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07/27/2023
Generative AI for Medical Imaging: extending the MONAI Framework
Recent advances in generative AI have brought incredible breakthroughs i...
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07/11/2023
A Causal Ordering Prior for Unsupervised Representation Learning
Unsupervised representation learning with variational inference relies h...
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06/13/2023
Compositionally Equivariant Representation Learning
Deep learning models often need sufficient supervision (i.e. labelled da...
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06/02/2023
Privacy Distillation: Reducing Re-identification Risk of Multimodal Diffusion Models
Knowledge distillation in neural networks refers to compressing a large ...
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05/14/2023
Parameter-Efficient Fine-Tuning for Medical Image Analysis: The Missed Opportunity
We present a comprehensive evaluation of Parameter-Efficient Fine-Tuning...
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01/19/2023
The role of noise in denoising models for anomaly detection in medical images
Pathological brain lesions exhibit diverse appearance in brain images, i...
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11/15/2022
Clinically Plausible Pathology-Anatomy Disentanglement in Patient Brain MRI with Structured Variational Priors
We propose a hierarchically structured variational inference model for a...
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10/31/2022
Rethinking Generalization: The Impact of Annotation Style on Medical Image Segmentation
Generalization is an important attribute of machine learning models, par...
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10/12/2022
Diffusion Models for Causal Discovery via Topological Ordering
Discovering causal relations from observational data becomes possible wi...
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08/06/2022
HSIC-InfoGAN: Learning Unsupervised Disentangled Representations by Maximising Approximated Mutual Information
Learning disentangled representations requires either supervision or the...
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07/25/2022
What is Healthy? Generative Counterfactual Diffusion for Lesion Localization
Reducing the requirement for densely annotated masks in medical image se...
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06/29/2022
Why patient data cannot be easily forgotten?
Rights provisioned within data protection regulations, permit patients t...
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06/29/2022
vMFNet: Compositionality Meets Domain-generalised Segmentation
Training medical image segmentation models usually requires a large amou...
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05/23/2022
Causal Machine Learning for Healthcare and Precision Medicine
Causal machine learning (CML) has experienced increasing popularity in h...
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05/20/2022
Unintended memorisation of unique features in neural networks
Neural networks pose a privacy risk due to their propensity to memorise ...
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03/15/2022
Adversarial Counterfactual Augmentation: Application in Alzheimer's Disease Classification
Data augmentation has been widely used in deep learning to reduce over-f...
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02/21/2022
Diffusion Causal Models for Counterfactual Estimation
We consider the task of counterfactual estimation from observational ima...
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02/16/2022
Measuring Unintended Memorisation of Unique Private Features in Neural Networks
Neural networks pose a privacy risk to training data due to their propen...
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02/12/2022
Indication as Prior Knowledge for Multimodal Disease Classification in Chest Radiographs with Transformers
When a clinician refers a patient for an imaging exam, they include the ...
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01/10/2022
MyoPS: A Benchmark of Myocardial Pathology Segmentation Combining Three-Sequence Cardiac Magnetic Resonance Images
Assessment of myocardial viability is essential in diagnosis and treatme...
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08/26/2021
A Tutorial on Learning Disentangled Representations in the Imaging Domain
Disentangled representation learning has been proposed as an approach to...
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08/26/2021
Re-using Adversarial Mask Discriminators for Test-time Training under Distribution Shifts
Thanks to their ability to learn flexible data-driven losses, Generative...
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08/26/2021
Stop Throwing Away Discriminators! Re-using Adversaries for Test-Time Training
Thanks to their ability to learn data distributions without requiring pa...
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08/26/2021
Self-supervised Multi-scale Consistency for Weakly Supervised Segmentation Learning
Collecting large-scale medical datasets with fine-grained annotations is...
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07/04/2021
Controllable cardiac synthesis via disentangled anatomy arithmetic
Acquiring annotated data at scale with rare diseases or conditions remai...
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07/04/2021
Survey: Leakage and Privacy at Inference Time
Leakage of data from publicly available Machine Learning (ML) models is ...
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06/24/2021
Semi-supervised Meta-learning with Disentanglement for Domain-generalised Medical Image Segmentation
Generalising deep models to new data from new centres (termed here domai...
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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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09/05/2020
Max-Fusion U-Net for Multi-Modal Pathology Segmentation with Attention and Dynamic Resampling
Automatic segmentation of multi-sequence (multi-modal) cardiac MR (CMR) ...
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09/05/2020
Semi-supervised Pathology Segmentation with Disentangled Representations
Automated pathology segmentation remains a valuable diagnostic tool in c...
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08/27/2020
Metrics for Exposing the Biases of Content-Style Disentanglement
Recent state-of-the-art semi- and un-supervised solutions for challengin...
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08/26/2020
Disentangled Representations for Domain-generalized Cardiac Segmentation
Robust cardiac image segmentation is still an open challenge due to the ...
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08/21/2020
INSIDE: Steering Spatial Attention with Non-Imaging Information in CNNs
We consider the problem of integrating non-imaging information into segm...
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07/02/2020
Weakly Supervised Segmentation with Multi-scale Adversarial Attention Gates
Large, fine-grained image segmentation datasets, annotated at pixel-leve...
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04/21/2020
Have you forgotten? A method to assess if machine learning models have forgotten data
In the era of deep learning, aggregation of data from several sources is...
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03/17/2020
Teacher-Student chain for efficient semi-supervised histology image classification
Deep learning shows great potential for the domain of digital pathology....
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12/05/2019
Blind Inpainting of Large-scale Masks of Thin Structures with Adversarial and Reinforcement Learning
Several imaging applications (vessels, retina, plant roots, road network...
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12/04/2019
Learning to synthesise the ageing brain without longitudinal data
Brain ageing is a continuous process that is affected by many factors in...
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11/11/2019
Disentangle, align and fuse for multimodal and zero-shot image segmentation
Magnetic resonance (MR) protocols rely on several sequences to properly ...
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08/29/2019
Temporal Consistency Objectives Regularize the Learning of Disentangled Representations
There has been an increasing focus in learning interpretable feature rep...
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07/11/2019
FIRE: Unsupervised bi-directional inter-modality registration using deep networks
Inter-modality image registration is an critical preprocessing step for ...
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03/22/2019
Factorised Representation Learning in Cardiac Image Analysis
Typically, a medical image offers spatial information on the anatomy (an...
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02/22/2019
The Generalized Complex Kernel Least-Mean-Square Algorithm
We propose a novel adaptive kernel based regression method for complex-v...
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01/10/2019
Adversarial Pseudo Healthy Synthesis Needs Pathology Factorization
Pseudo healthy synthesis, i.e. the creation of a subject-specific `healt...
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03/19/2018
Factorised spatial representation learning: application in semi-supervised myocardial segmentation
The success and generalisation of deep learning algorithms heavily depen...
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09/05/2017
Leveraging multiple datasets for deep leaf counting
The number of leaves a plant has is one of the key traits (phenotypes) d...
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09/04/2017
ARIGAN: Synthetic Arabidopsis Plants using Generative Adversarial Network
In recent years, there has been an increasing interest in image-based pl...
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06/28/2016
Theta-RBM: Unfactored Gated Restricted Boltzmann Machine for Rotation-Invariant Representations
Learning invariant representations is a critical task in computer vision...
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04/24/2016