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09/06/2023
M3D-NCA: Robust 3D Segmentation with Built-in Quality Control
Medical image segmentation relies heavily on large-scale deep learning m...
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09/01/2023
Jointly Exploring Client Drift and Catastrophic Forgetting in Dynamic Learning
Federated and Continual Learning have emerged as potential paradigms for...
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08/03/2023
Synthesising Rare Cataract Surgery Samples with Guided Diffusion Models
Cataract surgery is a frequently performed procedure that demands automa...
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05/21/2023
CoSINT: Designing a Collaborative Capture the Flag Competition to Investigate Misinformation
Crowdsourced investigations shore up democratic institutions by debunkin...
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02/07/2023
Med-NCA: Robust and Lightweight Segmentation with Neural Cellular Automata
Access to the proper infrastructure is critical when performing medical ...
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09/29/2022
Federated Stain Normalization for Computational Pathology
Although deep federated learning has received much attention in recent y...
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09/20/2022
Detecting respiratory motion artefacts for cardiovascular MRIs to ensure high-quality segmentation
While machine learning approaches perform well on their training domain,...
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08/05/2022
Distance-based detection of out-of-distribution silent failures for Covid-19 lung lesion segmentation
Automatic segmentation of ground glass opacities and consolidations in c...
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08/05/2022
Task-agnostic Continual Hippocampus Segmentation for Smooth Population Shifts
Most continual learning methods are validated in settings where task bou...
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08/01/2022
FrOoDo: Framework for Out-of-Distribution Detection
FrOoDo is an easy-to-use and flexible framework for Out-of-Distribution ...
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04/17/2022
Continual Hippocampus Segmentation with Transformers
In clinical settings, where acquisition conditions and patient populatio...
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01/26/2022
Improving robustness and calibration in ensembles with diversity regularization
Calibration and uncertainty estimation are crucial topics in high-risk e...
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01/14/2022
Disentanglement enables cross-domain Hippocampus Segmentation
Limited amount of labelled training data are a common problem in medical...
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12/16/2021
Quality monitoring of federated Covid-19 lesion segmentation
Federated Learning is the most promising way to train robust Deep Learni...
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09/03/2021
How Reliable Are Out-of-Distribution Generalization Methods for Medical Image Segmentation?
The recent achievements of Deep Learning rely on the test data being sim...
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07/19/2021
Adversarial Continual Learning for Multi-Domain Hippocampal Segmentation
Deep learning for medical imaging suffers from temporal and privacy-rela...
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07/13/2021
Detecting when pre-trained nnU-Net models fail silently for Covid-19 lung lesion segmentation
Automatic segmentation of lung lesions in computer tomography has the po...
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03/02/2021
Simulation-to-Real domain adaptation with teacher-student learning for endoscopic instrument segmentation
Purpose: Segmentation of surgical instruments in endoscopic videos is es...
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01/19/2021
A survey on shape-constraint deep learning for medical image segmentation
Since the advent of U-Net, fully convolutional deep neural networks and ...
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01/05/2021
CycleGAN for Interpretable Online EMT Compensation
Purpose: Electromagnetic Tracking (EMT) can partially replace X-ray guid...
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12/05/2020
Understanding Interpretability by generalized distillation in Supervised Classification
The ability to interpret decisions taken by Machine Learning (ML) models...
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12/04/2020
Super-Selfish: Self-Supervised Learning on Images with PyTorch
Super-Selfish is an easy to use PyTorch framework for image-based self-s...
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10/21/2020
What is Wrong with Continual Learning in Medical Image Segmentation?
Continual learning protocols are attracting increasing attention from th...
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08/18/2020
EXCLUVIS: A MATLAB GUI Software for Comparative Study of Clustering and Visualization of Gene Expression Data
Clustering is a popular data mining technique that aims to partition an ...
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07/22/2020
Endo-Sim2Real: Consistency learning-based domain adaptation for instrument segmentation
Surgical tool segmentation in endoscopic videos is an important componen...
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07/01/2020
M3d-CAM: A PyTorch library to generate 3D data attention maps for medical deep learning
M3d-CAM is an easy to use library for generating attention maps of CNN-b...
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06/26/2020
AutoSNAP: Automatically Learning Neural Architectures for Instrument Pose Estimation
Despite recent successes, the advances in Deep Learning have not yet bee...
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09/13/2018
GANs for Medical Image Analysis
Generative Adversarial Networks (GANs) and their extensions have carved ...
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09/12/2018
Deep Spectral Correspondence for Matching Disparate Image Pairs
A novel, non-learning-based, saliency-aware, shape-cognizant corresponde...
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06/26/2018
A Theory of Diagnostic Interpretation in Supervised Classification
Interpretable deep learning is a fundamental building block towards safe...
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06/25/2018
Exploring Adversarial Examples: Patterns of One-Pixel Attacks
Failure cases of black-box deep learning, e.g. adversarial examples, mig...
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06/20/2018
How Bad is Good enough: Noisy annotations for instrument pose estimation
Though analysis of Medical Images by Deep Learning achieves unprecedente...
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02/26/2018
i3PosNet: Instrument Pose Estimation from X-Ray
Performing delicate Minimally Invasive Surgeries (MIS) forces surgeons t...
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02/21/2018
Planning Nonlinear Access Paths for Temporal Bone Surgery
Purpose: Interventions at the otobasis operate in the narrow region of t...
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08/31/2017
Quality Enhancement by Weighted Rank Aggregation of Crowd Opinion
Expertise of annotators has a major role in crowdsourcing based opinion ...
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10/27/2016
Tool and Phase recognition using contextual CNN features
A transfer learning method for generating features suitable for surgical...
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09/28/2013