Search Results for author: Weilin Fu

Found 7 papers, 0 papers with code

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

no code implementations19 Dec 2019 Siming Bayer, Xia Zhong, Weilin Fu, Nishant Ravikumar, Andreas Maier

In this work, we propose an imitation learning framework for the registration of 2D color funduscopic images for a wide range of applications such as disease monitoring, image stitching and super-resolution.

Image Registration Image Stitching +2

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

no code implementations6 Nov 2019 Weilin Fu, Katharina Breininger, Zhaoya Pan, Andreas Maier

Results show that for retinal vessel segmentation on DRIVE database, U-Net does not degenerate until surprisingly acute conditions: one level, one filter in convolutional layers, and one training sample.

Retinal Vessel Segmentation Segmentation

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

no code implementations5 Nov 2019 Weilin Fu, Lennart Husvogt, Stefan Ploner James G. Fujimoto Andreas Maier

Statistics of the grades by the experts indicate that the transferred module improves both the image quality and the diagnostic quality.

Retinal Vessel Segmentation Transfer Learning

A Divide-and-Conquer Approach towards Understanding Deep Networks

no code implementations14 Jul 2019 Weilin Fu, Katharina Breininger, Roman Schaffert, Nishant Ravikumar, Andreas Maier

We start with a high-performance U-Net and show by step-by-step conversion that we are able to divide the network into modules of known operators.

Image Segmentation Retinal Vessel Segmentation +1

Learning with Known Operators reduces Maximum Training Error Bounds

no code implementations3 Jul 2019 Andreas K. Maier, Christopher Syben, Bernhard Stimpel, Tobias Würfl, Mathis Hoffmann, Frank Schebesch, Weilin Fu, Leonid Mill, Lasse Kling, Silke Christiansen

We assume that our analysis will support further investigation of known operators in other fields of physics, imaging, and signal processing.

Image Reconstruction

Frangi-Net: A Neural Network Approach to Vessel Segmentation

no code implementations9 Nov 2017 Weilin Fu, Katharina Breininger, Tobias Würfl, Nishant Ravikumar, Roman Schaffert, Andreas Maier

In this paper, we reformulate the conventional 2-D Frangi vesselness measure into a pre-weighted neural network ("Frangi-Net"), and illustrate that the Frangi-Net is equivalent to the original Frangi filter.

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