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08/15/2023
Riemannian geometry for efficient analysis of protein dynamics data
An increasingly common viewpoint is that protein dynamics data sets resi...
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08/02/2023
MammoDG: Generalisable Deep Learning Breaks the Limits of Cross-Domain Multi-Center Breast Cancer Screening
Breast cancer is a major cause of cancer death among women, emphasising ...
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07/25/2023
Reinterpreting survival analysis in the universal approximator age
Survival analysis is an integral part of the statistical toolbox. Howeve...
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07/18/2023
Convergent regularization in inverse problems and linear plug-and-play denoisers
Plug-and-play (PnP) denoising is a popular iterative framework for solvi...
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07/14/2023
Inverse Evolution Layers: Physics-informed Regularizers for Deep Neural Networks
This paper proposes a novel approach to integrating partial differential...
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06/30/2023
Proximal Langevin Sampling With Inexact Proximal Mapping
In order to solve tasks like uncertainty quantification or hypothesis te...
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06/29/2023
Designing Stable Neural Networks using Convex Analysis and ODEs
Motivated by classical work on the numerical integration of ordinary dif...
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06/25/2023
CDiffMR: Can We Replace the Gaussian Noise with K-Space Undersampling for Fast MRI?
Deep learning has shown the capability to substantially accelerate MRI r...
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06/15/2023
Dis-AE: Multi-domain Multi-task Generalisation on Real-World Clinical Data
Clinical data is often affected by clinically irrelevant factors such as...
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04/24/2023
Variational Diffusion Auto-encoder: Deep Latent Variable Model with Unconditional Diffusion Prior
Variational auto-encoders (VAEs) are one of the most popular approaches ...
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04/17/2023
NF-ULA: Langevin Monte Carlo with Normalizing Flow Prior for Imaging Inverse Problems
Bayesian methods for solving inverse problems are a powerful alternative...
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03/19/2023
DiffMIC: Dual-Guidance Diffusion Network for Medical Image Classification
Diffusion Probabilistic Models have recently shown remarkable performanc...
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03/18/2023
HGIB: Prognosis for Alzheimer's Disease via Hypergraph Information Bottleneck
Alzheimer's disease prognosis is critical for early Mild Cognitive Impai...
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03/15/2023
Class-Guided Image-to-Image Diffusion: Cell Painting from Brightfield Images with Class Labels
Image-to-image reconstruction problems with free or inexpensive metadata...
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03/14/2023
Homeomorphic Image Registration via Conformal-Invariant Hyperelastic Regularisation
Deformable image registration is a fundamental task in medical image ana...
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03/09/2023
Provably Convergent Plug-and-Play Quasi-Newton Methods
Plug-and-Play (PnP) methods are a class of efficient iterative methods t...
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03/07/2023
Hidden Knowledge: Mathematical Methods for the Extraction of the Fingerprint of Medieval Paper from Digital Images
Medieval paper, a handmade product, is made with a mould which leaves an...
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02/24/2023
Implicit neural representations for unsupervised super-resolution and denoising of 4D flow MRI
4D flow MRI is a non-invasive imaging method that can measure blood flow...
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02/08/2023
Can Physics-Informed Neural Networks beat the Finite Element Method?
Partial differential equations play a fundamental role in the mathematic...
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02/01/2023
Continuous U-Net: Faster, Greater and Noiseless
Image segmentation is a fundamental task in image analysis and clinical ...
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12/23/2022
Your diffusion model secretly knows the dimension of the data manifold
In this work, we propose a novel framework for estimating the dimension ...
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11/25/2022
On Krylov Methods for Large Scale CBCT Reconstruction
Krylov subspace methods are a powerful family of iterative solvers for l...
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11/17/2022
TrafficCAM: A Versatile Dataset for Traffic Flow Segmentation
Traffic flow analysis is revolutionising traffic management. Qualifying ...
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11/17/2022
NorMatch: Matching Normalizing Flows with Discriminative Classifiers for Semi-Supervised Learning
Semi-Supervised Learning (SSL) aims to learn a model using a tiny labele...
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11/13/2022
SCOTCH and SODA: A Transformer Video Shadow Detection Framework
Shadows in videos are difficult to detect because of the large shadow de...
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11/09/2022
Maximum Entropy on the Mean and the Cramér Rate Function in Statistical Estimation and Inverse Problems: Properties, Models, and Algorithms
We explore a method of statistical estimation called Maximum Entropy on ...
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10/21/2022
Navigating the challenges in creating complex data systems: a development philosophy
In this perspective, we argue that despite the democratization of powerf...
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10/05/2022
Dynamical systems' based neural networks
Neural networks have gained much interest because of their effectiveness...
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09/18/2022
Why Deep Surgical Models Fail?: Revisiting Surgical Action Triplet Recognition through the Lens of Robustness
Surgical action triplet recognition provides a better understanding of t...
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09/16/2022
Self-Supervised Learning of Phenotypic Representations from Cell Images with Weak Labels
We propose WS-DINO as a novel framework to use weak label information in...
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09/12/2022
Spectral decomposition of atomic structures in heterogeneous cryo-EM
We consider the problem of recovering the three-dimensional atomic struc...
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09/05/2022
Imaging with Equivariant Deep Learning
From early image processing to modern computational imaging, successful ...
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08/31/2022
Accelerating Deep Unrolling Networks via Dimensionality Reduction
In this work we propose a new paradigm for designing efficient deep unro...
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08/11/2022
Joint reconstruction-segmentation on graphs
Practical image segmentation tasks concern images which must be reconstr...
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08/02/2022
Stochastic Primal-Dual Three Operator Splitting with Arbitrary Sampling and Preconditioning
In this work we propose a stochastic primal-dual preconditioned three-op...
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07/20/2022
Non-Uniform Diffusion Models
Diffusion models have emerged as one of the most promising frameworks fo...
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06/16/2022
Classification of datasets with imputed missing values: does imputation quality matter?
Classifying samples in incomplete datasets is a common aim for machine l...
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06/11/2022
Learned reconstruction with convergence guarantees
In recent years, deep learning has achieved remarkable empirical success...
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06/09/2022
Unsupervised Learning of the Total Variation Flow
The total variation (TV) flow generates a scale-space representation of ...
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04/04/2022
Multi-Modal Hypergraph Diffusion Network with Dual Prior for Alzheimer Classification
The automatic early diagnosis of prodromal stages of Alzheimer's disease...
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03/21/2022
Multi-modal learning for predicting the genotype of glioma
The isocitrate dehydrogenase (IDH) gene mutation is an essential biomark...
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03/14/2022
Unsupervised Clustering of Roman Potsherds via Variational Autoencoders
In this paper we propose an artificial intelligence imaging solution to ...
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03/10/2022
PC-SwinMorph: Patch Representation for Unsupervised Medical Image Registration and Segmentation
Medical image registration and segmentation are critical tasks for sever...
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03/08/2022
Predicting conversion of mild cognitive impairment to Alzheimer's disease
Alzheimer's disease (AD) is the most common age-related dementia. Mild c...
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03/08/2022
Mutual Contrastive Learning to Disentangle Whole Slide Image Representations for Glioma Grading
Whole slide images (WSI) provide valuable phenotypic information for his...
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03/01/2022
Simultaneous Semantic and Instance Segmentation for Colon Nuclei Identification and Counting
We address the problem of automated nuclear segmentation, classification...
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02/10/2022
Γ-Convergence of an Ambrosio-Tortorelli approximation scheme for image segmentation
Given an image u_0, the aim of minimising the Mumford-Shah functional is...
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01/14/2022
Collaborative learning of images and geometrics for predicting isocitrate dehydrogenase status of glioma
The isocitrate dehydrogenase (IDH) gene mutation status is an important ...
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12/23/2021
AI-based Reconstruction for Fast MRI – A Systematic Review and Meta-analysis
Compressed sensing (CS) has been playing a key role in accelerating the ...
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12/07/2021