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Crowdsourced emphysema assessment

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

Classification of emphysema patterns is believed to be useful for improved diagnosis and prognosis of chronic obstructive pulmonary disease. Emphysema patterns can be assessed visually on lung CT scans. Visual assessment is a complex and time-consuming task performed by experts, making it unsuitable for obtaining large amounts of labeled data. We investigate if visual assessment of emphysema can be framed as an image similarity task that does not require expert. Substituting untrained annotators for experts makes it possible to label data sets much faster and at a lower cost. We use crowd annotators to gather similarity triplets and use t-distributed stochastic triplet embedding to learn an embedding. The quality of the embedding is evaluated by predicting expert assessed emphysema patterns. We find that although performance varies due to low quality triplets and randomness in the embedding, we still achieve a median F1 score of 0.58 for prediction of four patterns.

OriginalsprogEngelsk
TitelIntravascular Imaging and Computer Assisted Stenting, and Large-Scale Annotation of Biomedical Data and Expert Label Synthesis : 6th Joint International Workshops, CVII-STENT 2017 and Second International Workshop, LABELS 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 10–14, 2017, Proceedings
RedaktørerM. Jorge Cardoso, Tal Arbel, Su-Lin Lee, Veronika Cheplygina, Simone Balocco, Diana Mateus, Guillaume Zahnd, Lena Maier-Hein, Stefanie Dermirci, Eric Granger, Luc Duong, Marc-André Carbonneau, Shadi Albarquoni, Gustaco Carneiro
Antal sider10
ForlagSpringer
Publikationsdato2017
Sider126-135
ISBN (Trykt)978-3-319-67533-6
ISBN (Elektronisk)978-3-319-67534-3
DOI
StatusUdgivet - 2017
Begivenhed2nd International Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis - Québec City, Canada
Varighed: 10 sep. 201714 sep. 2017
Konferencens nummer: 2

Workshop

Workshop2nd International Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis
Nummer2
LandCanada
ByQuébec City
Periode10/09/201714/09/2017
NavnLecture notes in computer science
Vol/bind10552
ISSN0302-9743

ID: 184144420