A survey of crowdsourcing in medical image analysis

SN Ørting, A Doyle, A van Hilten, M Hirth… - Human …, 2020 - 104.237.144.41
Rapid advances in image processing capabilities have been seen across many domains,
fostered by the application of machine learning algorithms to" big-data". However, within the …

Labelling instructions matter in biomedical image analysis

T Rädsch, A Reinke, V Weru, MD Tizabi… - Nature Machine …, 2023 - nature.com
Biomedical image analysis algorithm validation depends on high-quality annotation of
reference datasets, for which labelling instructions are key. Despite their importance, their …

A survey of crowdsourcing in medical image analysis

S Ørting, A Doyle, A van Hilten, M Hirth, O Inel… - arXiv preprint arXiv …, 2019 - arxiv.org
Rapid advances in image processing capabilities have been seen across many domains,
fostered by the application of machine learning algorithms to" big-data". However, within the …

[图书][B] Academic crowdsourcing in the humanities: Crowds, communities and co-production

M Hedges, S Dunn - 2017 - books.google.com
Academic Crowdsourcing in the Humanities lays the foundations for a theoretical framework
to understand the value of crowdsourcing, an avenue that is increasingly becoming …

Crowdsourcing labels for pathological patterns in CT lung scans: can non-experts contribute expert-quality ground truth?

AQ O'Neil, JT Murchison, EJR van Beek… - … Imaging and Computer …, 2017 - Springer
This paper investigates what quality of ground truth might be obtained when crowdsourcing
specialist medical imaging ground truth from non-experts. Following basic tuition, 34 …

SwifTree: Interactive extraction of 3D trees supporting gaming and crowdsourcing

M Huang, G Hamarneh - … Imaging and Computer Assisted Stenting, and …, 2017 - Springer
Abstract Analysis of vascular and airway trees of circulatory and respiratory systems is
important for many clinical applications. Automatic segmentation of these tree-like structures …

Fine-tuning deep learning by crowd participation

S Albarqouni - IEEE pulse, 2018 - ieeexplore.ieee.org
One of the major challenges currently facing researchers in applying deep learning (DL)
models to medical image analysis is the limited amount of annotated data. Collecting such …

A Survey of Crowdsourcing in Medical Image Analysis

A Doyle, A van Hilten, M Hirth… - Human …, 2020 - nottingham-repository.worktribe.com
Rapid advances in image processing capabilities have been seen across many domains,
fostered by the application of machine learning algorithms to" big-data". However, within the …

Interactive extraction of 3D trees from medical images supporting gaming and crowdsourcing

M Huang - 2017 - summit.sfu.ca
Analysis of vascular and airway trees of circulatory and respiratory systems is important for a
wide range of clinical applications. Automatic segmentation of these tree-like structures from …