Weilin Fu

According to our database, Weilin Fu authored at least 16 papers between 2017 and 2022.

Collaborative distances:

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

2022

Form Follows Function - Smart Network Design Enables Zero-shot Network Reuse.

Weilin Fu, Lennart Husvogt, Katharina Breininger, Roman Schaffert, Omar Abu-Qamar, James G. Fujimoto, Andreas K. Maier

Proceedings of the Bildverarbeitung für die Medizin 2022, 2022

2021

"Keep it simple, scholar": an experimental analysis of few-parameter segmentation networks for retinal vessels in fundus imaging.

Weilin Fu, Katharina Breininger, Roman Schaffert, Zhaoya Pan, Andreas K. Maier

Int. J. Comput. Assist. Radiol. Surg., 2021

Novel Evaluation Metrics for Vascular Structure Segmentation.

Marcel Reimann, Weilin Fu, Andreas Maier

Proceedings of the Bildverarbeitung für die Medizin 2021, 2021

Towards Mouse Bone X-ray Microscopy Scan Simulation.

Weilin Fu, Leonid Mill, Stephan Seitz, Tobias Geimer, Lasse Kling, Dennis Possart, Silke H. Christiansen, Andreas Maier

Proceedings of the Bildverarbeitung für die Medizin 2021, 2021

2020

Modularization of Deep Networks Allows Cross-Modality Reuse.

Weilin Fu, Lennart Husvogt, Stefan B. Ploner, James G. Fujimoto, Andreas K. Maier

Proceedings of the Bildverarbeitung für die Medizin 2020 - Algorithmen - Systeme, 2020

Abstract: Divide-And-Conquer Approach Towards Understanding Deep Networks.

Weilin Fu, Katharina Breininger, Roman Schaffert, Nishant Ravikumar, Andreas K. Maier

Proceedings of the Bildverarbeitung für die Medizin 2020 - Algorithmen - Systeme, 2020

Degenerating U-Net on Retinal Vessel Segmentation.

Weilin Fu, Katharina Breininger, Zhaoya Pan, Andreas K. Maier

Proceedings of the Bildverarbeitung für die Medizin 2020 - Algorithmen - Systeme, 2020

Imitation Learning Network for Fundus Image Registration Using a Divide-And-Conquer Approach.

Siming Bayer, Xia Zhong, Weilin Fu, Nishant Ravikumar, Andreas K. Maier

Proceedings of the Bildverarbeitung für die Medizin 2020 - Algorithmen - Systeme, 2020

2019

Learning with known operators reduces maximum error bounds.

Andreas K. Maier, Christopher Syben, Bernhard Stimpel, Tobias Würfl, Mathis Hoffmann, Frank Schebesch, Weilin Fu, Leonid Mill, Lasse Kling, Silke H. Christiansen

Nat. Mach. Intell., 2019

Analyzing an Imitation Learning Network for Fundus Image Registration Using a Divide-and-Conquer Approach.

Siming Bayer, Xia Zhong, Weilin Fu, Nishant Ravikumar, Andreas Maier

CoRR, 2019

What Do We Really Need? Degenerating U-Net on Retinal Vessel Segmentation.

Weilin Fu, Katharina Breininger, Zhaoya Pan, Andreas K. Maier

CoRR, 2019

Lesson Learnt: Modularization of Deep Networks Allow Cross-Modality Reuse.

Weilin Fu, Lennart Husvogt, Stefan B. Ploner, James G. Fujimoto, Andreas K. Maier

CoRR, 2019

Learning with Known Operators reduces Maximum Training Error Bounds.

Andreas K. Maier, Christopher Syben, Bernhard Stimpel, Tobias Würfl, Mathis Hoffmann, Frank Schebesch, Weilin Fu, Leonid Mill, Lasse Kling, Silke H. Christiansen

CoRR, 2019

A Divide-and-Conquer Approach Towards Understanding Deep Networks.

Weilin Fu, Katharina Breininger, Roman Schaffert, Nishant Ravikumar, Andreas K. Maier

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

2018

Frangi-Net.

Weilin Fu, Katharina Breininger, Roman Schaffert, Nishant Ravikumar, Tobias Würfl, Jim Fujimoto, Eric Moult, Andreas K. Maier

Proceedings of the Bildverarbeitung für die Medizin 2018 - Algorithmen - Systeme, 2018

2017

Frangi-Net: A Neural Network Approach to Vessel Segmentation.

Weilin Fu, Katharina Breininger, Tobias Würfl, Nishant Ravikumar, Roman Schaffert, Andreas K. Maier

CoRR, 2017