1.1k citations · 2.7k across the 92 of their papers we have counts for
11 papers · 1 filter
AIROGS: Artificial Intelligence for RObust Glaucoma Screening Challenge
Coen de Vente, Koenraad A. Vermeer, Nicolas Jaccard +33
The early detection of glaucoma is essential in preventing visual impairment. Artificial intelligence (AI) can be used to analyze color fundus photographs (CFPs) in a cost-effectiv…
Unsupervised Anomaly Detection in Medical Images with a Memory-augmented Multi-level Cross-attentional Masked Autoencoder
Yu Tian, Guansong Pang, Yuyuan Liu +7
Unsupervised anomaly detection (UAD) aims to find anomalous images by optimising a detector using a training set that contains only normal images. UAD approaches can be based on re…
BoMD: Bag of Multi-label Descriptors for Noisy Chest X-ray Classification
Yuanhong Chen, Fengbei Liu, Hu Wang +4
Deep learning methods have shown outstanding classification accuracy in medical imaging problems, which is largely attributed to the availability of large-scale datasets manually a…
Mutual information neural estimation for unsupervised multi-modal registration of brain images
Gerard Snaauw, Michele Sasdelli, Gabriel Maicas +4
Many applications in image-guided surgery and therapy require fast and reliable non-linear, multi-modal image registration. Recently proposed unsupervised deep learning-based regis…
A Hierarchical Multi-Task Approach to Gastrointestinal Image Analysis
Adrian Galdran, Gustavo Carneiro, Miguel A. González Ballester
A large number of different lesions and pathologies can affect the human digestive system, resulting in life-threatening situations. Early detection plays a relevant role in the su…
Convolutional Nets Versus Vision Transformers for Diabetic Foot Ulcer Classification
Adrian Galdran, Gustavo Carneiro, Miguel A. González Ballester
This paper compares well-established Convolutional Neural Networks (CNNs) to recently introduced Vision Transformers for the task of Diabetic Foot Ulcer Classification, in the cont…
Double Encoder-Decoder Networks for Gastrointestinal Polyp Segmentation
Adrian Galdran, Gustavo Carneiro, Miguel A. González Ballester
Polyps represent an early sign of the development of Colorectal Cancer. The standard procedure for their detection consists of colonoscopic examination of the gastrointestinal trac…
Self-supervised Pseudo Multi-class Pre-training for Unsupervised Anomaly Detection and Segmentation in Medical Images
Yu Tian, Fengbei Liu, Guansong Pang +5
Unsupervised anomaly detection (UAD) methods are trained with normal (or healthy) images only, but during testing, they are able to classify normal and abnormal (or disease) images…
Self-supervised Lesion Change Detection and Localisation in Longitudinal Multiple Sclerosis Brain Imaging
Minh-Son To, Ian G Sarno, Chee Chong +2
Longitudinal imaging forms an essential component in the management and follow-up of many medical conditions. The presence of lesion changes on serial imaging can have significant…
Self-supervised Depth Estimation to Regularise Semantic Segmentation in Knee Arthroscopy
Fengbei Liu, Yaqub Jonmohamadi, Gabriel Maicas +2
Intra-operative automatic semantic segmentation of knee joint structures can assist surgeons during knee arthroscopy in terms of situational awareness. However, due to poor imaging…
Unsupervised Dual Adversarial Learning for Anomaly Detection in Colonoscopy Video Frames
Yuyuan Liu, Yu Tian, Gabriel Maicas +4
The automatic detection of frames containing polyps from a colonoscopy video sequence is an important first step for a fully automated colonoscopy analysis tool. Typically, such de…