D
Dakai Jin
Researcher at National Institutes of Health
Publications - 88
Citations - 1742
Dakai Jin is an academic researcher from National Institutes of Health. The author has contributed to research in topics: Segmentation & Computer science. The author has an hindex of 19, co-authored 74 publications receiving 1103 citations. Previous affiliations of Dakai Jin include University of Iowa.
Papers
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Journal ArticleDOI
Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities and Results of the WMH Segmentation Challenge
Hugo J. Kuijf,Adrià Casamitjana,D. Louis Collins,Mahsa Dadar,Achilleas Georgiou,Mohsen Ghafoorian,Dakai Jin,April Khademi,Jesse Knight,Hongwei Li,Xavier Lladó,J. Matthijs Biesbroek,Miguel Luna,Qaiser Mahmood,Richard McKinley,Alireza Mehrtash,Sebastien Ourselin,Bo-yong Park,Hyunjin Park,Sang-Hyun Park,Simon Pezold,Elodie Puybareau,Jeroen de Bresser,Leticia Rittner,Carole H. Sudre,Sergi Valverde,Verónica Vilaplana,Roland Wiest,Yongchao Xu,Ziyue Xu,Guodong Zeng,Jianguo Zhang,Guoyan Zheng,Rutger Heinen,Christopher Chen,Wiesje M. van der Flier,Frederik Barkhof,Max A. Viergever,Geert Jan Biessels,Simon Andermatt,Mariana P. Bento,Matt Berseth,Mikhail Belyaev,M. Jorge Cardoso +43 more
TL;DR: There is a cluster of four methods that rank significantly better than the other methods, with one clear winner, and the inter-scanner robustness ranking shows that not all the methods generalize to unseen scanners.
Journal ArticleDOI
Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities and Results of the WMH Segmentation Challenge
Hugo J. Kuijf,J. Matthijs Biesbroek,Jeroen de Bresser,Rutger Heinen,Simon Andermatt,Mariana P. Bento,Matt Berseth,Mikhail Belyaev,M. Jorge Cardoso,Adrià Casamitjana,D. Louis Collins,Mahsa Dadar,Achilleas Georgiou,Mohsen Ghafoorian,Dakai Jin,April Khademi,Jesse Knight,Hongwei Li,Xavier Lladó,Miguel Luna,Qaiser Mahmood,Richard McKinley,Alireza Mehrtash,Sebastien Ourselin,Bo-yong Park,Hyunjin Park,Sang-Hyun Park,Simon Pezold,Elodie Puybareau,Leticia Rittner,Carole H. Sudre,Sergi Valverde,Verónica Vilaplana,Roland Wiest,Yongchao Xu,Ziyue Xu,Guodong Zeng,Jianguo Zhang,Guoyan Zheng,Christopher Chen,Wiesje M. van der Flier,Frederik Barkhof,Max A. Viergever,Geert Jan Biessels +43 more
TL;DR: The WMH segmentation challenge as discussed by the authors was the first attempt to evaluate the performance of automatic segmentation of cerebral white matter hyperintensities (WMH) of presumed vascular origin.
Book ChapterDOI
CT-Realistic Lung Nodule Simulation from 3D Conditional Generative Adversarial Networks for Robust Lung Segmentation
TL;DR: This work develops a 3D generative adversarial network (GAN) that effectively learns lung nodule property distributions in 3D space and proposes a novel multi-mask reconstruction loss to improve realism and blending with the background.
Journal ArticleDOI
Quantitative Dual-Energy Computed Tomography Supports a Vascular Etiology of Smoking-induced Inflammatory Lung Disease
Krishna S. Iyer,John D. Newell,Dakai Jin,Matthew K. Fuld,Punam K. Saha,Sif Hansdottir,Eric A. Hoffman +6 more
TL;DR: These results demonstrate that sildenafil restores peripheral perfusion and reduces central arterial enlargement in normal SS subjects with little effect in NS subjects, highlighting DECT-PBV as a biomarker of reversible endothelial dysfunction in smokers with CAE.
Journal ArticleDOI
From community-acquired pneumonia to COVID-19: a deep learning-based method for quantitative analysis of COVID-19 on thick-section CT scans.
Zhang Li,Zheng Zhong,Yang Li,Tianyu Zhang,Tianyu Zhang,Liangxin Gao,Dakai Jin,Yue Sun,Xianghua Ye,Li Yu,Zheyu Hu,Jing Xiao,Lingyun Huang,Yuling Tang +13 more
TL;DR: A deep learning–based AI system built on the thick-section CT imaging can accurately quantify the COVID-19-associated lung abnormalities and assess the disease severity and its progressions.