Edward Walczak

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Common Coauthors
Commonly Cited References
Action Title Year Authors # of times referenced
+ PDF Chat Deep Residual Learning for Image Recognition 2016 Kaiming He
Xiangyu Zhang
Shaoqing Ren
Jian Sun
1
+ PDF Chat Identity Mappings in Deep Residual Networks 2016 Kaiming He
Xiangyu Zhang
Shaoqing Ren
Jian Sun
1
+ V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation 2016 Fausto MilletarĂŹ
Nassir Navab
Seyed‐Ahmad Ahmadi
1
+ PDF Chat A survey on deep learning in medical image analysis 2017 Geert Litjens
Thijs Kooi
Babak Ehteshami Bejnordi
Arnaud Arindra Adiyoso Setio
Francesco Ciompi
Mohsen Ghafoorian
Jeroen van der Laak
Bram van Ginneken
Clara I. Sá‎nchez
1
+ Attention U-Net: Learning Where to Look for the Pancreas 2018 Ozan Oktay
Jo Schlemper
LoĂŻc Le Folgoc
Matthew C. H. Lee
Mattias P. Heinrich‬
Kazunari Misawa
Kensaku Mori
Steven McDonagh
Nils Hammerla
Bernhard Kainz
1
+ Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge 2018 Spyridon Bakas
Mauricio Reyes
Enzo Battistella
Siddhartha Chandra
Huiguang He
Lucas Fidon
Maria Vakalopoulou
Roger Sun
et al.
Éric Deutsch
1
+ PDF Chat Why rankings of biomedical image analysis competitions should be interpreted with care 2018 Lena Maier‐Hein
Matthias Eisenmann
Annika Reinke
Sinan Onogur
Marko Stankovic
Patrick Scholz
Tal Arbel
Hrvoje Bogunović
Andrew P. Bradley
Aaron Carass
1
+ Evaluation of Algorithms for Multi-Modality Whole Heart Segmentation: An Open-Access Grand Challenge 2019 Xiahai Zhuang
Lei Li
Christian Payer
Darko Ĺ tern
Martin Urschler
Mattias P. Heinrich‬
Julien Oster
Chunliang Wang
Örjan Smedby
Cheng Bian
1
+ The KiTS19 Challenge Data: 300 Kidney Tumor Cases with Clinical Context, CT Semantic Segmentations, and Surgical Outcomes 2019 Nicholas Heller
Niranjan Sathianathen
Arveen Kalapara
Edward Walczak
Keenan Moore
Heather Kaluzniak
Joel Rosenberg
Paul Blake
Zachary Rengel
Makinna Oestreich
1
+ nnU-Net: Breaking the Spell on Successful Medical Image Segmentation. 2019 Fabian Isensee
Jens Petersen
Simon Kohl
Paul F. Jäger
Klaus H. Maier‐Hein
1
+ 3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation 2016 Özgün Çiçek
Ahmed Abdulkadir
Soeren S. Lienkamp
Thomas Brox
Olaf Ronneberger
1
+ Semi-Automatic RECIST Labeling on CT Scans with Cascaded Convolutional Neural Networks 2018 Youbao Tang
Adam P. Harrison
Mohammadhadi Bagheri
Jing Xiao
Ronald M. Summers
1
+ PDF Chat Kid-Net: Convolution Networks for Kidney Vessels Segmentation from CT-Volumes 2018 Ahmed Taha
Pechin Lo
Junning Li
Tao Zhao
1
+ PDF Chat H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation From CT Volumes 2018 Xiaomeng Li
Hao Chen
Xiaojuan Qi
Qi Dou
Chi‐Wing Fu
Pheng‐Ann Heng
1
+ An attempt at beating the 3D U-Net 2019 Fabian Isensee
Klaus H. Maier‐Hein
1
+ Evaluation of algorithms for Multi-Modality Whole Heart Segmentation: An open-access grand challenge 2019 Xiahai Zhuang
Lei Li
Christian Payer
Darko Ĺ tern
Martin Urschler
Mattias P. Heinrich‬
Julien Oster
Chunliang Wang
Örjan Smedby
Cheng Bian
1
+ Cascaded Volumetric Convolutional Network for Kidney Tumor Segmentation from CT volumes 2019 Yao Zhang
Yixin Wang
Feng Hou
Jiawei Yang
Guangwei Xiong
Jiang Tian
Cheng Zhong
1
+ PDF Chat The Role of Publicly Available Data in MICCAI Papers from 2014 to 2018 2019 Nicholas Heller
Jack Rickman
Christopher J. Weight
Nikolaos Papanikolopoulos
1
+ PDF Chat nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation 2020 Fabian Isensee
Paul F. Jaeger
Simon Kohl
Jens Petersen
Klaus H. Maier‐Hein
1
+ PDF Chat Methods and open-source toolkit for analyzing and visualizing challenge results 2021 Manuel Wiesenfarth
Annika Reinke
Bennett A. Landman
Matthias Eisenmann
Laura Aguilera Saiz
M. Jorge Cardoso
Lena Maier‐Hein
Annette Kopp‐Schneider
1
+ Understanding deep learning requires rethinking generalization 2016 Chiyuan Zhang
Samy Bengio
Moritz Hardt
Benjamin Recht
Oriol Vinyals
1
+ Methods and open-source toolkit for analyzing and visualizing challenge results 2019 Manuel Wiesenfarth
Annika Reinke
Bennett A. Landman
M. Jorge Cardoso
Klaus H. Maier‐Hein
Annette Kopp‐Schneider
1
+ nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation 2018 Fabian Isensee
Jens Petersen
AndrĂŠ Klein
David Zimmerer
Paul F. Jaeger
Simon Kohl
Jakob Wasserthal
Gregor Koehler
Tobias Norajitra
Sebastian Wirkert
1
+ The Liver Tumor Segmentation Benchmark (LiTS) 2019 Patrick Bilic
Patrick Ferdinand Christ
Hongwei Li
Eugene Vorontsov
Avi Ben-Cohen
Georgios Kaissis
Adi Szeskin
Colin Jacobs
Gabriel Efrain Humpire Mamani
Gabriel Chartrand
1