Automated segmentation of kidney and renal mass and automated detection of renal mass in CT urography using 3D U-Net-based deep convolutional neural network

Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

Freddie Bray, Jacques Ferlay, Isabelle Soerjomataram et al. · CA A Cancer Journal for Clinicians · 2018 · 87.7K citations · Full text

Medicine, Oncology, Cancer Epidemiology +16

The KiTS19 Challenge Data: 300 Kidney Tumor Cases with Clinical Context, CT Semantic Segmentations, and Surgical Outcomes

Nicholas Heller, Niranjan Sathianathen, Arveen Kalapara et al. · arXiv (Cornell University) · 2019 · 329 citations · Full text

Medicine, Oncology, Radiology +17

Automatic kidney segmentation in CT images based on multi-atlas image registration

Guanyu Yang, Jinjin Gu, Yang Chen et al. · 2014 · 73 citations

Computing, Radiology, Urology +17

Deep feature classification of angiomyolipoma without visible fat and renal cell carcinoma in abdominal contrast‐enhanced <scp>CT</scp> images with texture image patches and hand‐crafted feature concatenation

Hansang Lee, Helen Hong, Junmo Kim et al. · Medical Physics · 2018 · 66 citations · Full text

Medicine, Oncology, Radiology +17

Small renal Oncocytomas: Differentiation with multiphase CT

Georgios Gakis, Ulrich Krämer, David Schilling et al. · European Journal of Radiology · 2010 · 63 citations

Medicine, Pathology, Radiology +14