Feb 13, 2024 · We design a robust coarse-to-fine model that ranks images based on their semantic image quality and endow our predicted rankings with an uncertainty estimate.

Our model is built on the assumption that annotated image quality rankings are noisy. This is confirmed by the intra-rater consistency for annotator A1 ...

Feb 13, 2024 · Working in fetal ultrasound, where ranking is challenging and annotations are noisy, we design a robust coarse-to-fine model that ranks images ...

Feb 13, 2024 · A robust coarse-to-fine model is designed that ranks images based on their semantic image quality and endow the authors' predicted rankings with an uncertainty ...

May 27, 2024 · We design a robust coarse-to-fine model that ranks images based on their semantic image quality and endow our predicted rankings with an uncertainty estimate.

This paper deals with the semantic enrichment of automatic annotations of images. Since it par-tially tackles the Semantic Gap Problem, seman-tic image ...

Dive into the research topics of 'Learning Semantic Image Quality for Fetal Ultrasound from Noisy Ranking Annotation'. Together they form a unique fingerprint.

We introduce the notion of semantic image quality for applications where image quality relies on semantic requirements. Working in fetal ultrasound, ...

Feb 13, 2024 · The denoising Generative Adversarial Network (GAN) proposed in this study demonstrates effective removal of speckle noise from B-mode ultrasound ...

Co-authors ; Learning semantic image quality for fetal ultrasound from noisy ranking annotation. M Lin*, J Ambsdorf*, EPF Sejer, Z Bashir, CK Wong, P Pegios, A ...