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Zach Edgerton
Researcher at University of Minnesota
Publications - 7
Citations - 453
Zach Edgerton is an academic researcher from University of Minnesota. The author has contributed to research in topics: Medical image computing & Urinary continence. The author has an hindex of 5, co-authored 7 publications receiving 95 citations.
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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 H. Maier-Hein,Xiaoshuai Hou,Xie Chunmei,Fengyi Li,Yang Nan,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 H. Peterson,Arveen Kalapara,Niranjan J. Sathianathen,Nikolaos Papanikolopoulos,Christopher J. Weight +40 more
TL;DR: The 2019 Kidney and Kidney Tumor Segmentation challenge (KiTS19) was a competition held in conjunction with the 2019 International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) which sought to address issues and stimulate progress on this automatic segmentation problem.
Posted Content
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 H. Maier-Hein,Xiaoshuai Hou,Xie Chunmei,Fengyi Li,Yang Nan,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 H. Peterson,Arveen Kalapara,Niranjan J. Sathianathen,Nikolaos Papanikolopoulos,Christopher J. Weight +40 more
TL;DR: The 2019 Kidney and Kidney Tumor Segmentation challenge (KiTS19) as discussed by the authors was a competition held in conjunction with the 2019 International Conference on Medical Image Computing and Computer assisted intervention (MICCAI).
Journal ArticleDOI
An international challenge to use artificial intelligence to define the state-of-the-art in kidney and kidney tumor segmentation in CT imaging.
Nicholas Heller,Sean McSweeney,Matthew Peterson,Sarah H. Peterson,Jack Rickman,Bethany Stai,Resha Tejpaul,Makinna Oestreich,Paul Blake,Joel Rosenberg,Keenan Moore,Edward Walczak,Zachary Rengel,Zach Edgerton,Ranveer Vasdev,Arveen Kalapara,Niranjan J. Sathianathen,Nikolaos Papanikolopoulos,Christopher J. Weight +18 more
TL;DR: This poster presents a probabilistic procedure to estimate the probability that a single cell in the immune system will secrete a substance called “tumor-like substance” during surgery.
Journal ArticleDOI
Retzius-sparing versus standard robotic-assisted laparoscopic prostatectomy for the treatment of clinically localized prostate cancer.
Joel Rosenberg,Jae Hung Jung,Zach Edgerton,Hunju Lee,Solam Lee,Caitlin J Bakker,Philipp Dahm +6 more
TL;DR: To assess the effects of RS-RALP compared to standard RALP for the treatment of clinically localized prostate cancer, a comprehensive search of the Cochrane Library, MEDLINE, Embase, three other databases, trials registries, other sources of the grey literature, and conference proceedings was performed.
Journal ArticleDOI
Public Perceptions of Artificial Intelligence and Robotics in Medicine.
Bethany Stai,Nicholas Heller,Sean McSweeney,Jack Rickman,Paul Blake,Ranveer Vasdev,Zach Edgerton,Resha Tejpaul,Matthew Peterson,Joel Rosenberg,Arveen Kalapara,Subodh Regmi,Nikolaos Papanikolopoulos,Christopher J. Weight +13 more
TL;DR: Most participants express confidence in AI providing medical diagnoses, sometimes even over human physicians, and health care providers should be cognizant of the potential amount of misinformation and sensitivity that patients have to how such technology is represented.