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20172022
most citedFreehand Ultrasound Image Simulation with Spatially-Conditioned Generative Adversarial Networks

77 citations · 213 across the 16 of their papers we have counts for

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7 papers · 1 filter

cs.CV2022

Active learning using adaptable task-based prioritisation

Shaheer U. Saeed, João Ramalhinho, Mark Pinnock +9

Supervised machine learning-based medical image computing applications necessitate expert label curation, while unlabelled image data might be relatively abundant. Active learning…

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.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…

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…

cs.CV2018

Weakly-Supervised Convolutional Neural Networks for Multimodal Image Registration

Yipeng Hu, Marc Modat, Eli Gibson +11

One of the fundamental challenges in supervised learning for multimodal image registration is the lack of ground-truth for voxel-level spatial correspondence. This work describes a…

cs.CV201725 cited

Automatic segmentation method of pelvic floor levator hiatus in ultrasound using a self-normalising neural network

Ester Bonmati, Yipeng Hu, Nikhil Sindhwani +5

Segmentation of the levator hiatus in ultrasound allows to extract biometrics which are of importance for pelvic floor disorder assessment. In this work, we present a fully automat…