Bernhard Kainz

research

∙ 11/09/2020

Detecting Outliers with Foreign Patch Interpolation

In medical imaging, outliers can contain hypo/hyper-intensities, minor d...

Jeremy Tan, et al. ∙

research

∙ 10/30/2020

Mutual Information-based Disentangled Neural Networks for Classifying Unseen Categories in Different Domains: Application to Fetal Ultrasound Imaging

Deep neural networks exhibit limited generalizability across images with...

Qingjie Meng, et al. ∙

research

∙ 10/04/2020

Surface Agnostic Metrics for Cortical Volume Segmentation and Regression

The cerebral cortex performs higher-order brain functions and is thus im...

Samuel Budd, et al. ∙

research

∙ 08/20/2020

Causal Future Prediction in a Minkowski Space-Time

Estimating future events is a difficult task. Unlike humans, machine lea...

Athanasios Vlontzos, et al. ∙

research

∙ 08/19/2020

Unsupervised Cross-domain Image Classification by Distance Metric Guided Feature Alignment

Learning deep neural networks that are generalizable across different do...

Qingjie Meng, et al. ∙

research

∙ 08/16/2020

Automated Detection of Congenital Heart Disease in Fetal Ultrasound Screening

Prenatal screening with ultrasound can lower neonatal mortality signific...

Jeremy Tan, et al. ∙

research

∙ 06/23/2020

Projective Latent Space Decluttering

High-dimensional latent representations learned by neural network classi...

Andreas Hinterreiter, et al. ∙

research

∙ 06/23/2020

3D Probabilistic Segmentation and Volumetry from 2D projection images

X-Ray imaging is quick, cheap and useful for front-line care assessment ...

Athanasios Vlontzos, et al. ∙

research

∙ 05/19/2020

Ultrasound Video Summarization using Deep Reinforcement Learning

Video is an essential imaging modality for diagnostics, e.g. in ultrasou...

Tianrui Liu, et al. ∙

research

∙ 04/16/2020

Divergent Search for Few-Shot Image Classification

When data is unlabelled and the target task is not known a priori, diver...

Jeremy Tan, et al. ∙

research

∙ 02/29/2020

Learning Cross-domain Generalizable Features by Representation Disentanglement

Deep learning models exhibit limited generalizability across different d...

Qingjie Meng, et al. ∙

research

∙ 10/07/2019

A Survey on Active Learning and Human-in-the-Loop Deep Learning for Medical Image Analysis

Fully automatic deep learning has become the state-of-the-art technique ...

Samuel Budd, et al. ∙

research

∙ 10/06/2019

One Shot Radiance: Global Illumination Using Convolutional Autoencoders

Rendering realistic images with Global Illumination (GI) is a computatio...

Giulio Jiang, et al. ∙

research

∙ 08/31/2019

Automatic Detection of Bowel Disease with Residual Networks

Crohn's disease, one of two inflammatory bowel diseases (IBD), affects 2...

Robert Holland, et al. ∙

research

∙ 08/30/2019

Semi-supervised Learning of Fetal Anatomy from Ultrasound

Semi-supervised learning methods have achieved excellent performance on ...

Jeremy Tan, et al. ∙

research

∙ 08/29/2019

Flexible Conditional Image Generation of Missing Data with Learned Mental Maps

Real-world settings often do not allow acquisition of high-resolution vo...

Benjamin Hou, et al. ∙

research

∙ 08/21/2019

Representation Disentanglement for Multi-task Learning with application to Fetal Ultrasound

One of the biggest challenges for deep learning algorithms in medical im...

Qingjie Meng, et al. ∙

research

∙ 08/07/2019

Confident Head Circumference Measurement from Ultrasound with Real-time Feedback for Sonographers

Manual estimation of fetal Head Circumference (HC) from Ultrasound (US) ...

Samuel Budd, et al. ∙

research

∙ 06/30/2019

Multiple Landmark Detection using Multi-Agent Reinforcement Learning

The detection of anatomical landmarks is a vital step for medical image ...

Athanasios Vlontzos, et al. ∙

research

∙ 03/05/2019

FastReg: Fast Non-Rigid Registration via Accelerated Optimisation on the Manifold of Diffeomorphisms

We present a new approach to diffeomorphic non-rigid registration of med...

Daniel Grzech, et al. ∙

research

∙ 01/27/2019

Automated Quality Control in Image Segmentation: Application to the UK Biobank Cardiac MR Imaging Study

Background: The trend towards large-scale studies including population i...

Robert Robinson, et al. ∙

research

∙ 11/20/2018

Weakly Supervised Estimation of Shadow Confidence Maps in Ultrasound Imaging

Detecting acoustic shadows in ultrasound images is important in many cli...

Qingjie Meng, et al. ∙

research

∙ 09/27/2018

Morpho-MNIST: Quantitative Assessment and Diagnostics for Representation Learning

Revealing latent structure in data is an active field of research, havin...

Daniel Coelho de Castro, et al. ∙

research

∙ 08/22/2018

Attention Gated Networks: Learning to Leverage Salient Regions in Medical Images

We propose a novel attention gate (AG) model for medical image analysis ...

Jo Schlemper, et al. ∙

research

∙ 07/19/2018

EchoFusion: Tracking and Reconstruction of Objects in 4D Freehand Ultrasound Imaging without External Trackers

Ultrasound (US) is the most widely used fetal imaging technique. However...

Bishesh Khanal, et al. ∙

research

∙ 06/19/2018

Standard Plane Detection in 3D Fetal Ultrasound Using an Iterative Transformation Network

Standard scan plane detection in fetal brain ultrasound (US) forms a cru...

Yuanwei Li, et al. ∙

research

∙ 06/18/2018

Fast Multiple Landmark Localisation Using a Patch-based Iterative Network

We propose a new Patch-based Iterative Network (PIN) for fast and accura...

Yuanwei Li, et al. ∙

research

∙ 06/16/2018

Real-time Prediction of Segmentation Quality

Recent advances in deep learning based image segmentation methods have e...

Robert Robinson, et al. ∙

research

∙ 06/08/2018

Automatic View Planning with Multi-scale Deep Reinforcement Learning Agents

We propose a fully automatic method to find standardized view planes in ...

Amir Alansary, et al. ∙

research

∙ 05/02/2018

Computing CNN Loss and Gradients for Pose Estimation with Riemannian Geometry

Pose estimation, i.e. predicting a 3D rigid transformation with respect ...

Benjamin Hou, et al. ∙

research

∙ 04/24/2018

Human-level Performance On Automatic Head Biometrics In Fetal Ultrasound Using Fully Convolutional Neural Networks

Measurement of head biometrics from fetal ultrasonography images is of k...

Matthew Sinclair, et al. ∙

research

∙ 04/15/2018

Attention-Gated Networks for Improving Ultrasound Scan Plane Detection

In this work, we apply an attention-gated network to real-time automated...

Jo Schlemper, et al. ∙

research

∙ 04/11/2018

Attention U-Net: Learning Where to Look for the Pancreas

We propose a novel attention gate (AG) model for medical imaging that au...

Ozan Oktay, et al. ∙

research

∙ 01/05/2018

Efficient Image Evidence Analysis of CNN Classification Results

Convolutional neural networks (CNNs) define the current state-of-the-art...

Keyang Zhou, et al. ∙

research

∙ 11/18/2017

DLTK: State of the Art Reference Implementations for Deep Learning on Medical Images

We present DLTK, a toolkit providing baseline implementations for effici...

Nick Pawlowski, et al. ∙

research

∙ 11/04/2017

Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation

Deep learning approaches such as convolutional neural nets have consiste...

Konstantinos Kamnitsas, et al. ∙

research

∙ 10/25/2017

Human-level CMR image analysis with deep fully convolutional networks

Cardiovascular magnetic resonance (CMR) imaging is a standard imaging mo...

Wenjia Bai, et al. ∙

research

∙ 09/19/2017

3D Reconstruction in Canonical Co-ordinate Space from Arbitrarily Oriented 2D Images

Limited capture range and the requirement to provide high quality initia...

Benjamin Hou, et al. ∙

research

∙ 05/22/2017

Anatomically Constrained Neural Networks (ACNN): Application to Cardiac Image Enhancement and Segmentation

Incorporation of prior knowledge about organ shape and location is key t...

Ozan Oktay, et al. ∙

research

∙ 02/28/2017

Context-Sensitive Super-Resolution for Fast Fetal Magnetic Resonance Imaging

3D Magnetic Resonance Imaging (MRI) is often a trade-off between fast bu...

Steven McDonagh, et al. ∙

research

∙ 02/28/2017

Predicting Slice-to-Volume Transformation in Presence of Arbitrary Subject Motion

This paper aims to solve a fundamental problem in intensity-based 2D/3D ...

Benjamin Hou, et al. ∙

research

∙ 12/16/2016

SonoNet: Real-Time Detection and Localisation of Fetal Standard Scan Planes in Freehand Ultrasound

Identifying and interpreting fetal standard scan planes during 2D ultras...

Christian F. Baumgartner, et al. ∙

research

∙ 11/22/2016

PVR: Patch-to-Volume Reconstruction for Large Area Motion Correction of Fetal MRI

In this paper we present a novel method for the correction of motion art...

Amir Alansary, et al. ∙

research

∙ 06/03/2016

Learning under Distributed Weak Supervision

The availability of training data for supervision is a frequently encoun...

Martin Rajchl, et al. ∙

research

∙ 05/25/2016

DeepCut: Object Segmentation from Bounding Box Annotations using Convolutional Neural Networks

In this paper, we propose DeepCut, a method to obtain pixelwise object s...

Martin Rajchl, et al. ∙

research

∙ 10/21/2015

Interactive Volumetry Of Liver Ablation Zones

Percutaneous radiofrequency ablation (RFA) is a minimally invasive techn...

Jan Egger, et al. ∙

Bernhard Kainz

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