2.7k citations · 9.2k across the 86 of their papers we have counts for
19 papers · 1 filter
Biomedical image analysis competitions: The state of current participation practice
Matthias Eisenmann, Annika Reinke, Vivienn Weru +352
The number of international benchmarking competitions is steadily increasing in various fields of machine learning (ML) research and practice. So far, however, little is known abou…
MONAI: An open-source framework for deep learning in healthcare
M. Jorge Cardoso, Wenqi Li, Richard Brown +53
Artificial Intelligence (AI) is having a tremendous impact across most areas of science. Applications of AI in healthcare have the potential to improve our ability to detect, diagn…
Trackerless freehand ultrasound with sequence modelling and auxiliary transformation over past and future frames
Qi Li, Ziyi Shen, Qian Li +5
Three-dimensional (3D) freehand ultrasound (US) reconstruction without a tracker can be advantageous over its two-dimensional or tracked counterparts in many clinical applications.…
Rapid and robust endoscopic content area estimation: A lean GPU-based pipeline and curated benchmark dataset
Charlie Budd, Luis C. Garcia-Peraza-Herrera, Martin Huber +2
Endoscopic content area refers to the informative area enclosed by the dark, non-informative, border regions present in most endoscopic footage. The estimation of the content area…
ROS-PyBullet Interface: A Framework for Reliable Contact Simulation and Human-Robot Interaction
Christopher E. Mower, Theodoros Stouraitis, João Moura +7
Reliable contact simulation plays a key role in the development of (semi-)autonomous robots, especially when dealing with contact-rich manipulation scenarios, an active robotics re…
Can segmentation models be trained with fully synthetically generated data?
Virginia Fernandez, Walter Hugo Lopez Pinaya, Pedro Borges +4
In order to achieve good performance and generalisability, medical image segmentation models should be trained on sizeable datasets with sufficient variability. Due to ethics and g…
Driving Points Prediction For Abdominal Probabilistic Registration
Samuel Joutard, Reuben Dorent, Sebastien Ourselin +2
Inter-patient abdominal registration has various applications, from pharmakinematic studies to anatomy modeling. Yet, it remains a challenging application due to the morphological…
FastGeodis: Fast Generalised Geodesic Distance Transform
Muhammad Asad, Reuben Dorent, Tom Vercauteren
The FastGeodis package provides an efficient implementation for computing Geodesic and Euclidean distance transforms (or a mixture of both), targeting efficient utilisation of CPU…
Cross-Modality Image Registration using a Training-Time Privileged Third Modality
Qianye Yang, David Atkinson, Yunguan Fu +7
In this work, we consider the task of pairwise cross-modality image registration, which may benefit from exploiting additional images available only at training time from an additi…
Spatiotemporal singular value decomposition for denoising in photoacoustic imaging with low-energy excitation light source
Mengjie Shi, Tom Vercauteren, Wenfeng Xia
Photoacoustic (PA) imaging is an emerging hybrid imaging modality that combines rich optical spectroscopic contrast and high ultrasonic resolution and thus holds tremendous promise…
Ultrathin, high-speed, all-optical photoacoustic endomicroscopy probe for guiding minimally invasive surgery
Tianrui Zhao, Truc Thuy Pham, Christian Baker +6
Photoacoustic (PA) endoscopy has shown significant potential for clinical diagnosis and surgical guidance. Multimode fibres (MMFs) are becoming increasing attractive for the develo…
Deep Quality Estimation: Creating Surrogate Models for Human Quality Ratings
Florian Kofler, Ivan Ezhov, Lucas Fidon +14
Human ratings are abstract representations of segmentation quality. To approximate human quality ratings on scarce expert data, we train surrogate quality estimation models. We eva…
blob loss: instance imbalance aware loss functions for semantic segmentation
Florian Kofler, Suprosanna Shit, Ivan Ezhov +14
Deep convolutional neural networks (CNN) have proven to be remarkably effective in semantic segmentation tasks. Most popular loss functions were introduced targeting improved volum…
Fetal Brain Tissue Annotation and Segmentation Challenge Results
Kelly Payette, Hongwei Li, Priscille de Dumast +55
In-utero fetal MRI is emerging as an important tool in the diagnosis and analysis of the developing human brain. Automatic segmentation of the developing fetal brain is a vital ste…
A Dempster-Shafer approach to trustworthy AI with application to fetal brain MRI segmentation
Lucas Fidon, Michael Aertsen, Florian Kofler +18
Deep learning models for medical image segmentation can fail unexpectedly and spectacularly for pathological cases and images acquired at different centers than training images, wi…
MONAI Label: A framework for AI-assisted Interactive Labeling of 3D Medical Images
Andres Diaz-Pinto, Sachidanand Alle, Vishwesh Nath +14
The lack of annotated datasets is a major bottleneck for training new task-specific supervised machine learning models, considering that manual annotation is extremely expensive an…
Motion Correction and Volumetric Reconstruction for Fetal Functional Magnetic Resonance Imaging Data
Daniel Sobotka, Michael Ebner, Ernst Schwartz +8
Motion correction is an essential preprocessing step in functional Magnetic Resonance Imaging (fMRI) of the fetal brain with the aim to remove artifacts caused by fetal movement an…
ECONet: Efficient Convolutional Online Likelihood Network for Scribble-based Interactive Segmentation
Muhammad Asad, Lucas Fidon, Tom Vercauteren
Automatic segmentation of lung lesions associated with COVID-19 in CT images requires large amount of annotated volumes. Annotations mandate expert knowledge and are time-intensive…
CrossMoDA 2021 challenge: Benchmark of Cross-Modality Domain Adaptation techniques for Vestibular Schwannoma and Cochlea Segmentation
Reuben Dorent, Aaron Kujawa, Marina Ivory +37
Domain Adaptation (DA) has recently raised strong interests in the medical imaging community. While a large variety of DA techniques has been proposed for image segmentation, most…