activity
20202022
most citedImage quality assessment for machine learning tasks using meta-reinforcement learning

51 citations · 103 across the 8 of their papers we have counts for

collaborators

9 papers

eess.IV2022

Meta-Learning Initializations for Interactive Medical Image Registration

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

We present a meta-learning framework for interactive medical image registration. Our proposed framework comprises three components: a learning-based medical image registration algo…

eess.IV202251 cited

Image quality assessment for machine learning tasks using meta-reinforcement learning

Shaheer U. Saeed, Yunguan Fu, Vasilis Stavrinides +8

In this paper, we consider image quality assessment (IQA) as a measure of how images are amenable with respect to a given downstream task, or task amenability. When the task is per…

eess.IV2021

Real-time multimodal image registration with partial intraoperative point-set data

Zachary M C Baum, Yipeng Hu, Dean C Barratt

We present Free Point Transformer (FPT) - a deep neural network architecture for non-rigid point-set registration. Consisting of two modules, a global feature extraction module and…

cs.CV2021

Adaptable image quality assessment using meta-reinforcement learning of task amenability

Shaheer U. Saeed, Yunguan Fu, Vasilis Stavrinides +8

The performance of many medical image analysis tasks are strongly associated with image data quality. When developing modern deep learning algorithms, rather than relying on subjec…

cs.LG20211 cited

Learning image quality assessment by reinforcing task amenable data selection

Shaheer U. Saeed, Yunguan Fu, Zachary M. C. Baum +6

In this paper, we consider a type of image quality assessment as a task-specific measurement, which can be used to select images that are more amenable to a given target task, such…

eess.IV202047 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.