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h5 指数:103
h5 中位数:171

h5 指数是指在过去整整 5 年中所发表文章的 h 指数。h 指在 2018-2022 年间发表的 h 篇文章每篇至少都被引用过 h 次的最大值。隐藏

出版物的 h5 中位数，是指出版物的 h5 指数所涵盖的所有文章获得的引用次数的中位值。隐藏

#8 Computer Vision & Pattern Recognition

标题/作者	引用次数	年份
Generative adversarial network in medical imaging: A review X Yi, E Walia, P Babyn Medical Image Analysis 58, 101552	1284	2019
Attention gated networks: Learning to leverage salient regions in medical images J Schlemper, O Oktay, M Schaap, M Heinrich, B Kainz, B Glocker, ... Medical Image Analysis 53, 197-207	1014	2019
f-AnoGAN: Fast unsupervised anomaly detection with generative adversarial networks T Schlegl, P Seeböck, SM Waldstein, G Langs, U Schmidt-Erfurth Medical Image Analysis 54, 30-44	822	2019
Deep-COVID: Predicting COVID-19 from chest X-ray images using deep transfer learning S Minaee, R Kafieh, M Sonka, S Yazdani, GJ Soufi Medical Image Analysis 65, 101794	818	2020
Not-so-supervised: A survey of semi-supervised, multi-instance, and transfer learning in medical image analysis V Cheplygina, M de Bruijne, JPW Pluim Medical Image Analysis 54, 280-296	690	2019
A deep learning model integrating FCNNs and CRFs for brain tumor segmentation X Zhao, Y Wu, G Song, Z Li, Y Zhang, Y Fan Medical Image Analysis 43, 98-111	659	2018
The Liver Tumor Segmentation Benchmark (LiTS). P Bilic, P Christ, HB Li, E Vorontsov, A Ben-Cohen, G Kaissis, A Szeskin, ... Medical Image Analysis 84, 102680-102680	656	2022
A deep learning framework for unsupervised affine and deformable image registration BD de Vos, FF Berendsen, MA Viergever, H Sokooti, M Staring, I Išgum Medical Image Analysis 52, 128-143	592	2019
Embracing imperfect datasets: A review of deep learning solutions for medical image segmentation N Tajbakhsh, L Jeyaseelan, Q Li, JN Chiang, Z Wu, X Ding Medical Image Analysis 63, 101693	571	2020
Hover-Net: Simultaneous segmentation and classification of nuclei in multi-tissue histology images S Graham, QD Vu, SEA Raza, A Azam, YW Tsang, JT Kwak, N Rajpoot Medical Image Analysis 58, 101563	539	2019
BACH: Grand challenge on breast cancer histology images G Aresta, T Araújo, S Kwok, SS Chennamsetty, M Safwan, V Alex, ... Medical Image Analysis 56, 122-139	443	2019
Spatial aggregation of holistically-nested convolutional neural networks for automated pancreas localization and segmentation HR Roth, L Lu, N Lay, AP Harrison, A Farag, A Sohn, RM Summers Medical Image Analysis 45, 94-107	402	2018
PadChest: A large chest x-ray image dataset with multi-label annotated reports A Bustos, A Pertusa, JM Salinas, M de la Iglesia-Vayá Medical Image Analysis 66, 101797	394	2020
Disease prediction using graph convolutional networks: Application to Autism Spectrum Disorder and Alzheimer’s disease S Parisot, SI Ktena, E Ferrante, M Lee, R Guerrero, B Glocker, D Rueckert Medical Image Analysis 48, 117-130	393	2018
REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs JI Orlando, H Fu, JB Breda, K van Keer, DR Bathula, A Diaz-Pinto, R Fang, ... Medical Image Analysis 59, 101570	374	2020
Convolutional neural networks for classification of Alzheimer's disease: Overview and reproducible evaluation J Wen, E Thibeau-Sutre, M Diaz-Melo, J Samper-González, A Routier, ... Medical Image Analysis 63, 101694	370	2020
Self-supervised learning for medical image analysis using image context restoration L Chen, P Bentley, K Mori, K Misawa, M Fujiwara, D Rueckert Medical Image Analysis 58, 101539	368	2019
Deep neural network models for computational histopathology: A survey CL Srinidhi, O Ciga, AL Martel Medical Image Analysis 67, 101813	367	2021
Deep learning with noisy labels: Exploring techniques and remedies in medical image analysis D Karimi, H Dou, SK Warfield, A Gholipour Medical Image Analysis 65, 101759	358	2020
Boundary loss for highly unbalanced segmentation H Kervadec, J Bouchtiba, C Desrosiers, E Granger, J Dolz, IB Ayed Medical Image Analysis 67, 101851	355	2021

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