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A Survey on Active Learning and Human-in-the-Loop Deep Learning for Medical Image Analysis
Samuel Budd, Emma C Robinson, Bernhard Kainz
Fully automatic deep learning has become the state-of-the-art technique for many tasks including image acquisition, analysis and interpretation, and for the extraction of clinicall…
Deep Radiance Caching: Convolutional Autoencoders Deeper in Ray Tracing
Giulio Jiang, Bernhard Kainz
Rendering realistic images with global illumination is a computationally demanding task and often requires dedicated hardware for feasible runtime. Recent research uses Deep Neural…
Automatic Detection of Bowel Disease with Residual Networks
Robert Holland, Uday Patel, Phillip Lung +2
Crohn's disease, one of two inflammatory bowel diseases (IBD), affects 200,000 people in the UK alone, or roughly one in every 500. We explore the feasibility of deep learning algo…
Semi-supervised Learning of Fetal Anatomy from Ultrasound
Jeremy Tan, Anselm Au, Qingjie Meng +1
Semi-supervised learning methods have achieved excellent performance on standard benchmark datasets using very few labelled images. Anatomy classification in fetal 2D ultrasound is…
Flexible Conditional Image Generation of Missing Data with Learned Mental Maps
Benjamin Hou, Athanasios Vlontzos, Amir Alansary +2
Real-world settings often do not allow acquisition of high-resolution volumetric images for accurate morphological assessment and diagnostic. In clinical practice it is frequently…
Representation Disentanglement for Multi-task Learning with application to Fetal Ultrasound
Qingjie Meng, Nick Pawlowski, Daniel Rueckert +1
One of the biggest challenges for deep learning algorithms in medical image analysis is the indiscriminate mixing of image properties, e.g. artifacts and anatomy. These entangled i…
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…
Multiple Landmark Detection using Multi-Agent Reinforcement Learning
Athanasios Vlontzos, Amir Alansary, Konstantinos Kamnitsas +2
The detection of anatomical landmarks is a vital step for medical image analysis and applications for diagnosis, interpretation and guidance. Manual annotation of landmarks is a te…
FastReg: Fast Non-Rigid Registration via Accelerated Optimisation on the Manifold of Diffeomorphisms
Daniel Grzech, Loïc le Folgoc, Mattias P. Heinrich +5
We present an implementation of a new approach to diffeomorphic non-rigid registration of medical images. The method is based on optical flow and warps images via gradient flow wit…
Automated Quality Control in Image Segmentation: Application to the UK Biobank Cardiac MR Imaging Study
Robert Robinson, Vanya V. Valindria, Wenjia Bai +19
Background: The trend towards large-scale studies including population imaging poses new challenges in terms of quality control (QC). This is a particular issue when automatic proc…