The state of the art in kidney and kidney tumor segmentation in contrast-enhanced CT imaging: Results of the KiTS19 challenge

Nicholas Heller , Fabian Isensee , Klaus Maier‐Hein , Nicholas Heller , Fabian Isensee , Klaus Maier‐Hein , Xiaoshuai Hou , Chunmei Xie , Fengyi Li , Nan Yang , Guangrui Mu , Zhiyong Lin , Miofei Han , Guang Yao , Yaozong Gao , Yao Zhang , Yixin Wang , Feng Hou , Jiawei Yang , Guangwei Xiong , Jiang Tian , Cheng Zhong , Jun Ma , Jack Rickman , Joshua Dean , Bethany Stai , Resha Tejpaul , Makinna Oestreich , Paul Blake , Heather Kaluzniak , Shaneabbas Raza , Joel Rosenberg , Keenan Moore , Edward Walczak , Zachary Rengel , Zach Edgerton , Ranveer Vasdev , Matthew Peterson , Sean McSweeney , Sarah Peterson , Arveen Kalapara , Niranjan Sathianathen , Nikolaos Papanikolopoulos , Christopher Weight
2020 Medical Image Analysis 55 citations

Keywords

SegmentationGround truthComputer scienceArtificial intelligenceDiceKidneySørensen–Dice coefficientMedicineRadiologyImage segmentationMathematicsInternal medicineStatistics

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Year
2020
Type
preprint
Volume
67
Pages
101821-101821
Citations
55
Access
Closed

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Nicholas Heller, Fabian Isensee, Klaus Maier‐Hein et al. (2020). The state of the art in kidney and kidney tumor segmentation in contrast-enhanced CT imaging: Results of the KiTS19 challenge. Medical Image Analysis , 67 , 101821-101821. https://doi.org/10.1016/j.media.2020.101821

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DOI
10.1016/j.media.2020.101821