Cross
      American Journal of Neuroradiology October 2024, 45 (10) 1512-1520; DOI: https://doi.org/10.3174/ajnr.A8343
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