b'Jens Petersen'

research

∙ 08/16/2023

Prediction of post-radiotherapy recurrence volumes in head and neck squamous cell carcinoma using 3D U-Net segmentation

Locoregional recurrences (LRR) are still a frequent site of treatment fa...

0 Denis Kutnar, et al. ∙

research

∙ 04/10/2023

Localise to segment: crop to improve organ at risk segmentation accuracy

Increased organ at risk segmentation accuracy is required to reduce cost...

0 Abraham George Smith, et al. ∙

research

∙ 04/09/2023

Transformer Utilization in Medical Image Segmentation Networks

Owing to success in the data-rich domain of natural images, Transformers...

0 Saikat Roy, et al. ∙

research

∙ 03/17/2023

MedNeXt: Transformer-driven Scaling of ConvNets for Medical Image Segmentation

There has been exploding interest in embracing Transformer-based archite...

0 Saikat Roy, et al. ∙

research

∙ 01/13/2023

Neural Image Compression with a Diffusion-Based Decoder

Diffusion probabilistic models have recently achieved remarkable success...

4 Noor Fathima Goose, et al. ∙

research

∙ 01/13/2023

Explicit Temporal Embedding in Deep Generative Latent Models for Longitudinal Medical Image Synthesis

Medical imaging plays a vital role in modern diagnostics and treatment. ...

0 Julian Schön, et al. ∙

research

∙ 01/05/2023

CRADL: Contrastive Representations for Unsupervised Anomaly Detection and Localization

Unsupervised anomaly detection in medical imaging aims to detect and loc...

0 Carsten T. Lüth, et al. ∙

research

∙ 07/20/2022

Interpreting Latent Spaces of Generative Models for Medical Images using Unsupervised Methods

Generative models such as Generative Adversarial Networks (GANs) and Var...

0 Julian Schön, et al. ∙

research

∙ 09/15/2021

Patch-based medical image segmentation using Quantum Tensor Networks

Tensor networks are efficient factorisations of high dimensional tensors...

9 Raghavendra Selvan, et al. ∙

research

∙ 06/23/2021

Continuous-Time Deep Glioma Growth Models

The ability to estimate how a tumor might evolve in the future could hav...

0 Jens Petersen, et al. ∙

research

∙ 06/22/2021

RootPainter3D: Interactive-machine-learning enables rapid and accurate contouring for radiotherapy

Organ-at-risk contouring is still a bottleneck in radiotherapy, with man...

0 Abraham George Smith, et al. ∙

research

∙ 06/09/2021

GP-ConvCNP: Better Generalization for Convolutional Conditional Neural Processes on Time Series Data

Neural Processes (NPs) are a family of conditional generative models tha...

0 Jens Petersen, et al. ∙

research

∙ 04/12/2021

Common Limitations of Image Processing Metrics: A Picture Story

While the importance of automatic image analysis is increasing at an eno...

6 Annika Reinke, et al. ∙

research

∙ 02/13/2021

Segmenting two-dimensional structures with strided tensor networks

Tensor networks provide an efficient approximation of operations involvi...

0 Raghavendra Selvan, et al. ∙

research

∙ 11/28/2019

A Case for the Score: Identifying Image Anomalies using Variational Autoencoder Gradients

Through training on unlabeled data, anomaly detection has the potential ...

0 David Zimmerer, et al. ∙

research

∙ 11/27/2019

High- and Low-level image component decomposition using VAEs for improved reconstruction and anomaly detection

Variational Auto-Encoders have often been used for unsupervised pretrain...

14 David Zimmerer, et al. ∙

research

∙ 07/09/2019

Deep Probabilistic Modeling of Glioma Growth

Existing approaches to modeling the dynamics of brain tumor growth, spec...

1 Jens Petersen, et al. ∙

research

∙ 07/04/2019

Unsupervised Anomaly Localization using Variational Auto-Encoders

An assumption-free automatic check of medical images for potentially ove...

0 David Zimmerer, et al. ∙

research

∙ 04/17/2019

nnU-Net: Breaking the Spell on Successful Medical Image Segmentation

Fueled by the diversity of datasets, semantic segmentation is a popular ...

0 Fabian Isensee, et al. ∙

research

∙ 03/11/2019

A cross-center smoothness prior for variational Bayesian brain tissue segmentation

Suppose one is faced with the challenge of tissue segmentation in MR ima...

0 Wouter M. Kouw, et al. ∙

research

∙ 02/28/2019

Segmentation of Roots in Soil with U-Net

Plant root research can provide a way to attain stress-tolerant crops th...

0 Abraham George Smith, et al. ∙

research

∙ 12/14/2018

Context-encoding Variational Autoencoder for Unsupervised Anomaly Detection

Unsupervised learning can leverage large-scale data sources without the ...

0 David Zimmerer, et al. ∙

research

∙ 11/21/2018

Graph Refinement based Tree Extraction using Mean-Field Networks and Graph Neural Networks

Graph refinement, or the task of obtaining subgraphs of interest from ov...

10 Raghavendra Selvan, et al. ∙

research

∙ 10/17/2018

Learning to quantify emphysema extent: What labels do we need?

Accurate assessment of pulmonary emphysema is crucial to assess disease ...

0 Silas Nyboe Ørting, et al. ∙

research

∙ 09/27/2018

nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation

The U-Net was presented in 2015. With its straight-forward and successfu...

0 Fabian Isensee, et al. ∙

research

∙ 06/23/2018

Extracting Tree-structures in CT data by Tracking Multiple Statistically Ranked Hypotheses

In this work, we adapt a method based on multiple hypothesis tracking (M...

2 Raghavendra Selvan, et al. ∙

research

∙ 06/19/2018

Feature learning based on visual similarity triplets in medical image analysis: A case study of emphysema in chest CT scans

Supervised feature learning using convolutional neural networks (CNNs) c...

12 Silas Nyboe Ørting, et al. ∙

research

∙ 04/12/2018

Extraction of Airways using Graph Neural Networks

We present extraction of tree structures, such as airways, from image da...

0 Raghavendra Selvan, et al. ∙

research

∙ 04/10/2018

Mean Field Network based Graph Refinement with application to Airway Tree Extraction

We present tree extraction in 3D images as a graph refinement task, of o...

0 Raghavendra Selvan, et al. ∙

research

∙ 08/07/2017

Extraction of Airways with Probabilistic State-space Models and Bayesian Smoothing

Segmenting tree structures is common in several image processing applica...

0 Raghavendra Selvan, et al. ∙

research

∙ 11/24/2016

Extraction of airway trees using multiple hypothesis tracking and template matching

Knowledge of airway tree morphology has important clinical applications ...

0 Raghavendra Selvan, et al. ∙

research

∙ 03/29/2013

Geometric tree kernels: Classification of COPD from airway tree geometry

Methodological contributions: This paper introduces a family of kernels ...

0 Aasa Feragen, et al. ∙

Jens Petersen

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