日期 影响因子
日期:
2020 年 — 2026 年
2020
2021
2022
2023
2024
2025
2026
影响因子:
–

THINGSplus: New norms and metadata for the THINGS database of 1854 object concepts and 26,107 natural object images

THINGSplus：为包含 1854 个物体概念和 26107 个自然物体图像的 THINGS 数据库添加新的规范和元数据

期刊:Behavior Research Methods
影响因子:3.9
doi:10.3758/s13428-023-02110-8
Stoinski, Laura M; Perkuhn, Jonas; Hebart, Martin N
发表日期：2024
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AI support for accurate and fast radiological diagnosis of COVID-19: an international multicenter, multivendor CT study

人工智能辅助实现COVID-19放射学诊断的准确快速：一项国际多中心、多厂商CT研究

期刊:European Radiology
影响因子:4.7
doi:10.1007/s00330-022-09335-9
Meng, Fanyang; Kottlors, Jonathan; Shahzad, Rahil; Liu, Haifeng; Fervers, Philipp; Jin, Yinhua; Rinneburger, Miriam; Le, Dou; Weisthoff, Mathilda; Liu, Wenyun; Ni, Mengzhe; Sun, Ye; An, Liying; Huai, Xiaochen; Móré, Dorottya; Giannakis, Athanasios; Kaltenborn, Isabel; Bucher, Andreas; Maintz, David; Zhang, Lei; Thiele, Frank; Li, Mingyang; Perkuhn, Michael; Zhang, Huimao; Persigehl, Thorsten
发表日期：2023
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Automated Detection and Segmentation of Brain Metastases in Malignant Melanoma: Evaluation of a Dedicated Deep Learning Model

恶性黑色素瘤脑转移的自动检测与分割：专用深度学习模型的评估

期刊:American Journal of Neuroradiology
影响因子:3.7
doi:10.3174/ajnr.A6982
Pennig, L; Shahzad, R; Caldeira, L; Lennartz, S; Thiele, F; Goertz, L; Zopfs, D; Meißner, A-K; Fürtjes, G; Perkuhn, M; Kabbasch, C; Grau, S; Borggrefe, J; Laukamp, K R
黑色素瘤
神经科学
发表日期：2021
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Deep learning assistance increases the detection sensitivity of radiologists for secondary intracranial aneurysms in subarachnoid hemorrhage

深度学习辅助技术提高了放射科医生对蛛网膜下腔出血继发性颅内动脉瘤的检测敏感性。

期刊:Neuroradiology
影响因子:2.6
doi:10.1007/s00234-021-02697-9
Pennig, Lenhard; Hoyer, Ulrike Cornelia Isabel; Krauskopf, Alexandra; Shahzad, Rahil; Jünger, Stephanie T; Thiele, Frank; Laukamp, Kai Roman; Grunz, Jan-Peter; Perkuhn, Michael; Schlamann, Marc; Kabbasch, Christoph; Borggrefe, Jan; Goertz, Lukas
心血管
动脉瘤
发表日期：2021
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Comparison of Accuracy of Arrival-Time-Insensitive and Arrival-Time-Sensitive CTP Algorithms for Prediction of Infarct Tissue Volumes

比较到达时间不敏感和到达时间敏感的CTP算法在预测梗死组织体积方面的准确性

期刊:Scientific Reports
影响因子:3.9
doi:10.1038/s41598-020-66041-6
Pennig, Lenhard; Thiele, Frank; Goertz, Lukas; Laukamp, Kai Roman; Perkuhn, Michael; Kabbasch, Christoph; Schlamann, Marc; Fink, Gereon Rudolf; Borggrefe, Jan
发表日期：2020
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Fully automated detection and segmentation of intracranial aneurysms in subarachnoid hemorrhage on CTA using deep learning

利用深度学习对CTA图像上蛛网膜下腔出血合并颅内动脉瘤进行全自动检测和分割

期刊:Scientific Reports
影响因子:3.9
doi:10.1038/s41598-020-78384-1
Shahzad, Rahil; Pennig, Lenhard; Goertz, Lukas; Thiele, Frank; Kabbasch, Christoph; Schlamann, Marc; Krischek, Boris; Maintz, David; Perkuhn, Michael; Borggrefe, Jan
心血管
动脉瘤
发表日期：2020
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Fully automated detection and segmentation of meningiomas using deep learning on routine multiparametric MRI

利用深度学习对常规多参数磁共振成像数据进行脑膜瘤的全自动检测和分割

期刊:European Radiology
影响因子:4.7
doi:10.1007/s00330-018-5595-8
Laukamp, Kai Roman; Thiele, Frank; Shakirin, Georgy; Zopfs, David; Faymonville, Andrea; Timmer, Marco; Maintz, David; Perkuhn, Michael; Borggrefe, Jan
神经科学
发表日期：2019
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Clinical Evaluation of a Multiparametric Deep Learning Model for Glioblastoma Segmentation Using Heterogeneous Magnetic Resonance Imaging Data From Clinical Routine

基于临床常规异质磁共振成像数据的胶质母细胞瘤分割多参数深度学习模型的临床评估

期刊:Investigative Radiology
影响因子:8
doi:10.1097/RLI.0000000000000484
Perkuhn, Michael; Stavrinou, Pantelis; Thiele, Frank; Shakirin, Georgy; Mohan, Manoj; Garmpis, Dionysios; Kabbasch, Christoph; Borggrefe, Jan
细胞生物学
发表日期：2018
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