output
20152025
most citedStandardized Assessment of Automatic Segmentation of White Matter Hyperintensities and Results of the WMH Segmentation Challenge

309 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

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Showing eess.IVShow all

6 papers · 1 filter

eess.IV2022

BiometryNet: Landmark-based Fetal Biometry Estimation from Standard Ultrasound Planes

Netanell Avisdris, Leo Joskowicz, Brian Dromey +5

Fetal growth assessment from ultrasound is based on a few biometric measurements that are performed manually and assessed relative to the expected gestational age. Reliable biometr…

eess.IV2022★ 51 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★ 27 cited

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…

eess.IV2021★ 1 cited

Volume of hyperintense inflammation (VHI): a deep learning-enabled quantitative imaging biomarker of inflammation load in spondyloarthritis

Carolyna Hepburn, Alexis Jones, Alan Bainbridge +6

Short inversion time inversion recovery (STIR) MRI is widely used in clinical practice to identify and quantify inflammation in axial spondyloarthritis. However, assessment of STIR…

eess.IV2021★ 32 cited

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…

eess.IV2021★ 31 cited

Intrapapillary Capillary Loop Classification in Magnification Endoscopy: Open Dataset and Baseline Methodology

Luis C. Garcia-Peraza-Herrera, Martin Everson, Laurence Lovat +6

Purpose. Early squamous cell neoplasia (ESCN) in the oesophagus is a highly treatable condition. Lesions confined to the mucosal layer can be curatively treated endoscopically. We…