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09/14/2023
RecycleNet: Latent Feature Recycling Leads to Iterative Decision Refinement
Despite the remarkable success of deep learning systems over the last de...
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09/07/2023
Anatomy-informed Data Augmentation for Enhanced Prostate Cancer Detection
Data augmentation (DA) is a key factor in medical image analysis, such a...
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07/05/2023
Exploring new ways: Enforcing representational dissimilarity to learn new features and reduce error consistency
Independently trained machine learning models tend to learn similar feat...
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04/09/2023
Transformer Utilization in Medical Image Segmentation Networks
Owing to success in the data-rich domain of natural images, Transformers...
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03/25/2023
MultiTalent: A Multi-Dataset Approach to Medical Image Segmentation
The medical imaging community generates a wealth of datasets, many of wh...
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03/17/2023
MedNeXt: Transformer-driven Scaling of ConvNets for Medical Image Segmentation
There has been exploding interest in embracing Transformer-based archite...
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01/30/2023
[Work in progress] Scalable, out-of-the box segmentation of individual particles from mineral samples acquired with micro CT
Minerals are indispensable for a functioning modern society. Yet, their ...
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01/05/2023
CRADL: Contrastive Representations for Unsupervised Anomaly Detection and Localization
Unsupervised anomaly detection in medical imaging aims to detect and loc...
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12/03/2022
Precise Energy Consumption Measurements of Heterogeneous Artificial Intelligence Workloads
With the rise of AI in recent years and the increase in complexity of th...
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09/26/2022
Evaluation of Medical Image Segmentation Models for Uncertain, Small or Empty Reference Annotations
Performance metrics for medical image segmentation models are used to me...
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08/23/2022
Extending nnU-Net is all you need
Semantic segmentation is one of the most popular research areas in medic...
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12/16/2021
Classification of diffraction patterns using a convolutional neural network in single particle imaging experiments performed at X-ray free-electron lasers
Single particle imaging (SPI) at X-ray free electron lasers (XFELs) is p...
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06/23/2021
Continuous-Time Deep Glioma Growth Models
The ability to estimate how a tumor might evolve in the future could hav...
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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...
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06/01/2021
nnDetection: A Self-configuring Method for Medical Object Detection
Simultaneous localisation and categorization of objects in medical image...
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04/12/2021
Common Limitations of Image Processing Metrics: A Picture Story
While the importance of automatic image analysis is increasing at an eno...
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03/10/2021
Are we using appropriate segmentation metrics? Identifying correlates of human expert perception for CNN training beyond rolling the DICE coefficient
In this study, we explore quantitative correlates of qualitative human e...
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11/15/2020
Studying Robustness of Semantic Segmentation under Domain Shift in cardiac MRI
Cardiac magnetic resonance imaging (cMRI) is an integral part of diagnos...
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11/02/2020
nnU-Net for Brain Tumor Segmentation
We apply nnU-Net to the segmentation task of the BraTS 2020 challenge. T...
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04/27/2020
OR-UNet: an Optimized Robust Residual U-Net for Instrument Segmentation in Endoscopic Images
Segmentation of endoscopic images is an essential processing step for co...
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03/23/2020
Robust Medical Instrument Segmentation Challenge 2019
Intraoperative tracking of laparoscopic instruments is often a prerequis...
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01/17/2020
CHAOS Challenge – Combined (CT-MR) Healthy Abdominal Organ Segmentation
Segmentation of abdominal organs has been a comprehensive, yet unresolve...
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12/02/2019
The state of the art in kidney and kidney tumor segmentation in contrast-enhanced CT imaging: Results of the KiTS19 Challenge
There is a large body of literature linking anatomic and geometric chara...
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11/26/2019
ModelHub.AI: Dissemination Platform for Deep Learning Models
Recent advances in artificial intelligence research have led to a profus...
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08/06/2019
An attempt at beating the 3D U-Net
The U-Net is arguably the most successful segmentation architecture in t...
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07/09/2019
Deep Probabilistic Modeling of Glioma Growth
Existing approaches to modeling the dynamics of brain tumor growth, spec...
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07/04/2019
Unsupervised Anomaly Localization using Variational Auto-Encoders
An assumption-free automatic check of medical images for potentially ove...
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04/17/2019
nnU-Net: Breaking the Spell on Successful Medical Image Segmentation
Fueled by the diversity of datasets, semantic segmentation is a popular ...
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01/31/2019
Automated brain extraction of multi-sequence MRI using artificial neural networks
Brain extraction is a critical preprocessing step in the analysis of MRI...
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12/14/2018
Context-encoding Variational Autoencoder for Unsupervised Anomaly Detection
Unsupervised learning can leverage large-scale data sources without the ...
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11/21/2018
Retina U-Net: Embarrassingly Simple Exploitation of Segmentation Supervision for Medical Object Detection
The task of localizing and categorizing objects in medical images often ...
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11/05/2018
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge
Gliomas are the most common primary brain malignancies, with different d...
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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...
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09/27/2018
No New-Net
In this paper we demonstrate the effectiveness of a well trained U-Net i...
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02/28/2018
Brain Tumor Segmentation and Radiomics Survival Prediction: Contribution to the BRATS 2017 Challenge
Quantitative analysis of brain tumors is critical for clinical decision ...
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11/27/2017
Exploiting the potential of unlabeled endoscopic video data with self-supervised learning
Purpose: Due to the breakthrough successes of deep learning-based soluti...
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07/03/2017
Automatic Cardiac Disease Assessment on cine-MRI via Time-Series Segmentation and Domain Specific Features
Cardiac magnetic resonance imaging improves on diagnosis of cardiovascul...
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03/06/2017
Direct White Matter Bundle Segmentation using Stacked U-Nets
The state-of-the-art method for automatically segmenting white matter bu...
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11/25/2016
