Publications (37)
Uncertainty Propagation for Echocardiography Clinical Metric Estimation via Contour Sampling
Thierry Judge, Olivier Bernard, Woo-Jin Cho Kim +4
Echocardiography plays a fundamental role in the extraction of important clinical parameters (e.g. left ventricular volume and ejection fraction) required to determine the presence…
Deep Generative Models to Simulate 2D Patient-Specific Ultrasound Images in Real Time
Cesare Magnetti, Veronika Zimmer, Nooshin Ghavami +6
We present a computational method for real-time, patient-specific simulation of 2D ultrasound (US) images. The method uses a large number of tracked ultrasound images to learn a fu…
Fully Automatic Data Labeling for Ultrasound Screen Detection
Alberto Gomez, Jorge Oliveira, Ramon Casero +1
Ultrasound (US) machines display images on a built-in monitor, but routine transfer to hospital systems relies on DICOM. We propose a fully automatic method to generate labeled dat…
B-line Detection in Lung Ultrasound Videos: Cartesian vs Polar Representation
Hamideh Kerdegari, Phung Tran Huy Nhat, Angela McBride +5
Lung ultrasound (LUS) imaging is becoming popular in the intensive care units (ICU) for assessing lung abnormalities such as the appearance of B-line artefacts as a result of sever…
BackMix: Mitigating Shortcut Learning in Echocardiography with Minimal Supervision
Kit Mills Bransby, Arian Beqiri, Woo-Jin Cho Kim +3
Neural networks can learn spurious correlations that lead to the correct prediction in a validation set, but generalise poorly because the predictions are right for the wrong reaso…
Robotic-assisted Ultrasound for Fetal Imaging: Evolution from Single-arm to Dual-arm System
Shuangyi Wang, James Housden, Yohan Noh +20
The development of robotic-assisted extracorporeal ultrasound systems has a long history and a number of projects have been proposed since the 1990s focusing on different technical…
EchoFusion: Tracking and Reconstruction of Objects in 4D Freehand Ultrasound Imaging without External Trackers
Bishesh Khanal, Alberto Gomez, Nicolas Toussaint +11
Ultrasound (US) is the most widely used fetal imaging technique. However, US images have limited capture range, and suffer from view dependent artefacts such as acoustic shadows. C…
3-D Coherent Multi-Transducer Ultrasound Imaging with Sparse Spiral Arrays
Laura Peralta, Daniele Mazierli, Alberto Gomez +3
Coherent multi-transducer ultrasound (CoMTUS) creates an extended effective aperture through the coherent combination of multiple arrays, which results in images with enhanced reso…
MIPROT: A Medical Image Processing Toolbox for MATLAB
Alberto Gomez
This paper presents a Matlab toolbox to perform basic image processing and visualization tasks, particularly designed for medical image processing. The functionalities available ar…
Anatomically Constrained Transformers for Echocardiogram Analysis
Alexander Thorley, Agis Chartsias, Jordan Strom +4
Video transformers have recently demonstrated strong potential for echocardiogram (echo) analysis, leveraging self-supervised pre-training and flexible adaptation across diverse ta…
Adapted and Oversegmenting Graphs: Application to Geometric Deep Learning
Alberto Gomez, Veronika A. Zimmer, Bishesh Khanal +2
We propose a novel iterative method to adapt a a graph to d-dimensional image data. The method drives the nodes of the graph towards image features. The adaptation process naturall…
Confident Head Circumference Measurement from Ultrasound with Real-time Feedback for Sonographers
Samuel Budd, Matthew Sinclair, Bishesh Khanal +6
Manual estimation of fetal Head Circumference (HC) from Ultrasound (US) is a key biometric for monitoring the healthy development of fetuses. Unfortunately, such measurements are s…
Mutual Information-based Disentangled Neural Networks for Classifying Unseen Categories in Different Domains: Application to Fetal Ultrasound Imaging
Qingjie Meng, Jacqueline Matthew, Veronika A. Zimmer +4
Deep neural networks exhibit limited generalizability across images with different entangled domain features and categorical features. Learning generalizable features that can form…
Multi-Site Class-Incremental Learning with Weighted Experts in Echocardiography
Kit M. Bransby, Woo-jin Cho Kim, Jorge Oliveira +4
Building an echocardiography view classifier that maintains performance in real-life cases requires diverse multi-site data, and frequent updates with newly available data to mitig…
A Machine Learning Case Study for AI-empowered echocardiography of Intensive Care Unit Patients in low- and middle-income countries
Miguel Xochicale, Louise Thwaites, Sophie Yacoub +5
We present a Machine Learning (ML) study case to illustrate the challenges of clinical translation for a real-time AI-empowered echocardiography system with data of ICU patients in…
Left Ventricle Contouring of Apical Three-Chamber Views on 2D Echocardiography
Alberto Gomez, Mihaela Porumb, Angela Mumith +5
We propose a new method to automatically contour the left ventricle on 2D echocardiographic images. Unlike most existing segmentation methods, which are based on predicting segment…
Feature-Conditioned Cascaded Video Diffusion Models for Precise Echocardiogram Synthesis
Hadrien Reynaud, Mengyun Qiao, Mischa Dombrowski +5
Image synthesis is expected to provide value for the translation of machine learning methods into clinical practice. Fundamental problems like model robustness, domain transfer, ca…
Automatic Detection of B-lines in Lung Ultrasound Videos From Severe Dengue Patients
Hamideh Kerdegari, Phung Tran Huy Nhat, Angela McBride +6
Lung ultrasound (LUS) imaging is used to assess lung abnormalities, including the presence of B-line artefacts due to fluid leakage into the lungs caused by a variety of diseases.…
Mechanically Powered Motion Imaging Phantoms: Proof of Concept
Alberto Gomez, Cornelia Schmitz, Markus Henningsson +8
Motion imaging phantoms are expensive, bulky and difficult to transport and set-up. The purpose of this paper is to demonstrate a simple approach to the design of multi-modality mo…
InfoMotion: A Graph-Based Approach to Video Dataset Distillation for Echocardiography
Zhe Li, Hadrien Reynaud, Alberto Gomez +1
Echocardiography plays a critical role in the diagnosis and monitoring of cardiovascular diseases as a non-invasive real-time assessment of cardiac structure and function. However,…
Fourier-Net+: Leveraging Band-Limited Representation for Efficient 3D Medical Image Registration
Xi Jia, Alexander Thorley, Alberto Gomez +3
U-Net style networks are commonly utilized in unsupervised image registration to predict dense displacement fields, which for high-resolution volumetric image data is a resource-in…
Coherent Multi-Transducer Ultrasound Imaging
Laura Peralta, Alberto Gomez, Ying Luan +3
An extended aperture has the potential to greatly improve ultrasound imaging performance. This work extends the effective aperture size by coherently compounding the received radio…
Learning to Stop: Reinforcement Learning for Efficient Patient-Level Echocardiographic Classification
Woo-Jin Cho Kim, Jorge Oliveira, Arian Beqiri +8
Guidelines for transthoracic echocardiographic examination recommend the acquisition of multiple video clips from different views of the heart, resulting in a large number of clips…
Automatic retrieval of corresponding US views in longitudinal examinations
Hamideh Kerdegari, Tran Huy Nhat Phung1, Van Hao Nguyen +12
Skeletal muscle atrophy is a common occurrence in critically ill patients in the intensive care unit (ICU) who spend long periods in bed. Muscle mass must be recovered through phys…
Anatomically Constrained Transformers for Cardiac Amyloidosis Classification
Alexander Thorley, Agis Chartsias, Jordan Strom +7
Cardiac amyloidosis (CA) is a rare cardiomyopathy, with typical abnormalities in clinical measurements from echocardiograms such as reduced global longitudinal strain of the myocar…
Placenta Segmentation in Ultrasound Imaging: Addressing Sources of Uncertainty and Limited Field-of-View
Veronika A. Zimmer, Alberto Gomez, Emily Skelton +10
Automatic segmentation of the placenta in fetal ultrasound (US) is challenging due to the (i) high diversity of placenta appearance, (ii) the restricted quality in US resulting in…
Weakly Supervised Localisation for Fetal Ultrasound Images
Nicolas Toussaint, Bishesh Khanal, Matthew Sinclair +4
This paper addresses the task of detecting and localising fetal anatomical regions in 2D ultrasound images, where only image-level labels are present at training, i.e. without any…
AI-enabled Assessment of Cardiac Systolic and Diastolic Function from Echocardiography
Esther Puyol-Antón, Bram Ruijsink, Baldeep S. Sidhu +12
Left ventricular (LV) function is an important factor in terms of patient management, outcome, and long-term survival of patients with heart disease. The most recently published cl…
Efficient Semantic Diffusion Architectures for Model Training on Synthetic Echocardiograms
David Stojanovski, Mariana da Silva, Pablo Lamata +2
We investigate the utility of diffusion generative models to efficiently synthesise datasets that effectively train deep learning models for image analysis. Specifically, we propos…
EchoNet-Synthetic: Privacy-preserving Video Generation for Safe Medical Data Sharing
Hadrien Reynaud, Qingjie Meng, Mischa Dombrowski +5
To make medical datasets accessible without sharing sensitive patient information, we introduce a novel end-to-end approach for generative de-identification of dynamic medical imag…
PRETUS: A plug-in based platform for real-time ultrasound imaging research
Alberto Gomez, Veronika A. Zimmer, Gavin Wheeler +8
We present PRETUS -a Plugin-based Real Time UltraSound software platform for live ultrasound image analysis and operator support. The software is lightweight; functionality is brou…
Screen Tracking for Clinical Translation of Live Ultrasound Image Analysis Methods
Simona Treivase, Alberto Gomez, Jacqueline Matthew +3
Ultrasound (US) imaging is one of the most commonly used non-invasive imaging techniques. However, US image acquisition requires simultaneous guidance of the transducer and interpr…
EchoFlow: A Foundation Model for Cardiac Ultrasound Image and Video Generation
Hadrien Reynaud, Alberto Gomez, Paul Leeson +2
Advances in deep learning have significantly enhanced medical image analysis, yet the availability of large-scale medical datasets remains constrained by patient privacy concerns.…
Weakly Supervised Estimation of Shadow Confidence Maps in Fetal Ultrasound Imaging
Qingjie Meng, Matthew Sinclair, Veronika Zimmer +11
Detecting acoustic shadows in ultrasound images is important in many clinical and engineering applications. Real-time feedback of acoustic shadows can guide sonographers to a stand…
DeepSPV: A Deep Learning Pipeline for 3D Spleen Volume Estimation from 2D Ultrasound Images
Zhen Yuan, David Stojanovski, Lei Li +5
Splenomegaly, the enlargement of the spleen, is an important clinical indicator for various associated medical conditions, such as sickle cell disease (SCD). Spleen length measured…
Efficient Pix2Vox++ for 3D Cardiac Reconstruction from 2D echo views
David Stojanovski, Uxio Hermida, Marica Muffoletto +3
Accurate geometric quantification of the human heart is a key step in the diagnosis of numerous cardiac diseases, and in the management of cardiac patients. Ultrasound imaging is t…
Echo from noise: synthetic ultrasound image generation using diffusion models for real image segmentation
David Stojanovski, Uxio Hermida, Pablo Lamata +2
We propose a novel pipeline for the generation of synthetic ultrasound images via Denoising Diffusion Probabilistic Models (DDPMs) guided by cardiac semantic label maps. We show th…