activity
20172026
most citedWeakly-Supervised Convolutional Neural Networks for Multimodal Image Registration

477 citations · 994 across the 58 of their papers we have counts for

collaborators
Showing 2020Show all

6 papers · 1 filter

eess.IV2020★ 47 cited

DeepReg: a deep learning toolkit for medical image registration

Yunguan Fu, Nina Montaña Brown, Shaheer U. Saeed +14

DeepReg (https://github.com/DeepRegNet/DeepReg) is a community-supported open-source toolkit for research and education in medical image registration using deep learning.

cs.CV2020

Assisted Probe Positioning for Ultrasound Guided Radiotherapy Using Image Sequence Classification

Alexander Grimwood, Helen McNair, Yipeng Hu +3

Effective transperineal ultrasound image guidance in prostate external beam radiotherapy requires consistent alignment between probe and prostate at each session during patient set…

eess.IV2020★ 5 cited

Longitudinal Image Registration with Temporal-order and Subject-specificity Discrimination

Qianye Yang, Yunguan Fu, Francesco Giganti +6

Morphological analysis of longitudinal MR images plays a key role in monitoring disease progression for prostate cancer patients, who are placed under an active surveillance progra…

cs.CV2020

Multimodality Biomedical Image Registration using Free Point Transformer Networks

Zachary M. C. Baum, Yipeng Hu, Dean C. Barratt

We describe a point-set registration algorithm based on a novel free point transformer (FPT) network, designed for points extracted from multimodal biomedical images for registrati…

eess.IV2020★ 3 cited

Image quality assessment for closed-loop computer-assisted lung ultrasound

Zachary M C Baum, Ester Bonmati, Lorenzo Cristoni +8

We describe a novel, two-stage computer assistance system for lung anomaly detection using ultrasound imaging in the intensive care setting to improve operator performance and pati…

cs.LG2020

Prostate motion modelling using biomechanically-trained deep neural networks on unstructured nodes

Shaheer U. Saeed, Zeike A. Taylor, Mark A. Pinnock +3

In this paper, we propose to train deep neural networks with biomechanical simulations, to predict the prostate motion encountered during ultrasound-guided interventions. In this a…