Search Results for author: Olaf Ronneberger

Found 11 papers, 7 papers with code

A Hierarchical Probabilistic U-Net for Modeling Multi-Scale Ambiguities

3 code implementations30 May 2019 Simon A. A. Kohl, Bernardino Romera-Paredes, Klaus H. Maier-Hein, Danilo Jimenez Rezende, S. M. Ali Eslami, Pushmeet Kohli, Andrew Zisserman, Olaf Ronneberger

Medical imaging only indirectly measures the molecular identity of the tissue within each voxel, which often produces only ambiguous image evidence for target measures of interest, like semantic segmentation.

Instance Segmentation Medical Image Segmentation +1

A Probabilistic U-Net for Segmentation of Ambiguous Images

7 code implementations NeurIPS 2018 Simon A. A. Kohl, Bernardino Romera-Paredes, Clemens Meyer, Jeffrey De Fauw, Joseph R. Ledsam, Klaus H. Maier-Hein, S. M. Ali Eslami, Danilo Jimenez Rezende, Olaf Ronneberger

To this end we propose a generative segmentation model based on a combination of a U-Net with a conditional variational autoencoder that is capable of efficiently producing an unlimited number of plausible hypotheses.

Decision Making Semantic Segmentation

3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation

16 code implementations21 Jun 2016 Özgün Çiçek, Ahmed Abdulkadir, Soeren S. Lienkamp, Thomas Brox, Olaf Ronneberger

This paper introduces a network for volumetric segmentation that learns from sparsely annotated volumetric images.

Ranked #34 on 3D Part Segmentation on ShapeNet-Part (Instance Average IoU metric)

Data Augmentation

U-Net: Convolutional Networks for Biomedical Image Segmentation

373 code implementations18 May 2015 Olaf Ronneberger, Philipp Fischer, Thomas Brox

There is large consent that successful training of deep networks requires many thousand annotated training samples.

Cell Segmentation Colorectal Gland Segmentation: +8

Cannot find the paper you are looking for? You can Submit a new open access paper.