39 citations · 51 across the 9 of their papers we have counts for
3 papers · 1 filter
Learning semantic image quality for fetal ultrasound from noisy ranking annotation
Manxi Lin, Jakob Ambsdorf, Emilie Pi Fogtmann Sejer +9
We introduce the notion of semantic image quality for applications where image quality relies on semantic requirements. Working in fetal ultrasound, where ranking is challenging an…
Removing confounding information from fetal ultrasound images
Kamil Mikolaj, Manxi Lin, Zahra Bashir +4
Confounding information in the form of text or markings embedded in medical images can severely affect the training of diagnostic deep learning algorithms. However, data collected…
Explainable fetal ultrasound quality assessment with progressive concept bottleneck models
Manxi Lin, Aasa Feragen, Kamil Mikolaj +3
The quality of fetal ultrasound screening scans directly influences the precision of biometric measurements. However, acquiring high-quality scans is labor-intensive and highly rel…