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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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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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03/14/2023
Homeomorphic Image Registration via Conformal-Invariant Hyperelastic Regularisation
Deformable image registration is a fundamental task in medical image ana...
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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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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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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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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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03/10/2022
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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03/01/2022
Simultaneous Semantic and Instance Segmentation for Colon Nuclei Identification and Counting
We address the problem of automated nuclear segmentation, classification...
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07/21/2021
Delving Into Deep Walkers: A Convergence Analysis of Random-Walk-Based Vertex Embeddings
Graph vertex embeddings based on random walks have become increasingly i...
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06/08/2021
LaplaceNet: A Hybrid Energy-Neural Model for Deep Semi-Supervised Classification
Semi-supervised learning has received a lot of recent attention as it al...
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06/07/2021
HERS Superpixels: Deep Affinity Learning for Hierarchical Entropy Rate Segmentation
Superpixels serve as a powerful preprocessing tool in many computer visi...
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01/20/2021
Beyond Fine-tuning: Classifying High Resolution Mammograms using Function-Preserving Transformations
The task of classifying mammograms is very challenging because the lesio...
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11/17/2020
Contrastive Registration for Unsupervised Medical Image Segmentation
Medical image segmentation is a relevant task as it serves as the first ...
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09/30/2020
GraphXCOVID: Explainable Deep Graph Diffusion Pseudo-Labelling for Identifying COVID-19 on Chest X-rays
Can one learn to diagnose COVID-19 under extreme minimal supervision? Si...
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08/14/2020
Machine learning for COVID-19 detection and prognostication using chest radiographs and CT scans: a systematic methodological review
Background: Machine learning methods offer great potential for fast and ...
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03/13/2020
The GraphNet Zoo: A Plug-and-Play Framework for Deep Semi-Supervised Classification
We consider the problem of classifying a medical image dataset when we h...
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12/17/2019
Dim the Lights! – Low-Rank Prior Temporal Data for Specular-Free Video Recovery
The appearance of an object is significantly affected by the illuminatio...
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12/16/2019
Rethinking Medical Image Reconstruction via Shape Prior, Going Deeper and Faster: Deep Joint Indirect Registration and Reconstruction
Indirect image registration is a promising technique to improve image re...
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10/10/2019
Dynamic Spectral Residual Superpixels
We consider the problem of segmenting an image into superpixels in the c...
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08/16/2019
Variational Multi-Task MRI Reconstruction: Joint Reconstruction, Registration and Super-Resolution
Motion degradation is a central problem in Magnetic Resonance Imaging (M...
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07/23/2019
GraphX^NET- Chest X-Ray Classification Under Extreme Minimal Supervision
The task of classifying X-ray data is a problem of both theoretical and ...
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06/20/2019
Beyond Supervised Classification: Extreme Minimal Supervision with the Graph 1-Laplacian
We consider the task of classifying when an extremely reduced amount of ...
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10/25/2018
Compressed Sensing Plus Motion (CS+M): A New Perspective for Improving Undersampled MR Image Reconstruction
Purpose: To obtain high-quality reconstructions from highly undersampled...
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05/29/2018
Mirror, Mirror, on the Wall, Who's Got the Clearest Image of Them All? - A Tailored Approach to Single Image Reflection Removal
Removing reflection artefacts from a single-image is a problem of both t...
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02/08/2018
