David G. Ellis

According to our database, David G. Ellis authored at least 10 papers between 2014 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Towards clinical applicability and computational efficiency in automatic cranial implant design: An overview of the AutoImplant 2021 cranial implant design challenge.

Jianning Li, David G. Ellis, Oldrich Kodym, Laurèl Rauschenbach, Christoph Rieß, Ulrich Sure, Karsten H. Wrede, Carlos M. Alvarez, Marek Wodzinski, Mateusz Daniol, Daria Hemmerling, Hamza Mahdi, Allison Clement, Evan Kim, Zachary Fishman, Cari M. Whyne, James G. Mainprize, Michael R. Hardisty, Shashwat Pathak, Chitimireddy Sindhura, Rama Krishna Sai S. Gorthi, Degala Venkata Kiran, Subrahmanyam Gorthi, Bokai Yang, Ke Fang, Xingyu Li, Artem Kroviakov, Lei Yu, Yuan Jin, Antonio Pepe, Christina Gsaxner, Adam Herout, Victor Alves, Michal Spanel, Michele R. Aizenberg, Jens Kleesiek, Jan Egger

Medical Image Anal., August, 2023

MedShapeNet - A Large-Scale Dataset of 3D Medical Shapes for Computer Vision.

Jianning Li, Antonio Pepe, Christina Gsaxner, Gijs Luijten, Yuan Jin, Narmada Ambigapathy, Enrico Nasca, Naida Solak, Gian Marco Melito, Afaque R. Memon, Xiaojun Chen, Jan Stefan Kirschke, Ezequiel de la Rosa, Patrick Ferdinand Christ, Hongwei Bran Li, David G. Ellis, Michele R. Aizenberg, Sergios Gatidis, Thomas Küstner, Nadya Shusharina, Nicholas Heller, Vincent Andrearczyk, Adrien Depeursinge, Mathieu Hatt, Anjany Sekuboyina, Maximilian Löffler, Hans Liebl, Reuben Dorent, Tom Vercauteren, Jonathan Shapey, Aaron Kujawa, Stefan Cornelissen, Patrick Langenhuizen, Achraf Ben-Hamadou, Ahmed Rekik, Sergi Pujades, Edmond Boyer, Federico Bolelli, Costantino Grana, Luca Lumetti, Hamidreza Salehi, Jun Ma, Yao Zhang, Ramtin Gharleghi, Susann Beier, Arcot Sowmya, Eduardo A. Garza-Villarreal, Thania Balducci, et al.

CoRR, 2023

Why is the winner the best?

Matthias Eisenmann, Annika Reinke, Vivienn Weru, Minu Dietlinde Tizabi, Fabian Isensee, Tim J. Adler, Sharib Ali, Vincent Andrearczyk, Marc Aubreville, Ujjwal Baid, Spyridon Bakas, Niranjan Balu, Sophia Bano, Jorge Bernal, Sebastian Bodenstedt, Alessandro Casella, Veronika Cheplygina, Marie Daum, Marleen de Bruijne, Adrien Depeursinge, Reuben Dorent, Jan Egger, David G. Ellis, Sandy Engelhardt, Melanie Ganz, Noha M. Ghatwary, Gabriel Girard, Patrick Godau, Anubha Gupta, Lasse Hansen, Kanako Harada, Mattias P. Heinrich, Nicholas Heller, Alessa Hering, Arnaud Huaulmé, Pierre Jannin, Ali Emre Kavur, Oldrich Kodym, Michal Kozubek, Jianning Li, Hongwei Bran Li, Jun Ma, Carlos Martín-Isla, Bjoern H. Menze, J. Alison Noble, Valentin Oreiller, Nicolas Padoy, Sarthak Pati, Kelly Payette, Tim Rädsch, et al.

CoRR, 2023

Why is the Winner the Best?

Matthias Eisenmann, Annika Reinke, Vivienn Weru, Minu Dietlinde Tizabi, Fabian Isensee, Tim J. Adler, Sharib Ali, Vincent Andrearczyk, Marc Aubreville, Ujjwal Baid, Spyridon Bakas, Niranjan Balu, Sophia Bano, Jorge Bernal, Sebastian Bodenstedt, Alessandro Casella, Veronika Cheplygina, Marie Daum, Marleen de Bruijne, Adrien Depeursinge, Reuben Dorent, Jan Egger, David G. Ellis, Sandy Engelhardt, Melanie Ganz, Noha M. Ghatwary, Gabriel Girard, Patrick Godau, Anubha Gupta, Lasse Hansen, Kanako Harada, Mattias P. Heinrich, Nicholas Heller, Alessa Hering, Arnaud Huaulmé, Pierre Jannin, A. Emre Kavur, Oldrich Kodym, Michal Kozubek, Jianning Li, Hongwei Bran Li, Jun Ma, Carlos Martín-Isla, Bjoern H. Menze, J. Alison Noble, Valentin Oreiller, Nicolas Padoy, Sarthak Pati, Kelly Payette, Tim Rädsch, Jonathan Rafael-Patino, Vivek Singh Bawa, Stefanie Speidel, Carole H. Sudre, Kimberlin M. H. van Wijnen, Martin Wagner, D. Wei, Amine Yamlahi, Moi Hoon Yap, C. Yuan, Maximilian Zenk, A. Zia, David Zimmerer, Dogu Baran Aydogan, Binod Bhattarai, Louise Bloch, Raphael Brüngel, J. Cho, C. Choi, Q. Dou, Ivan Ezhov, Christoph M. Friedrich, C. Fuller, Rebati Raman Gaire, Adrian Galdran, Álvaro García-Faura, Maria Grammatikopoulou, S. Hong, Mostafa Jahanifar, I. Jang, Abdolrahim Kadkhodamohammadi, I. Kang, Florian Kofler, S. Kondo, Hugo Jaco Kuijf, M. Li, M. Luu, Tomaz Martincic, Pedro Morais, Mohamed A. Naser, Bruno Oliveira, David Owen, S. Pang, J. Park, S. Park, Szymon Plotka, Élodie Puybareau, Nasir M. Rajpoot, K. Ryu, Numan Saeed, Adam Shephard, Pengcheng Shi, Dejan Stepec, Ronast Subedi, Guillaume Tochon, Helena R. Torres, Hélène Urien, João L. Vilaça, Kareem A. Wahid, H. Wang, J. Wang, L. Wang, X. Wang, Benedikt Wiestler, Marek Wodzinski, F. Xia, J. Xie, Z. Xiong, S. Yang, Y. Yang, Z. Zhao, Klaus H. Maier-Hein, Paul F. Jäger, Annette Kopp-Schneider, Lena Maier-Hein

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Back to the Roots: Reconstructing Large and Complex Cranial Defects using an Image-based Statistical Shape Model.

Jianning Li, David G. Ellis, Antonio Pepe, Christina Gsaxner, Michele R. Aizenberg, Jens Kleesiek, Jan Egger

CoRR, 2022

2021

AutoImplant 2020-First MICCAI Challenge on Automatic Cranial Implant Design.

Jianning Li, Pedro Pimentel, Angelika Szengel, Moritz Ehlke, Hans Lamecker, Stefan Zachow, Laura Jovani Estacio Cerquin, Christian Doenitz, Heiko Ramm, Haochen Shi, Xiaojun Chen, Franco Matzkin, Virginia F. J. Newcombe, Enzo Ferrante, Yuan Jin, David G. Ellis, Michele R. Aizenberg, Oldrich Kodym, Michal Spanel, Adam Herout, James G. Mainprize, Zachary Fishman, Michael R. Hardisty, Amirhossein Bayat, Suprosanna Shit, Bomin Wang, Zhi Liu, Matthias Eder, Antonio Pepe, Christina Gsaxner, Victor Alves, Ulrike Zefferer, Gord von Campe, Karin Pistracher, Ute Schäfer, Dieter Schmalstieg, Bjoern H. Menze, Ben Glocker, Jan Egger

IEEE Trans. Medical Imaging, 2021

Qualitative Criteria for Feasible Cranial Implant Designs.

David G. Ellis, Carlos M. Alvarez, Michele R. Aizenberg

Proceedings of the Towards the Automatization of Cranial Implant Design in Cranioplasty II, 2021

2020

Deep Learning Using Augmentation via Registration: 1st Place Solution to the AutoImplant 2020 Challenge.

David G. Ellis, Michele R. Aizenberg

Proceedings of the Towards the Automatization of Cranial Implant Design in Cranioplasty, 2020

Trialing U-Net Training Modifications for Segmenting Gliomas Using Open Source Deep Learning Framework.

David G. Ellis, Michele R. Aizenberg

Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2020

2014

A reusable BIST with software assisted repair technology for improved memory and IO debug, validation and test time.

Bruce Querbach, Rahul Khanna, David Blankenbeckler, Yulan Zhang, Ronald T. Anderson, David G. Ellis, Zale T. Schoenborn, Sabyasachi Deyati, Patrick Chiang

Proceedings of the 2014 International Test Conference, 2014