726 citations · 1.5k across the 28 of their papers we have counts for
7 papers · 1 filter
Generalized Wasserstein Dice Loss, Test-time Augmentation, and Transformers for the BraTS 2021 challenge
Lucas Fidon, Suprosanna Shit, Ivan Ezhov +3
Brain tumor segmentation from multiple Magnetic Resonance Imaging (MRI) modalities is a challenging task in medical image computation. The main challenges lie in the generalizabili…
Improving needle visibility in LED-based photoacoustic imaging using deep learning with semi-synthetic datasets
Mengjie Shi, Tianrui Zhao, Simeon J. West +3
Photoacoustic imaging has shown great potential for guiding minimally invasive procedures by accurate identification of critical tissue targets and invasive medical devices (such a…
A self-supervised learning strategy for postoperative brain cavity segmentation simulating resections
Fernando Pérez-García, Reuben Dorent, Michele Rizzi +9
Accurate segmentation of brain resection cavities (RCs) aids in postoperative analysis and determining follow-up treatment. Convolutional neural networks (CNNs) are the state-of-th…
Zero-shot super-resolution with a physically-motivated downsampling kernel for endomicroscopy
Agnieszka Barbara Szczotka, Dzhoshkun Ismail Shakir, Matthew J. Clarkson +2
Super-resolution (SR) methods have seen significant advances thanks to the development of convolutional neural networks (CNNs). CNNs have been successfully employed to improve the…
MONAIfbs: MONAI-based fetal brain MRI deep learning segmentation
Marta B. M. Ranzini, Lucas Fidon, Sébastien Ourselin +2
In fetal Magnetic Resonance Imaging, Super Resolution Reconstruction (SRR) algorithms are becoming popular tools to obtain high-resolution 3D volume reconstructions from low-resolu…
Image Compositing for Segmentation of Surgical Tools without Manual Annotations
Luis C. Garcia-Peraza-Herrera, Lucas Fidon, Claudia D'Ettorre +3
Producing manual, pixel-accurate, image segmentation labels is tedious and time-consuming. This is often a rate-limiting factor when large amounts of labeled images are required, s…
Morphological Change Forecasting for Prostate Glands using Feature-based Registration and Kernel Density Extrapolation
Qianye Yang, Tom Vercauteren, Yunguan Fu +7
Organ morphology is a key indicator for prostate disease diagnosis and prognosis. For instance, In longitudinal study of prostate cancer patients under active surveillance, the vol…